From c186adda670e60b76e04c19473502eb590a9622c Mon Sep 17 00:00:00 2001 From: Alexander Poddubny <143108850+nv-apoddubny@users.noreply.github.com> Date: Tue, 8 Oct 2024 00:31:56 -0700 Subject: [PATCH 001/111] Adds buildspec for mirroring job (#1177) # Description Adding a buildspec for repo mirroring job: - Mirrors a branch - Uses personal github token - Target repo and branch names are coming from env variables - Pushing code with force --- .github/workflows/mirror-buildspec.yml | 15 +++++++++++++++ 1 file changed, 15 insertions(+) create mode 100644 .github/workflows/mirror-buildspec.yml diff --git a/.github/workflows/mirror-buildspec.yml b/.github/workflows/mirror-buildspec.yml new file mode 100644 index 0000000000..a537f5bfd9 --- /dev/null +++ b/.github/workflows/mirror-buildspec.yml @@ -0,0 +1,15 @@ +version: 0.2 + +phases: + install: + runtime-versions: + nodejs: 14 + pre_build: + commands: + - git config --global user.name "Isaac LAB CI Bot" + - git config --global user.email "isaac-lab-ci-bot@nvidia.com" + build: + commands: + - git remote set-url origin https://github.com/${TARGET_REPO}.git + - git checkout $SOURCE_BRANCH + - git push --force https://$GITHUB_TOKEN@github.com/${TARGET_REPO}.git $SOURCE_BRANCH:$TARGET_BRANCH From c81550acc11ba430b9dcbc42cf6586c22e00ee9a Mon Sep 17 00:00:00 2001 From: glvov-bdai Date: Tue, 8 Oct 2024 03:46:04 -0400 Subject: [PATCH 002/111] Fix Cartpole Manager-based Vision-Based Environment Task Name in Docs (#1176) # Description Name of Cartpole Manager-based Vision-Based was incorrect in docs, changed to match the exact argument that should be passed as task to workflows ## Type of change - Bug fix (non-breaking change which fixes an issue) - This change requires a documentation update ## Checklist - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [x] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [x] I have added tests that prove my fix is effective or that my feature works - [x] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [x] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --- docs/source/overview/environments.rst | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/docs/source/overview/environments.rst b/docs/source/overview/environments.rst index 274292d5b3..f42f3c34a5 100644 --- a/docs/source/overview/environments.rst +++ b/docs/source/overview/environments.rst @@ -69,8 +69,8 @@ Classic environments that are based on IsaacGymEnvs implementation of MuJoCo-sty .. |humanoid-link| replace:: `Isaac-Humanoid-v0 `__ .. |ant-link| replace:: `Isaac-Ant-v0 `__ .. |cartpole-link| replace:: `Isaac-Cartpole-v0 `__ -.. |cartpole-rgb-link| replace:: `Isaac-Cartpole-RGB-v0 `__ -.. |cartpole-depth-link| replace:: `Isaac-Cartpole-Depth-v0 `__ +.. |cartpole-rgb-link| replace:: `Isaac-Cartpole-RGB-Camera-v0 `__ +.. |cartpole-depth-link| replace:: `Isaac-Cartpole-Depth-Camera-v0 `__ .. |humanoid-direct-link| replace:: `Isaac-Humanoid-Direct-v0 `__ .. |ant-direct-link| replace:: `Isaac-Ant-Direct-v0 `__ From d18f0c266be39998630aea0efc3853725b056715 Mon Sep 17 00:00:00 2001 From: Toni-SM Date: Tue, 8 Oct 2024 04:05:32 -0400 Subject: [PATCH 003/111] Fixes Isaac Sim executable on pip installation (#1172) # Description This PR fix https://github.com/isaac-sim/IsaacLab/issues/831 by taking into account the Isaac Sim installation using PIP - Bug fix (non-breaking change which fixes an issue) ## Checklist - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [ ] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [ ] I have added tests that prove my fix is effective or that my feature works - [ ] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [x] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --- isaaclab.bat | 2 +- isaaclab.sh | 10 ++++++++-- 2 files changed, 9 insertions(+), 3 deletions(-) diff --git a/isaaclab.bat b/isaaclab.bat index 53674d71f8..b415ef1a13 100644 --- a/isaaclab.bat +++ b/isaaclab.bat @@ -81,7 +81,7 @@ if errorlevel 1 ( set isaacsim_exe=!isaac_path!\isaac-sim.bat ) else ( rem if isaac sim installed from pip - set isaacsim_exe=isaacsim + set isaacsim_exe=isaacsim omni.isaac.sim ) rem check if there is a python path available if not exist "%isaacsim_exe%" ( diff --git a/isaaclab.sh b/isaaclab.sh index 297424b9c2..a604706e70 100755 --- a/isaaclab.sh +++ b/isaaclab.sh @@ -90,8 +90,14 @@ extract_isaacsim_exe() { local isaacsim_exe=${isaac_path}/isaac-sim.sh # check if there is a python path available if [ ! -f "${isaacsim_exe}" ]; then - echo "[ERROR] No Isaac Sim executable found at path: ${isaacsim_exe}" >&2 - exit 1 + # check for installation using Isaac Sim pip + if [ $(python -m pip list | grep -c 'isaacsim-rl') -gt 0 ]; then + # Isaac Sim - Python packages entry point + local isaacsim_exe="isaacsim omni.isaac.sim" + else + echo "[ERROR] No Isaac Sim executable found at path: ${isaac_path}" >&2 + exit 1 + fi fi # return the result echo ${isaacsim_exe} From 4a773d91297c193832f8b58cda663c577fe6cfc4 Mon Sep 17 00:00:00 2001 From: Pascal Roth <57946385+pascal-roth@users.noreply.github.com> Date: Wed, 9 Oct 2024 11:30:09 +0200 Subject: [PATCH 004/111] Fixes the event for randomizing rigid body material (#1140) # Description The current friction randomization event only selects a single random number in the given range and does not vary them. With the given PR, this is getting fixed, and there is a sampling of the entire given range. ## Type of change - Bug fix (non-breaking change which fixes an issue) ## Screenshots | Before | After | | ------ | ----- | | ![Screenshot from 2024-10-03 22-26-49](https://github.com/user-attachments/assets/d13f86ee-c776-4046-af2e-46be8f271a00) | ![Screenshot from 2024-10-03 22-27-15](https://github.com/user-attachments/assets/cf0a536d-20d0-47f1-b580-25241049cdd4) | ## Checklist - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [x] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [ ] I have added tests that prove my fix is effective or that my feature works - [x] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [x] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --------- Co-authored-by: Mayank Mittal --- .../omni.isaac.lab/config/extension.toml | 2 +- .../omni.isaac.lab/docs/CHANGELOG.rst | 10 ++ .../omni/isaac/lab/envs/mdp/events.py | 159 +++++++++++------- 3 files changed, 109 insertions(+), 62 deletions(-) diff --git a/source/extensions/omni.isaac.lab/config/extension.toml b/source/extensions/omni.isaac.lab/config/extension.toml index 473b7a0986..b8b9a8c0ef 100644 --- a/source/extensions/omni.isaac.lab/config/extension.toml +++ b/source/extensions/omni.isaac.lab/config/extension.toml @@ -1,7 +1,7 @@ [package] # Note: Semantic Versioning is used: https://semver.org/ -version = "0.24.19" +version = "0.24.20" # Description title = "Isaac Lab framework for Robot Learning" diff --git a/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst b/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst index 2e67c3708c..9437a7aaf2 100644 --- a/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst +++ b/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst @@ -1,6 +1,16 @@ Changelog --------- +0.24.20 (2024-10-07) +~~~~~~~~~~~~~~~~~~~~ + +Fixes +^^^^^ + +* Fixed the :meth:`omni.isaac.lab.envs.mdp.events.randomize_rigid_body_material` function to + correctly sample friction and restitution from the given ranges. + + 0.24.19 (2024-10-05) ~~~~~~~~~~~~~~~~~~~~ diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/events.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/events.py index 8f2d737eb7..3eaeb650f9 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/events.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/events.py @@ -14,7 +14,6 @@ from __future__ import annotations -import numpy as np import torch from typing import TYPE_CHECKING, Literal @@ -25,22 +24,14 @@ import omni.isaac.lab.utils.math as math_utils from omni.isaac.lab.actuators import ImplicitActuator from omni.isaac.lab.assets import Articulation, DeformableObject, RigidObject -from omni.isaac.lab.managers import SceneEntityCfg +from omni.isaac.lab.managers import EventTermCfg, ManagerTermBase, SceneEntityCfg from omni.isaac.lab.terrains import TerrainImporter if TYPE_CHECKING: from omni.isaac.lab.envs import ManagerBasedEnv -def randomize_rigid_body_material( - env: ManagerBasedEnv, - env_ids: torch.Tensor | None, - static_friction_range: tuple[float, float], - dynamic_friction_range: tuple[float, float], - restitution_range: tuple[float, float], - num_buckets: int, - asset_cfg: SceneEntityCfg, -): +class randomize_rigid_body_material(ManagerTermBase): """Randomize the physics materials on all geometries of the asset. This function creates a set of physics materials with random static friction, dynamic friction, and restitution @@ -53,6 +44,10 @@ def randomize_rigid_body_material( all bodies). The integer values are used as indices to select the material properties from the material buckets. + If the flag ``make_consistent`` is set to ``True``, the dynamic friction is set to be less than or equal to + the static friction. This obeys the physics constraint on friction values. However, it may not always be + essential for the application. Thus, the flag is set to ``False`` by default. + .. attention:: This function uses CPU tensors to assign the material properties. It is recommended to use this function only during the initialization of the environment. Otherwise, it may lead to a significant performance @@ -60,69 +55,111 @@ def randomize_rigid_body_material( .. note:: PhysX only allows 64000 unique physics materials in the scene. If the number of materials exceeds this - limit, the simulation will crash. + limit, the simulation will crash. Due to this reason, we sample the materials only once during initialization. + Afterwards, these materials are randomly assigned to the geometries of the asset. """ - # extract the used quantities (to enable type-hinting) - asset: RigidObject | Articulation = env.scene[asset_cfg.name] - if not isinstance(asset, (RigidObject, Articulation)): - raise ValueError( - f"Randomization term 'randomize_rigid_body_material' not supported for asset: '{asset_cfg.name}'" - f" with type: '{type(asset)}'." - ) + def __init__(self, cfg: EventTermCfg, env: ManagerBasedEnv): + """Initialize the term. - # resolve environment ids - if env_ids is None: - env_ids = torch.arange(env.scene.num_envs, device="cpu") - else: - env_ids = env_ids.cpu() - - # retrieve material buffer - materials = asset.root_physx_view.get_material_properties() + Args: + cfg: The configuration of the event term. + env: The environment instance. - # sample material properties from the given ranges - material_samples = np.zeros(materials[env_ids].shape) - material_samples[..., 0] = np.random.uniform(*static_friction_range) - material_samples[..., 1] = np.random.uniform(*dynamic_friction_range) - material_samples[..., 2] = np.random.uniform(*restitution_range) + Raises: + ValueError: If the asset is not a RigidObject or an Articulation. + """ + super().__init__(cfg, env) - # create uniform range tensor for bucketing - lo = np.array([static_friction_range[0], dynamic_friction_range[0], restitution_range[0]]) - hi = np.array([static_friction_range[1], dynamic_friction_range[1], restitution_range[1]]) + # extract the used quantities (to enable type-hinting) + self.asset_cfg: SceneEntityCfg = cfg.params["asset_cfg"] + self.asset: RigidObject | Articulation = env.scene[self.asset_cfg.name] - # to avoid 64k material limit in physx, we bucket materials by binning randomized material properties - # into buckets based on the number of buckets specified - for d in range(3): - buckets = np.array([(hi[d] - lo[d]) * i / num_buckets + lo[d] for i in range(num_buckets)]) - material_samples[..., d] = buckets[np.searchsorted(buckets, material_samples[..., d]) - 1] + if not isinstance(self.asset, (RigidObject, Articulation)): + raise ValueError( + f"Randomization term 'randomize_rigid_body_material' not supported for asset: '{self.asset_cfg.name}'" + f" with type: '{type(self.asset)}'." + ) - # update material buffer with new samples - if isinstance(asset, Articulation) and asset_cfg.body_ids != slice(None): # obtain number of shapes per body (needed for indexing the material properties correctly) # note: this is a workaround since the Articulation does not provide a direct way to obtain the number of shapes # per body. We use the physics simulation view to obtain the number of shapes per body. - num_shapes_per_body = [] - for link_path in asset.root_physx_view.link_paths[0]: - link_physx_view = asset._physics_sim_view.create_rigid_body_view(link_path) # type: ignore - num_shapes_per_body.append(link_physx_view.max_shapes) + if isinstance(self.asset, Articulation) and self.asset_cfg.body_ids != slice(None): + self.num_shapes_per_body = [] + for link_path in self.asset.root_physx_view.link_paths[0]: + link_physx_view = self.asset._physics_sim_view.create_rigid_body_view(link_path) # type: ignore + self.num_shapes_per_body.append(link_physx_view.max_shapes) + # ensure the parsing is correct + num_shapes = sum(self.num_shapes_per_body) + expected_shapes = self.asset.root_physx_view.max_shapes + if num_shapes != expected_shapes: + raise ValueError( + "Randomization term 'randomize_rigid_body_material' failed to parse the number of shapes per body." + f" Expected total shapes: {expected_shapes}, but got: {num_shapes}." + ) + else: + # in this case, we don't need to do special indexing + self.num_shapes_per_body = None + + # obtain parameters for sampling friction and restitution values + static_friction_range = cfg.params.get("static_friction_range", (1.0, 1.0)) + dynamic_friction_range = cfg.params.get("dynamic_friction_range", (1.0, 1.0)) + restitution_range = cfg.params.get("restitution_range", (0.0, 0.0)) + num_buckets = int(cfg.params.get("num_buckets", 1)) # sample material properties from the given ranges - for body_id in asset_cfg.body_ids: - # start index of shape - start_idx = sum(num_shapes_per_body[:body_id]) - # end index of shape - end_idx = start_idx + num_shapes_per_body[body_id] - # assign the new materials - # material ids are of shape: num_env_ids x num_shapes - # material_buckets are of shape: num_buckets x 3 - materials[env_ids, start_idx:end_idx] = torch.from_numpy(material_samples[:, start_idx:end_idx]).to( - dtype=torch.float - ) - else: - materials[env_ids] = torch.from_numpy(material_samples).to(dtype=torch.float) + # note: we only sample the materials once during initialization + # afterwards these are randomly assigned to the geometries of the asset + range_list = [static_friction_range, dynamic_friction_range, restitution_range] + ranges = torch.tensor(range_list, device="cpu") + self.material_buckets = math_utils.sample_uniform(ranges[:, 0], ranges[:, 1], (num_buckets, 3), device="cpu") + + # ensure dynamic friction is always less than static friction + make_consistent = cfg.params.get("make_consistent", False) + if make_consistent: + self.material_buckets[:, 1] = torch.min(self.material_buckets[:, 0], self.material_buckets[:, 1]) + + def __call__( + self, + env: ManagerBasedEnv, + env_ids: torch.Tensor | None, + static_friction_range: tuple[float, float], + dynamic_friction_range: tuple[float, float], + restitution_range: tuple[float, float], + num_buckets: int, + asset_cfg: SceneEntityCfg, + make_consistent: bool = False, + ): + # resolve environment ids + if env_ids is None: + env_ids = torch.arange(env.scene.num_envs, device="cpu") + else: + env_ids = env_ids.cpu() + + # randomly assign material IDs to the geometries + total_num_shapes = self.asset.root_physx_view.max_shapes + bucket_ids = torch.randint(0, num_buckets, (len(env_ids), total_num_shapes), device="cpu") + material_samples = self.material_buckets[bucket_ids] + + # retrieve material buffer from the physics simulation + materials = self.asset.root_physx_view.get_material_properties() + + # update material buffer with new samples + if self.num_shapes_per_body is not None: + # sample material properties from the given ranges + for body_id in self.asset_cfg.body_ids: + # obtain indices of shapes for the body + start_idx = sum(self.num_shapes_per_body[:body_id]) + end_idx = start_idx + self.num_shapes_per_body[body_id] + # assign the new materials + # material samples are of shape: num_env_ids x total_num_shapes x 3 + materials[env_ids, start_idx:end_idx] = material_samples[:, start_idx:end_idx] + else: + # assign all the materials + materials[env_ids] = material_samples[:] - # apply to simulation - asset.root_physx_view.set_material_properties(materials, env_ids) + # apply to simulation + self.asset.root_physx_view.set_material_properties(materials, env_ids) def randomize_rigid_body_mass( From f6741f31d7e0f525466a5e4b7d13bcb9913bb6fc Mon Sep 17 00:00:00 2001 From: Mayank Mittal <12863862+Mayankm96@users.noreply.github.com> Date: Wed, 9 Oct 2024 11:54:30 +0200 Subject: [PATCH 005/111] Adds configuration classes for spawning different assets at prim paths (#1164) # Description This MR adds configuration classes that allow spawning different assets at the resolved prim paths. For instance, for the prim path expression "/World/envs/env_.*/Object", these configuration instances allow spawning a different type of prim at individual path locations. Fixes #186 ## Type of change - New feature (non-breaking change which adds functionality) ## Checklist - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [x] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [ ] I have added tests that prove my fix is effective or that my feature works - [x] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [x] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --------- Signed-off-by: Mayank Mittal <12863862+Mayankm96@users.noreply.github.com> Co-authored-by: David Hoeller --- docs/source/_static/demos/multi_asset.jpg | Bin 0 -> 559660 bytes .../api/lab/omni.isaac.lab.sim.spawners.rst | 25 ++ docs/source/how-to/index.rst | 11 + docs/source/how-to/multi_asset_spawning.rst | 101 ++++++++ docs/source/overview/showroom.rst | 45 +++- .../omni.isaac.lab/config/extension.toml | 2 +- .../omni.isaac.lab/docs/CHANGELOG.rst | 10 + .../omni/isaac/lab/scene/interactive_scene.py | 25 +- .../omni/isaac/lab/sim/spawners/__init__.py | 1 + .../isaac/lab/sim/spawners/spawner_cfg.py | 5 - .../lab/sim/spawners/wrappers/__init__.py | 14 + .../lab/sim/spawners/wrappers/wrappers.py | 169 ++++++++++++ .../lab/sim/spawners/wrappers/wrappers_cfg.py | 67 +++++ .../test/sim/test_spawn_wrappers.py | 191 ++++++++++++++ source/standalone/demos/multi_asset.py | 244 ++++++++++++++++++ 15 files changed, 886 insertions(+), 24 deletions(-) create mode 100644 docs/source/_static/demos/multi_asset.jpg create mode 100644 docs/source/how-to/multi_asset_spawning.rst create mode 100644 source/extensions/omni.isaac.lab/omni/isaac/lab/sim/spawners/wrappers/__init__.py create mode 100644 source/extensions/omni.isaac.lab/omni/isaac/lab/sim/spawners/wrappers/wrappers.py create mode 100644 source/extensions/omni.isaac.lab/omni/isaac/lab/sim/spawners/wrappers/wrappers_cfg.py create mode 100644 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a/docs/source/api/lab/omni.isaac.lab.sim.spawners.rst +++ b/docs/source/api/lab/omni.isaac.lab.sim.spawners.rst @@ -13,6 +13,7 @@ sensors from_files materials + wrappers .. rubric:: Classes @@ -302,3 +303,27 @@ Physical Materials .. autoclass:: DeformableBodyMaterialCfg :members: :exclude-members: __init__, func + +Wrappers +-------- + +.. automodule:: omni.isaac.lab.sim.spawners.wrappers + + .. rubric:: Classes + + .. autosummary:: + + MultiAssetSpawnerCfg + MultiUsdFileCfg + +.. autofunction:: spawn_multi_asset + +.. autoclass:: MultiAssetSpawnerCfg + :members: + :exclude-members: __init__, func + +.. autofunction:: spawn_multi_usd_file + +.. autoclass:: MultiUsdFileCfg + :members: + :exclude-members: __init__, func diff --git a/docs/source/how-to/index.rst b/docs/source/how-to/index.rst index 893b3a69b3..4b5c426d82 100644 --- a/docs/source/how-to/index.rst +++ b/docs/source/how-to/index.rst @@ -36,6 +36,17 @@ a fixed base robot. This guide goes over the various considerations and steps to make_fixed_prim +Spawning Multiple Assets +------------------------ + +This guide explains how to import and configure different assets in each environment. This is +useful when you want to create diverse environments with different objects. + +.. toctree:: + :maxdepth: 1 + + multi_asset_spawning + Saving Camera Output -------------------- diff --git a/docs/source/how-to/multi_asset_spawning.rst b/docs/source/how-to/multi_asset_spawning.rst new file mode 100644 index 0000000000..9f74e39f6b --- /dev/null +++ b/docs/source/how-to/multi_asset_spawning.rst @@ -0,0 +1,101 @@ +Spawning Multiple Assets +======================== + +.. currentmodule:: omni.isaac.lab + +Typical, spawning configurations (introduced in the :ref:`tutorial-spawn-prims` tutorial) copy the same +asset (or USD primitive) across the different resolved prim paths from the expressions. +For instance, if the user specifies to spawn the asset at "/World/Table\_.*/Object", the same +asset is created at the paths "/World/Table_0/Object", "/World/Table_1/Object" and so on. + +However, at times, it might be desirable to spawn different assets under the prim paths to +ensure a diversity in the simulation. This guide describes how to create different assets under +each prim path using the spawning functionality. + +The sample script ``multi_asset.py`` is used as a reference, located in the +``IsaacLab/source/standalone/demos`` directory. + +.. dropdown:: Code for multi_asset.py + :icon: code + + .. literalinclude:: ../../../source/standalone/demos/multi_asset.py + :language: python + :emphasize-lines: 101-123, 130-149 + :linenos: + +This script creates multiple environments, where each environment has a rigid object that is either a cone, +a cube, or a sphere, and an articulation that is either the ANYmal-C or ANYmal-D robot. + +.. image:: ../_static/demos/multi_asset.jpg + :width: 100% + :alt: result of multi_asset.py + +Using Multi-Asset Spawning Functions +------------------------------------ + +It is possible to spawn different assets and USDs in each environment using the spawners +:class:`~sim.spawners.wrappers.MultiAssetSpawnerCfg` and :class:`~sim.spawners.wrappers.MultiUsdFileCfg`: + +* We set the spawn configuration in :class:`~assets.RigidObjectCfg` to be + :class:`~sim.spawners.wrappers.MultiAssetSpawnerCfg`: + + .. literalinclude:: ../../../source/standalone/demos/multi_asset.py + :language: python + :lines: 99-125 + :dedent: + + This function allows you to define a list of different assets that can be spawned as rigid objects. + When :attr:`~sim.spawners.wrappers.MultiAssetSpawnerCfg.random_choice` is set to True, one asset from the list + is randomly selected and spawned at the specified prim path. + +* Similarly, we set the spawn configuration in :class:`~assets.ArticulationCfg` to be + :class:`~sim.spawners.wrappers.MultiUsdFileCfg`: + + .. literalinclude:: ../../../source/standalone/demos/multi_asset.py + :language: python + :lines: 128-161 + :dedent: + + Similar to before, this configuration allows the selection of different USD files representing articulated assets. + + +Things to Note +-------------- + +Similar asset structuring +~~~~~~~~~~~~~~~~~~~~~~~~~ + +While spawning and handling multiple assets using the same physics interface (the rigid object or articulation classes), +it is essential to have the assets at all the prim locations follow a similar structure. In case of an articulation, +this means that they all must have the same number of links and joints, the same number of collision bodies and +the same names for them. If that is not the case, the physics parsing of the prims can get affected and fail. + +The main purpose of this functionality is to enable the user to create randomized versions of the same asset, +for example robots with different link lengths, or rigid objects with different collider shapes. + +Disabling physics replication in interactive scene +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +By default, the flag :attr:`scene.InteractiveScene.replicate_physics` is set to True. This flag informs the physics +engine that the simulation environments are copies of one another so it just needs to parse the first environment +to understand the entire simulation scene. This helps speed up the simulation scene parsing. + +However, in the case of spawning different assets in different environments, this assumption does not hold +anymore. Hence the flag :attr:`scene.InteractiveScene.replicate_physics` must be disabled. + +.. literalinclude:: ../../../source/standalone/demos/multi_asset.py + :language: python + :lines: 221-224 + :dedent: + +The Code Execution +------------------ + +To execute the script with multiple environments and randomized assets, use the following command: + +.. code-block:: bash + + ./isaaclab.sh -p source/standalone/demos/multi_asset.py --num_envs 2048 + +This command runs the simulation with 2048 environments, each with randomly selected assets. +To stop the simulation, you can close the window, or press ``Ctrl+C`` in the terminal. diff --git a/docs/source/overview/showroom.rst b/docs/source/overview/showroom.rst index d8ff7a933d..d3d86fd777 100644 --- a/docs/source/overview/showroom.rst +++ b/docs/source/overview/showroom.rst @@ -77,7 +77,7 @@ A few quick showroom scripts to run and checkout: :width: 100% :alt: Dexterous hands in Isaac Lab -- Spawn procedurally generated terrains with different configurations: +- Spawn different deformable (soft) bodies and let them fall from a height: .. tab-set:: :sync-group: os @@ -87,20 +87,20 @@ A few quick showroom scripts to run and checkout: .. code:: bash - ./isaaclab.sh -p source/standalone/demos/procedural_terrain.py + ./isaaclab.sh -p source/standalone/demos/deformables.py .. tab-item:: :icon:`fa-brands fa-windows` Windows :sync: windows .. code:: batch - isaaclab.bat -p source\standalone\demos\procedural_terrain.py + isaaclab.bat -p source\standalone\demos\deformables.py - .. image:: ../_static/demos/procedural_terrain.jpg + .. image:: ../_static/demos/deformables.jpg :width: 100% - :alt: Procedural Terrains in Isaac Lab + :alt: Deformable primitive-shaped objects in Isaac Lab -- Spawn different deformable (soft) bodies and let them fall from a height: +- Use the interactive scene and spawn varying assets in individual environments: .. tab-set:: :sync-group: os @@ -110,20 +110,43 @@ A few quick showroom scripts to run and checkout: .. code:: bash - ./isaaclab.sh -p source/standalone/demos/deformables.py + ./isaaclab.sh -p source/standalone/demos/multi_asset.py .. tab-item:: :icon:`fa-brands fa-windows` Windows :sync: windows .. code:: batch - isaaclab.bat -p source\standalone\demos\deformables.py + isaaclab.bat -p source\standalone\demos\multi_asset.py - .. image:: ../_static/demos/deformables.jpg + .. image:: ../_static/demos/multi_asset.jpg :width: 100% - :alt: Deformable primitive-shaped objects in Isaac Lab + :alt: Multiple assets managed through the same simulation handles + +- Create and spawn procedurally generated terrains with different configurations: + + .. tab-set:: + :sync-group: os + + .. tab-item:: :icon:`fa-brands fa-linux` Linux + :sync: linux + + .. code:: bash + + ./isaaclab.sh -p source/standalone/demos/procedural_terrain.py + + .. tab-item:: :icon:`fa-brands fa-windows` Windows + :sync: windows + + .. code:: batch + + isaaclab.bat -p source\standalone\demos\procedural_terrain.py + + .. image:: ../_static/demos/procedural_terrain.jpg + :width: 100% + :alt: Procedural Terrains in Isaac Lab -- Spawn multiple markers that are useful for visualizations: +- Define multiple markers that are useful for visualizations: .. tab-set:: :sync-group: os diff --git a/source/extensions/omni.isaac.lab/config/extension.toml b/source/extensions/omni.isaac.lab/config/extension.toml index b8b9a8c0ef..7e9225c2b3 100644 --- a/source/extensions/omni.isaac.lab/config/extension.toml +++ b/source/extensions/omni.isaac.lab/config/extension.toml @@ -1,7 +1,7 @@ [package] # Note: Semantic Versioning is used: https://semver.org/ -version = "0.24.20" +version = "0.25.0" # Description title = "Isaac Lab framework for Robot Learning" diff --git a/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst b/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst index 9437a7aaf2..b0fa66f629 100644 --- a/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst +++ b/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst @@ -1,6 +1,16 @@ Changelog --------- +0.25.0 (2024-10-06) +~~~~~~~~~~~~~~~~~~~ + +Added +^^^^^ + +* Added configuration classes for spawning assets from a list of individual asset configurations randomly + at the specified prim paths. + + 0.24.20 (2024-10-07) ~~~~~~~~~~~~~~~~~~~~ diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/scene/interactive_scene.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/scene/interactive_scene.py index c803f0e305..8c4b81aaff 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/scene/interactive_scene.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/scene/interactive_scene.py @@ -166,6 +166,18 @@ def clone_environments(self, copy_from_source: bool = False): If True, clones are independent copies of the source prim and won't reflect its changes (start-up time may increase). Defaults to False. """ + # check if user spawned different assets in individual environments + # this flag will be None if no multi asset is spawned + carb_settings_iface = carb.settings.get_settings() + has_multi_assets = carb_settings_iface.get("/isaaclab/spawn/multi_assets") + if has_multi_assets and self.cfg.replicate_physics: + carb.log_warn( + "Varying assets might have been spawned under different environments." + " However, the replicate physics flag is enabled in the 'InteractiveScene' configuration." + " This may adversely affect PhysX parsing. We recommend disabling this property." + ) + + # clone the environment env_origins = self.cloner.clone( source_prim_path=self.env_prim_paths[0], prim_paths=self.env_prim_paths, @@ -187,9 +199,6 @@ def filter_collisions(self, global_prim_paths: list[str] | None = None): global_prim_paths: A list of global prim paths to enable collisions with. Defaults to None, in which case no global prim paths are considered. """ - # obtain the current physics scene - physics_scene_prim_path = self.physics_scene_path - # validate paths in global prim paths if global_prim_paths is None: global_prim_paths = [] @@ -203,7 +212,7 @@ def filter_collisions(self, global_prim_paths: list[str] | None = None): # filter collisions within each environment instance self.cloner.filter_collisions( - physics_scene_prim_path, + self.physics_scene_path, "/World/collisions", self.env_prim_paths, global_paths=self._global_prim_paths, @@ -224,14 +233,16 @@ def __str__(self) -> str: """ @property - def physics_scene_path(self): - """Search the stage for the physics scene""" + def physics_scene_path(self) -> str: + """The path to the USD Physics Scene.""" if self._physics_scene_path is None: for prim in self.stage.Traverse(): if prim.HasAPI(PhysxSchema.PhysxSceneAPI): - self._physics_scene_path = prim.GetPrimPath() + self._physics_scene_path = prim.GetPrimPath().pathString carb.log_info(f"Physics scene prim path: {self._physics_scene_path}") break + if self._physics_scene_path is None: + raise RuntimeError("No physics scene found! Please make sure one exists.") return self._physics_scene_path @property diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/spawners/__init__.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/spawners/__init__.py index 851750f371..94b1245ab6 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/spawners/__init__.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/spawners/__init__.py @@ -61,3 +61,4 @@ class and the function call in a single line of code. from .sensors import * # noqa: F401, F403 from .shapes import * # noqa: F401, F403 from .spawner_cfg import * # noqa: F401, F403 +from .wrappers import * # noqa: F401, F403 diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/spawners/spawner_cfg.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/spawners/spawner_cfg.py index 089b38b29a..351b3cde96 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/spawners/spawner_cfg.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/spawners/spawner_cfg.py @@ -64,11 +64,6 @@ class SpawnerCfg: This parameter is only used when cloning prims. If False, then the asset will be inherited from the source prim, i.e. all USD changes to the source prim will be reflected in the cloned prims. - - .. versionadded:: 2023.1 - - This parameter is only supported from Isaac Sim 2023.1 onwards. If you are using an older - version of Isaac Sim, this parameter will be ignored. """ diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/spawners/wrappers/__init__.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/spawners/wrappers/__init__.py new file mode 100644 index 0000000000..f05d3e58c7 --- /dev/null +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/spawners/wrappers/__init__.py @@ -0,0 +1,14 @@ +# Copyright (c) 2022-2024, The Isaac Lab Project Developers. +# All rights reserved. +# +# SPDX-License-Identifier: BSD-3-Clause + +"""Sub-module for wrapping spawner configurations. + +Unlike the other spawner modules, this module provides a way to wrap multiple spawner configurations +into a single configuration. This is useful when the user wants to spawn multiple assets based on +different configurations. +""" + +from .wrappers import spawn_multi_asset, spawn_multi_usd_file +from .wrappers_cfg import MultiAssetSpawnerCfg, MultiUsdFileCfg diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/spawners/wrappers/wrappers.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/spawners/wrappers/wrappers.py new file mode 100644 index 0000000000..9040569e4a --- /dev/null +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/spawners/wrappers/wrappers.py @@ -0,0 +1,169 @@ +# Copyright (c) 2022-2024, The Isaac Lab Project Developers. +# All rights reserved. +# +# SPDX-License-Identifier: BSD-3-Clause + +from __future__ import annotations + +import random +import re +from typing import TYPE_CHECKING + +import carb +import omni.isaac.core.utils.prims as prim_utils +import omni.isaac.core.utils.stage as stage_utils +from pxr import Sdf, Usd + +import omni.isaac.lab.sim as sim_utils +from omni.isaac.lab.sim.spawners.from_files import UsdFileCfg + +if TYPE_CHECKING: + from . import wrappers_cfg + + +def spawn_multi_asset( + prim_path: str, + cfg: wrappers_cfg.MultiAssetSpawnerCfg, + translation: tuple[float, float, float] | None = None, + orientation: tuple[float, float, float, float] | None = None, +) -> Usd.Prim: + """Spawn multiple assets based on the provided configurations. + + This function spawns multiple assets based on the provided configurations. The assets are spawned + in the order they are provided in the list. If the :attr:`~MultiAssetSpawnerCfg.random_choice` parameter is + set to True, a random asset configuration is selected for each spawn. + + Args: + prim_path: The prim path to spawn the assets. + cfg: The configuration for spawning the assets. + translation: The translation of the spawned assets. Default is None. + orientation: The orientation of the spawned assets in (w, x, y, z) order. Default is None. + + Returns: + The created prim at the first prim path. + """ + # resolve: {SPAWN_NS}/AssetName + # note: this assumes that the spawn namespace already exists in the stage + root_path, asset_path = prim_path.rsplit("/", 1) + # check if input is a regex expression + # note: a valid prim path can only contain alphanumeric characters, underscores, and forward slashes + is_regex_expression = re.match(r"^[a-zA-Z0-9/_]+$", root_path) is None + + # resolve matching prims for source prim path expression + if is_regex_expression and root_path != "": + source_prim_paths = sim_utils.find_matching_prim_paths(root_path) + # if no matching prims are found, raise an error + if len(source_prim_paths) == 0: + raise RuntimeError( + f"Unable to find source prim path: '{root_path}'. Please create the prim before spawning." + ) + else: + source_prim_paths = [root_path] + + # find a free prim path to hold all the template prims + template_prim_path = stage_utils.get_next_free_path("/World/Template") + prim_utils.create_prim(template_prim_path, "Scope") + + # spawn everything first in a "Dataset" prim + proto_prim_paths = list() + for index, asset_cfg in enumerate(cfg.assets_cfg): + # append semantic tags if specified + if cfg.semantic_tags is not None: + if asset_cfg.semantic_tags is None: + asset_cfg.semantic_tags = cfg.semantic_tags + else: + asset_cfg.semantic_tags += cfg.semantic_tags + # override settings for properties + attr_names = ["mass_props", "rigid_props", "collision_props", "activate_contact_sensors", "deformable_props"] + for attr_name in attr_names: + attr_value = getattr(cfg, attr_name) + if hasattr(asset_cfg, attr_name) and attr_value is not None: + setattr(asset_cfg, attr_name, attr_value) + # spawn single instance + proto_prim_path = f"{template_prim_path}/Asset_{index:04d}" + asset_cfg.func(proto_prim_path, asset_cfg, translation=translation, orientation=orientation) + # append to proto prim paths + proto_prim_paths.append(proto_prim_path) + + # resolve prim paths for spawning and cloning + prim_paths = [f"{source_prim_path}/{asset_path}" for source_prim_path in source_prim_paths] + + # acquire stage + stage = stage_utils.get_current_stage() + + # manually clone prims if the source prim path is a regex expression + # note: unlike in the cloner API from Isaac Sim, we do not "reset" xforms on the copied prims. + # This is because the "spawn" calls during the creation of the proto prims already handles this operation. + with Sdf.ChangeBlock(): + for index, prim_path in enumerate(prim_paths): + # spawn single instance + env_spec = Sdf.CreatePrimInLayer(stage.GetRootLayer(), prim_path) + # randomly select an asset configuration + if cfg.random_choice: + proto_path = random.choice(proto_prim_paths) + else: + proto_path = proto_prim_paths[index % len(proto_prim_paths)] + # copy the proto prim + Sdf.CopySpec(env_spec.layer, Sdf.Path(proto_path), env_spec.layer, Sdf.Path(prim_path)) + + # delete the dataset prim after spawning + prim_utils.delete_prim(template_prim_path) + + # set carb setting to indicate Isaac Lab's environments that different prims have been spawned + # at varying prim paths. In this case, PhysX parser shouldn't optimize the stage parsing. + # the flag is mainly used to inform the user that they should disable `InteractiveScene.replicate_physics` + carb_settings_iface = carb.settings.get_settings() + carb_settings_iface.set_bool("/isaaclab/spawn/multi_assets", True) + + # return the prim + return prim_utils.get_prim_at_path(prim_paths[0]) + + +def spawn_multi_usd_file( + prim_path: str, + cfg: wrappers_cfg.MultiUsdFileCfg, + translation: tuple[float, float, float] | None = None, + orientation: tuple[float, float, float, float] | None = None, +) -> Usd.Prim: + """Spawn multiple USD files based on the provided configurations. + + This function creates configuration instances corresponding the individual USD files and + calls the :meth:`spawn_multi_asset` method to spawn them into the scene. + + Args: + prim_path: The prim path to spawn the assets. + cfg: The configuration for spawning the assets. + translation: The translation of the spawned assets. Default is None. + orientation: The orientation of the spawned assets in (w, x, y, z) order. Default is None. + + Returns: + The created prim at the first prim path. + """ + # needed here to avoid circular imports + from .wrappers_cfg import MultiAssetSpawnerCfg + + # parse all the usd files + if isinstance(cfg.usd_path, str): + usd_paths = [cfg.usd_path] + else: + usd_paths = cfg.usd_path + + # make a template usd config + usd_template_cfg = UsdFileCfg() + for attr_name, attr_value in cfg.__dict__.items(): + # skip names we know are not present + if attr_name in ["func", "usd_path", "random_choice"]: + continue + # set the attribute into the template + setattr(usd_template_cfg, attr_name, attr_value) + + # create multi asset configuration of USD files + multi_asset_cfg = MultiAssetSpawnerCfg(assets_cfg=[]) + for usd_path in usd_paths: + usd_cfg = usd_template_cfg.replace(usd_path=usd_path) + multi_asset_cfg.assets_cfg.append(usd_cfg) + # set random choice + multi_asset_cfg.random_choice = cfg.random_choice + + # call the original function + return spawn_multi_asset(prim_path, multi_asset_cfg, translation, orientation) diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/spawners/wrappers/wrappers_cfg.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/spawners/wrappers/wrappers_cfg.py new file mode 100644 index 0000000000..83d42cc4af --- /dev/null +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/spawners/wrappers/wrappers_cfg.py @@ -0,0 +1,67 @@ +# Copyright (c) 2022-2024, The Isaac Lab Project Developers. +# All rights reserved. +# +# SPDX-License-Identifier: BSD-3-Clause + +from dataclasses import MISSING + +from omni.isaac.lab.sim.spawners.from_files import UsdFileCfg +from omni.isaac.lab.sim.spawners.spawner_cfg import DeformableObjectSpawnerCfg, RigidObjectSpawnerCfg, SpawnerCfg +from omni.isaac.lab.utils import configclass + +from . import wrappers + + +@configclass +class MultiAssetSpawnerCfg(RigidObjectSpawnerCfg, DeformableObjectSpawnerCfg): + """Configuration parameters for loading multiple assets from their individual configurations. + + Specifying values for any properties at the configuration level will override the settings of + individual assets' configuration. For instance if the attribute + :attr:`MultiAssetSpawnerCfg.mass_props` is specified, its value will overwrite the values of the + mass properties in each configuration inside :attr:`assets_cfg` (wherever applicable). + This is done to simplify configuring similar properties globally. By default, all properties are set to None. + + The following is an exception to the above: + + * :attr:`visible`: This parameter is ignored. Its value for the individual assets is used. + * :attr:`semantic_tags`: If specified, it will be appended to each individual asset's semantic tags. + + """ + + func = wrappers.spawn_multi_asset + + assets_cfg: list[SpawnerCfg] = MISSING + """List of asset configurations to spawn.""" + + random_choice: bool = True + """Whether to randomly select an asset configuration. Default is True. + + If False, the asset configurations are spawned in the order they are provided in the list. + If True, a random asset configuration is selected for each spawn. + """ + + +@configclass +class MultiUsdFileCfg(UsdFileCfg): + """Configuration parameters for loading multiple USD files. + + Specifying values for any properties at the configuration level is applied to all the assets + imported from their USD files. + + .. tip:: + It is recommended that all the USD based assets follow a similar prim-hierarchy. + + """ + + func = wrappers.spawn_multi_usd_file + + usd_path: str | list[str] = MISSING + """Path or a list of paths to the USD files to spawn asset from.""" + + random_choice: bool = True + """Whether to randomly select an asset configuration. Default is True. + + If False, the asset configurations are spawned in the order they are provided in the list. + If True, a random asset configuration is selected for each spawn. + """ diff --git a/source/extensions/omni.isaac.lab/test/sim/test_spawn_wrappers.py b/source/extensions/omni.isaac.lab/test/sim/test_spawn_wrappers.py new file mode 100644 index 0000000000..1260facf58 --- /dev/null +++ b/source/extensions/omni.isaac.lab/test/sim/test_spawn_wrappers.py @@ -0,0 +1,191 @@ +# Copyright (c) 2022-2024, The Isaac Lab Project Developers. +# All rights reserved. +# +# SPDX-License-Identifier: BSD-3-Clause + +"""Launch Isaac Sim Simulator first.""" + +from omni.isaac.lab.app import AppLauncher, run_tests + +# launch omniverse app +simulation_app = AppLauncher(headless=True).app + +"""Rest everything follows.""" + +import unittest + +import omni.isaac.core.utils.prims as prim_utils +import omni.isaac.core.utils.stage as stage_utils +from omni.isaac.core.simulation_context import SimulationContext + +import omni.isaac.lab.sim as sim_utils +from omni.isaac.lab.utils.assets import ISAACLAB_NUCLEUS_DIR + + +class TestSpawningWrappers(unittest.TestCase): + """Test fixture for checking spawning of multiple assets wrappers.""" + + def setUp(self) -> None: + """Create a blank new stage for each test.""" + # Create a new stage + stage_utils.create_new_stage() + # Simulation time-step + self.dt = 0.1 + # Load kit helper + self.sim = SimulationContext(physics_dt=self.dt, rendering_dt=self.dt, backend="numpy") + # Wait for spawning + stage_utils.update_stage() + + def tearDown(self) -> None: + """Stops simulator after each test.""" + # stop simulation + self.sim.stop() + self.sim.clear() + self.sim.clear_all_callbacks() + self.sim.clear_instance() + + """ + Tests - Multiple assets. + """ + + def test_spawn_multiple_shapes_with_global_settings(self): + """Test spawning of shapes randomly with global rigid body settings.""" + # Define prim parents + num_clones = 10 + for i in range(num_clones): + prim_utils.create_prim(f"/World/env_{i}", "Xform", translation=(i, i, 0)) + + # Spawn shapes + cfg = sim_utils.MultiAssetSpawnerCfg( + assets_cfg=[ + sim_utils.ConeCfg( + radius=0.3, + height=0.6, + visual_material=sim_utils.PreviewSurfaceCfg(diffuse_color=(0.0, 1.0, 0.0), metallic=0.2), + mass_props=sim_utils.MassPropertiesCfg(mass=100.0), # this one should get overridden + ), + sim_utils.CuboidCfg( + size=(0.3, 0.3, 0.3), + visual_material=sim_utils.PreviewSurfaceCfg(diffuse_color=(1.0, 0.0, 0.0), metallic=0.2), + ), + sim_utils.SphereCfg( + radius=0.3, + visual_material=sim_utils.PreviewSurfaceCfg(diffuse_color=(0.0, 0.0, 1.0), metallic=0.2), + ), + ], + random_choice=True, + rigid_props=sim_utils.RigidBodyPropertiesCfg( + solver_position_iteration_count=4, solver_velocity_iteration_count=0 + ), + mass_props=sim_utils.MassPropertiesCfg(mass=1.0), + collision_props=sim_utils.CollisionPropertiesCfg(), + ) + prim = cfg.func("/World/env_.*/Cone", cfg) + + # Check validity + self.assertTrue(prim.IsValid()) + self.assertEqual(prim_utils.get_prim_path(prim), "/World/env_0/Cone") + # Find matching prims + prim_paths = prim_utils.find_matching_prim_paths("/World/env_*/Cone") + self.assertEqual(len(prim_paths), num_clones) + + # Check all prims have correct settings + for prim_path in prim_paths: + prim = prim_utils.get_prim_at_path(prim_path) + self.assertEqual(prim.GetAttribute("physics:mass").Get(), cfg.mass_props.mass) + + def test_spawn_multiple_shapes_with_individual_settings(self): + """Test spawning of shapes randomly with individual rigid object settings""" + # Define prim parents + num_clones = 10 + for i in range(num_clones): + prim_utils.create_prim(f"/World/env_{i}", "Xform", translation=(i, i, 0)) + + # Make a list of masses + mass_variations = [2.0, 3.0, 4.0] + # Spawn shapes + cfg = sim_utils.MultiAssetSpawnerCfg( + assets_cfg=[ + sim_utils.ConeCfg( + radius=0.3, + height=0.6, + visual_material=sim_utils.PreviewSurfaceCfg(diffuse_color=(0.0, 1.0, 0.0), metallic=0.2), + rigid_props=sim_utils.RigidBodyPropertiesCfg(), + mass_props=sim_utils.MassPropertiesCfg(mass=mass_variations[0]), + collision_props=sim_utils.CollisionPropertiesCfg(), + ), + sim_utils.CuboidCfg( + size=(0.3, 0.3, 0.3), + visual_material=sim_utils.PreviewSurfaceCfg(diffuse_color=(1.0, 0.0, 0.0), metallic=0.2), + rigid_props=sim_utils.RigidBodyPropertiesCfg(), + mass_props=sim_utils.MassPropertiesCfg(mass=mass_variations[1]), + collision_props=sim_utils.CollisionPropertiesCfg(), + ), + sim_utils.SphereCfg( + radius=0.3, + visual_material=sim_utils.PreviewSurfaceCfg(diffuse_color=(0.0, 0.0, 1.0), metallic=0.2), + rigid_props=sim_utils.RigidBodyPropertiesCfg(), + mass_props=sim_utils.MassPropertiesCfg(mass=mass_variations[2]), + collision_props=sim_utils.CollisionPropertiesCfg(), + ), + ], + random_choice=True, + ) + prim = cfg.func("/World/env_.*/Cone", cfg) + + # Check validity + self.assertTrue(prim.IsValid()) + self.assertEqual(prim_utils.get_prim_path(prim), "/World/env_0/Cone") + # Find matching prims + prim_paths = prim_utils.find_matching_prim_paths("/World/env_*/Cone") + self.assertEqual(len(prim_paths), num_clones) + + # Check all prims have correct settings + for prim_path in prim_paths: + prim = prim_utils.get_prim_at_path(prim_path) + self.assertTrue(prim.GetAttribute("physics:mass").Get() in mass_variations) + + """ + Tests - Multiple USDs. + """ + + def test_spawn_multiple_files_with_global_settings(self): + """Test spawning of files randomly with global articulation settings.""" + # Define prim parents + num_clones = 10 + for i in range(num_clones): + prim_utils.create_prim(f"/World/env_{i}", "Xform", translation=(i, i, 0)) + + # Spawn shapes + cfg = sim_utils.MultiUsdFileCfg( + usd_path=[ + f"{ISAACLAB_NUCLEUS_DIR}/Robots/ANYbotics/ANYmal-C/anymal_c.usd", + f"{ISAACLAB_NUCLEUS_DIR}/Robots/ANYbotics/ANYmal-D/anymal_d.usd", + ], + random_choice=True, + rigid_props=sim_utils.RigidBodyPropertiesCfg( + disable_gravity=False, + retain_accelerations=False, + linear_damping=0.0, + angular_damping=0.0, + max_linear_velocity=1000.0, + max_angular_velocity=1000.0, + max_depenetration_velocity=1.0, + ), + articulation_props=sim_utils.ArticulationRootPropertiesCfg( + enabled_self_collisions=True, solver_position_iteration_count=4, solver_velocity_iteration_count=0 + ), + activate_contact_sensors=True, + ) + prim = cfg.func("/World/env_.*/Robot", cfg) + + # Check validity + self.assertTrue(prim.IsValid()) + self.assertEqual(prim_utils.get_prim_path(prim), "/World/env_0/Robot") + # Find matching prims + prim_paths = prim_utils.find_matching_prim_paths("/World/env_*/Robot") + self.assertEqual(len(prim_paths), num_clones) + + +if __name__ == "__main__": + run_tests() diff --git a/source/standalone/demos/multi_asset.py b/source/standalone/demos/multi_asset.py new file mode 100644 index 0000000000..6363999949 --- /dev/null +++ b/source/standalone/demos/multi_asset.py @@ -0,0 +1,244 @@ +# Copyright (c) 2022-2024, The Isaac Lab Project Developers. +# All rights reserved. +# +# SPDX-License-Identifier: BSD-3-Clause + +"""This script demonstrates how to spawn multiple objects in multiple environments. + +.. code-block:: bash + + # Usage + ./isaaclab.sh -p source/standalone/demos/multi_asset.py --num_envs 2048 + +""" + +from __future__ import annotations + +"""Launch Isaac Sim Simulator first.""" + + +import argparse + +from omni.isaac.lab.app import AppLauncher + +# add argparse arguments +parser = argparse.ArgumentParser(description="Demo on spawning different objects in multiple environments.") +parser.add_argument("--num_envs", type=int, default=1024, help="Number of environments to spawn.") +# append AppLauncher cli args +AppLauncher.add_app_launcher_args(parser) +# parse the arguments +args_cli = parser.parse_args() + +# launch omniverse app +app_launcher = AppLauncher(args_cli) +simulation_app = app_launcher.app + +"""Rest everything follows.""" + +import random + +import omni.usd +from pxr import Gf, Sdf + +import omni.isaac.lab.sim as sim_utils +from omni.isaac.lab.assets import ArticulationCfg, AssetBaseCfg, RigidObjectCfg +from omni.isaac.lab.scene import InteractiveScene, InteractiveSceneCfg +from omni.isaac.lab.sim import SimulationContext +from omni.isaac.lab.utils import Timer, configclass +from omni.isaac.lab.utils.assets import ISAACLAB_NUCLEUS_DIR + +## +# Pre-defined Configuration +## + +from omni.isaac.lab_assets.anymal import ANYDRIVE_3_LSTM_ACTUATOR_CFG # isort: skip + + +## +# Randomization events. +## + + +def randomize_shape_color(prim_path_expr: str): + """Randomize the color of the geometry.""" + # acquire stage + stage = omni.usd.get_context().get_stage() + # resolve prim paths for spawning and cloning + prim_paths = sim_utils.find_matching_prim_paths(prim_path_expr) + # manually clone prims if the source prim path is a regex expression + with Sdf.ChangeBlock(): + for prim_path in prim_paths: + # spawn single instance + prim_spec = Sdf.CreatePrimInLayer(stage.GetRootLayer(), prim_path) + + # DO YOUR OWN OTHER KIND OF RANDOMIZATION HERE! + # Note: Just need to acquire the right attribute about the property you want to set + # Here is an example on setting color randomly + color_spec = prim_spec.GetAttributeAtPath(prim_path + "/geometry/material/Shader.inputs:diffuseColor") + color_spec.default = Gf.Vec3f(random.random(), random.random(), random.random()) + + +## +# Scene Configuration +## + + +@configclass +class MultiObjectSceneCfg(InteractiveSceneCfg): + """Configuration for a multi-object scene.""" + + # ground plane + ground = AssetBaseCfg(prim_path="/World/defaultGroundPlane", spawn=sim_utils.GroundPlaneCfg()) + + # lights + dome_light = AssetBaseCfg( + prim_path="/World/Light", spawn=sim_utils.DomeLightCfg(intensity=3000.0, color=(0.75, 0.75, 0.75)) + ) + + # rigid object + object: RigidObjectCfg = RigidObjectCfg( + prim_path="/World/envs/env_.*/Object", + spawn=sim_utils.MultiAssetSpawnerCfg( + assets_cfg=[ + sim_utils.ConeCfg( + radius=0.3, + height=0.6, + visual_material=sim_utils.PreviewSurfaceCfg(diffuse_color=(0.0, 1.0, 0.0), metallic=0.2), + ), + sim_utils.CuboidCfg( + size=(0.3, 0.3, 0.3), + visual_material=sim_utils.PreviewSurfaceCfg(diffuse_color=(1.0, 0.0, 0.0), metallic=0.2), + ), + sim_utils.SphereCfg( + radius=0.3, + visual_material=sim_utils.PreviewSurfaceCfg(diffuse_color=(0.0, 0.0, 1.0), metallic=0.2), + ), + ], + random_choice=True, + rigid_props=sim_utils.RigidBodyPropertiesCfg( + solver_position_iteration_count=4, solver_velocity_iteration_count=0 + ), + mass_props=sim_utils.MassPropertiesCfg(mass=1.0), + collision_props=sim_utils.CollisionPropertiesCfg(), + ), + init_state=RigidObjectCfg.InitialStateCfg(pos=(0.0, 0.0, 2.0)), + ) + + # articulation + robot: ArticulationCfg = ArticulationCfg( + prim_path="/World/envs/env_.*/Robot", + spawn=sim_utils.MultiUsdFileCfg( + usd_path=[ + f"{ISAACLAB_NUCLEUS_DIR}/Robots/ANYbotics/ANYmal-C/anymal_c.usd", + f"{ISAACLAB_NUCLEUS_DIR}/Robots/ANYbotics/ANYmal-D/anymal_d.usd", + ], + random_choice=True, + rigid_props=sim_utils.RigidBodyPropertiesCfg( + disable_gravity=False, + retain_accelerations=False, + linear_damping=0.0, + angular_damping=0.0, + max_linear_velocity=1000.0, + max_angular_velocity=1000.0, + max_depenetration_velocity=1.0, + ), + articulation_props=sim_utils.ArticulationRootPropertiesCfg( + enabled_self_collisions=True, solver_position_iteration_count=4, solver_velocity_iteration_count=0 + ), + activate_contact_sensors=True, + ), + init_state=ArticulationCfg.InitialStateCfg( + pos=(0.0, 0.0, 0.6), + joint_pos={ + ".*HAA": 0.0, # all HAA + ".*F_HFE": 0.4, # both front HFE + ".*H_HFE": -0.4, # both hind HFE + ".*F_KFE": -0.8, # both front KFE + ".*H_KFE": 0.8, # both hind KFE + }, + ), + actuators={"legs": ANYDRIVE_3_LSTM_ACTUATOR_CFG}, + ) + + +## +# Simulation Loop +## + + +def run_simulator(sim: SimulationContext, scene: InteractiveScene): + """Runs the simulation loop.""" + # Extract scene entities + # note: we only do this here for readability. + rigid_object = scene["object"] + robot = scene["robot"] + # Define simulation stepping + sim_dt = sim.get_physics_dt() + count = 0 + # Simulation loop + while simulation_app.is_running(): + # Reset + if count % 500 == 0: + # reset counter + count = 0 + # reset the scene entities + # object + root_state = rigid_object.data.default_root_state.clone() + root_state[:, :3] += scene.env_origins + rigid_object.write_root_state_to_sim(root_state) + # robot + # -- root state + root_state = robot.data.default_root_state.clone() + root_state[:, :3] += scene.env_origins + robot.write_root_state_to_sim(root_state) + # -- joint state + joint_pos, joint_vel = robot.data.default_joint_pos.clone(), robot.data.default_joint_vel.clone() + robot.write_joint_state_to_sim(joint_pos, joint_vel) + # clear internal buffers + scene.reset() + print("[INFO]: Resetting scene state...") + + # Apply action to robot + robot.set_joint_position_target(robot.data.default_joint_pos) + # Write data to sim + scene.write_data_to_sim() + # Perform step + sim.step() + # Increment counter + count += 1 + # Update buffers + scene.update(sim_dt) + + +def main(): + """Main function.""" + # Load kit helper + sim_cfg = sim_utils.SimulationCfg(dt=0.005, device=args_cli.device) + sim = SimulationContext(sim_cfg) + # Set main camera + sim.set_camera_view([2.5, 0.0, 4.0], [0.0, 0.0, 2.0]) + + # Design scene + scene_cfg = MultiObjectSceneCfg(num_envs=args_cli.num_envs, env_spacing=2.0, replicate_physics=False) + with Timer("[INFO] Time to create scene: "): + scene = InteractiveScene(scene_cfg) + + with Timer("[INFO] Time to randomize scene: "): + # DO YOUR OWN OTHER KIND OF RANDOMIZATION HERE! + # Note: Just need to acquire the right attribute about the property you want to set + # Here is an example on setting color randomly + randomize_shape_color(scene_cfg.object.prim_path) + + # Play the simulator + sim.reset() + # Now we are ready! + print("[INFO]: Setup complete...") + # Run the simulator + run_simulator(sim, scene) + + +if __name__ == "__main__": + # run the main execution + main() + # close sim app + simulation_app.close() From c8e6a32afd4217d49c8da0c0f0677fddedce2f8a Mon Sep 17 00:00:00 2001 From: Alexander Poddubny <143108850+nv-apoddubny@users.noreply.github.com> Date: Thu, 10 Oct 2024 08:14:20 -0700 Subject: [PATCH 006/111] Moves codebuild pipeline files to `.aws` directory (#1196) # Description Moving codebuild pipelines out of github folder to avoid github actions being triggered on them. --- {.github/workflows => .aws}/mirror-buildspec.yml | 0 {.github/workflows => .aws}/postmerge-ci-buildspec.yml | 0 {.github/workflows => .aws}/premerge-ci-buildspec.yml | 0 3 files changed, 0 insertions(+), 0 deletions(-) rename {.github/workflows => .aws}/mirror-buildspec.yml (100%) rename {.github/workflows => .aws}/postmerge-ci-buildspec.yml (100%) rename {.github/workflows => .aws}/premerge-ci-buildspec.yml (100%) diff --git a/.github/workflows/mirror-buildspec.yml b/.aws/mirror-buildspec.yml similarity index 100% rename from .github/workflows/mirror-buildspec.yml rename to .aws/mirror-buildspec.yml diff --git a/.github/workflows/postmerge-ci-buildspec.yml b/.aws/postmerge-ci-buildspec.yml similarity index 100% rename from .github/workflows/postmerge-ci-buildspec.yml rename to .aws/postmerge-ci-buildspec.yml diff --git a/.github/workflows/premerge-ci-buildspec.yml b/.aws/premerge-ci-buildspec.yml similarity index 100% rename from .github/workflows/premerge-ci-buildspec.yml rename to .aws/premerge-ci-buildspec.yml From 5f813011e710fcf8a171c576823912ee078739bb Mon Sep 17 00:00:00 2001 From: Michael Gussert Date: Thu, 10 Oct 2024 08:18:30 -0700 Subject: [PATCH 007/111] Fixes the ray_caster_camera tutorial script when saving the data (#1198) There was a minor error in the `run_ray_caster_camera.py` tutorial script that prevented it from saving images. - [X] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [X] I have made corresponding changes to the documentation - [X] My changes generate no new warnings - [X] I have added tests that prove my fix is effective or that my feature works - [X] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [X] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --- .../tutorials/04_sensors/run_ray_caster_camera.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/source/standalone/tutorials/04_sensors/run_ray_caster_camera.py b/source/standalone/tutorials/04_sensors/run_ray_caster_camera.py index a54d9dc6f6..a813bd74ea 100644 --- a/source/standalone/tutorials/04_sensors/run_ray_caster_camera.py +++ b/source/standalone/tutorials/04_sensors/run_ray_caster_camera.py @@ -141,12 +141,12 @@ def run_simulator(sim: sim_utils.SimulationContext, scene_entities: dict): single_cam_info = camera.data.info[camera_index] # Pack data back into replicator format to save them using its writer - rep_output = dict() + rep_output = {"annotators": {}} for key, data, info in zip(single_cam_data.keys(), single_cam_data.values(), single_cam_info.values()): if info is not None: - rep_output[key] = {"data": data, "info": info} + rep_output["annotators"][key] = {"render_product": {"data": data, **info}} else: - rep_output[key] = data + rep_output["annotators"][key] = {"render_product": {"data": data}} # Save images rep_output["trigger_outputs"] = {"on_time": camera.frame[camera_index]} rep_writer.write(rep_output) From 73c47e4f0599544c7feffe01fa47c59f518773de Mon Sep 17 00:00:00 2001 From: Giulio Romualdi Date: Thu, 10 Oct 2024 17:31:50 +0200 Subject: [PATCH 008/111] Fixes running the docker container when the DISPLAY env variable is not defined (#1163) # Description This PR attempts to fix #1162 by adding the possibility to do not pass the `DISPLAY` env to the docker exec command if the variable is not defined Fixes #1162 ## Type of change - Bug fix (non-breaking change which fixes an issue) ## Checklist - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [ ] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [ ] I have added tests that prove my fix is effective or that my feature works - [ ] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [x] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --- CONTRIBUTORS.md | 1 + docker/utils/container_interface.py | 3 +-- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/CONTRIBUTORS.md b/CONTRIBUTORS.md index 26503d4e06..b84c3a0aa8 100644 --- a/CONTRIBUTORS.md +++ b/CONTRIBUTORS.md @@ -42,6 +42,7 @@ Guidelines for modifications: * Chenyu Yang * David Yang * Gary Lvov +* Giulio Romualdi * HoJin Jeon * Jean Tampon * Jia Lin Yuan diff --git a/docker/utils/container_interface.py b/docker/utils/container_interface.py index c717457029..aacbc79ccd 100644 --- a/docker/utils/container_interface.py +++ b/docker/utils/container_interface.py @@ -142,8 +142,7 @@ def enter(self): "exec", "--interactive", "--tty", - "-e", - f"DISPLAY={os.environ['DISPLAY']}", + *(["-e", f"DISPLAY={os.environ['DISPLAY']}"] if "DISPLAY" in os.environ else []), f"{self.container_name}", "bash", ]) From cb9fee62f14d03f07837cca29977088b6cb43a94 Mon Sep 17 00:00:00 2001 From: Kelly Guo Date: Thu, 10 Oct 2024 11:42:41 -0400 Subject: [PATCH 009/111] Fixes default joint pos when setting joint limits (#1040) # Description When setting joint limits, the existing default joint positions can fall outside of the bounds of the new joint limits. This change clips the default joint positions to ensure they are within the bounds of the new limits. ## Type of change - Bug fix (non-breaking change which fixes an issue) ## Checklist - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [ ] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [x] I have added tests that prove my fix is effective or that my feature works - [x] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [ ] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --- .../omni.isaac.lab/config/extension.toml | 2 +- .../omni.isaac.lab/docs/CHANGELOG.rst | 12 +++++- .../lab/assets/articulation/articulation.py | 7 ++++ .../test/assets/test_articulation.py | 42 +++++++++++++++++++ tools/per_test_timeouts.py | 1 + 5 files changed, 62 insertions(+), 2 deletions(-) diff --git a/source/extensions/omni.isaac.lab/config/extension.toml b/source/extensions/omni.isaac.lab/config/extension.toml index 7e9225c2b3..517ac00610 100644 --- a/source/extensions/omni.isaac.lab/config/extension.toml +++ b/source/extensions/omni.isaac.lab/config/extension.toml @@ -1,7 +1,7 @@ [package] # Note: Semantic Versioning is used: https://semver.org/ -version = "0.25.0" +version = "0.25.1" # Description title = "Isaac Lab framework for Robot Learning" diff --git a/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst b/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst index b0fa66f629..e78abdb068 100644 --- a/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst +++ b/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst @@ -1,6 +1,16 @@ Changelog --------- +0.25.1 (2024-10-10) +~~~~~~~~~~~~~~~~~~~ + +Fixed +^^^^^ + +* Fixed potential issue where default joint positions can fall outside of the limits being set with Articulation's + ``write_joint_limits_to_sim`` API. + + 0.25.0 (2024-10-06) ~~~~~~~~~~~~~~~~~~~ @@ -14,7 +24,7 @@ Added 0.24.20 (2024-10-07) ~~~~~~~~~~~~~~~~~~~~ -Fixes +Fixed ^^^^^ * Fixed the :meth:`omni.isaac.lab.envs.mdp.events.randomize_rigid_body_material` function to diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/articulation/articulation.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/articulation/articulation.py index c1765df56c..9357d90ca5 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/articulation/articulation.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/articulation/articulation.py @@ -539,6 +539,13 @@ def write_joint_limits_to_sim( env_ids = env_ids[:, None] # set into internal buffers self._data.joint_limits[env_ids, joint_ids] = limits + # update default joint pos to stay within the new limits + if torch.any((self._data.default_joint_pos < limits[..., 0]) | (self._data.default_joint_pos > limits[..., 1])): + self._data.default_joint_pos = torch.clamp(self._data.default_joint_pos, limits[..., 0], limits[..., 1]) + carb.log_warn( + "Some default joint positions are outside of the range of the new joint limits. Default joint positions" + " will be clamped to be within the new joint limits." + ) # set into simulation self.root_physx_view.set_dof_limits(self._data.joint_limits.cpu(), indices=physx_env_ids.cpu()) diff --git a/source/extensions/omni.isaac.lab/test/assets/test_articulation.py b/source/extensions/omni.isaac.lab/test/assets/test_articulation.py index 2fc0910ee9..da0b9accf6 100644 --- a/source/extensions/omni.isaac.lab/test/assets/test_articulation.py +++ b/source/extensions/omni.isaac.lab/test/assets/test_articulation.py @@ -542,6 +542,48 @@ def test_out_of_range_default_joint_vel(self): # Check if articulation is initialized self.assertFalse(articulation._is_initialized) + def test_joint_limits(self): + """Test write_joint_limits_to_sim API and when default pos falls outside of the new limits.""" + for num_articulations in (1, 2): + for device in ("cuda:0", "cpu"): + with self.subTest(num_articulations=num_articulations, device=device): + with build_simulation_context(device=device, add_ground_plane=True, auto_add_lighting=True) as sim: + # Create articulation + articulation_cfg = generate_articulation_cfg(articulation_type="panda") + articulation, _ = generate_articulation(articulation_cfg, num_articulations, device) + + # Play sim + sim.reset() + # Check if articulation is initialized + self.assertTrue(articulation._is_initialized) + + # Get current default joint pos + default_joint_pos = articulation._data.default_joint_pos.clone() + + # Set new joint limits + limits = torch.zeros(num_articulations, articulation.num_joints, 2, device=device) + limits[..., 0] = ( + torch.rand(num_articulations, articulation.num_joints, device=device) + 5.0 + ) * -1.0 + limits[..., 1] = torch.rand(num_articulations, articulation.num_joints, device=device) + 5.0 + articulation.write_joint_limits_to_sim(limits) + + # Check new limits are in place + torch.testing.assert_close(articulation._data.joint_limits, limits) + torch.testing.assert_close(articulation._data.default_joint_pos, default_joint_pos) + + # Set new joint limits that invalidate default joint pos + limits = torch.zeros(num_articulations, articulation.num_joints, 2, device=device) + limits[..., 0] = torch.rand(num_articulations, articulation.num_joints, device=device) * -0.1 + limits[..., 1] = torch.rand(num_articulations, articulation.num_joints, device=device) * 0.1 + articulation.write_joint_limits_to_sim(limits) + + # Check if all values are within the bounds + within_bounds = (articulation._data.default_joint_pos >= limits[..., 0]) & ( + articulation._data.default_joint_pos <= limits[..., 1] + ) + self.assertTrue(torch.all(within_bounds)) + def test_external_force_on_single_body(self): """Test application of external force on the base of the articulation.""" for num_articulations in (1, 2): diff --git a/tools/per_test_timeouts.py b/tools/per_test_timeouts.py index e9fad0a293..e98595372f 100644 --- a/tools/per_test_timeouts.py +++ b/tools/per_test_timeouts.py @@ -8,6 +8,7 @@ Any tests not listed here will use the default timeout. """ PER_TEST_TIMEOUTS = { + "test_articulation.py": 200, "test_environments.py": 1200, # This test runs through all the environments for 100 steps each "test_environment_determinism.py": 200, # This test runs through many the environments for 100 steps each "test_env_rendering_logic.py": 300, From 92dcb8c05642aa890979a5e40a7b5cc9255799d2 Mon Sep 17 00:00:00 2001 From: Mayank Mittal <12863862+Mayankm96@users.noreply.github.com> Date: Fri, 11 Oct 2024 19:01:15 +0200 Subject: [PATCH 010/111] Adds benchmark script to measure robot loading (#1195) # Description This MR makes a minimal script to measure how long it takes to load different robots. ## Type of change - New feature (non-breaking change which adds functionality) ## Screenshots For loading 2048 robots headless: | **Metric** | **H1** | **G1** | **Anymal_D** | |-------------------|-------------------|-------------------|-------------------| | App start time | 3791.73 ms | 3660.98 ms | 3597.30 ms | | Imports time | 1116.61 ms | 1132.87 ms | 1142.27 ms | | Scene creation time | 1584.14 ms | 1674.18 ms | 2000.40 ms | | Sim start time | 1451.94 ms | 2647.43 ms | 1778.49 ms | | Per step time | 2.31 ms | 4.71 ms | 3.67 ms | Computer specs: * OS: Ubuntu 20.04.6 LTS x86_64 * CPU: 12th Gen Intel i9-12900K (24) @ 5.100GHz * GPU: NVIDIA 4090 RTX ## Checklist - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [x] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [ ] I have added tests that prove my fix is effective or that my feature works - [ ] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [x] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --- .../omni/isaac/lab_assets/unitree.py | 2 + .../benchmarks/benchmark_load_robot.py | 178 ++++++++++++++++++ 2 files changed, 180 insertions(+) create mode 100644 source/standalone/benchmarks/benchmark_load_robot.py diff --git a/source/extensions/omni.isaac.lab_assets/omni/isaac/lab_assets/unitree.py b/source/extensions/omni.isaac.lab_assets/omni/isaac/lab_assets/unitree.py index e13722ae59..d0eb236dae 100644 --- a/source/extensions/omni.isaac.lab_assets/omni/isaac/lab_assets/unitree.py +++ b/source/extensions/omni.isaac.lab_assets/omni/isaac/lab_assets/unitree.py @@ -11,7 +11,9 @@ * :obj:`UNITREE_GO1_CFG`: Unitree Go1 robot with actuator net model for the legs * :obj:`UNITREE_GO2_CFG`: Unitree Go2 robot with DC motor model for the legs * :obj:`H1_CFG`: H1 humanoid robot +* :obj:`H1_MINIMAL_CFG`: H1 humanoid robot with minimal collision bodies * :obj:`G1_CFG`: G1 humanoid robot +* :obj:`G1_MINIMAL_CFG`: G1 humanoid robot with minimal collision bodies Reference: https://github.com/unitreerobotics/unitree_ros """ diff --git a/source/standalone/benchmarks/benchmark_load_robot.py b/source/standalone/benchmarks/benchmark_load_robot.py new file mode 100644 index 0000000000..65715c4648 --- /dev/null +++ b/source/standalone/benchmarks/benchmark_load_robot.py @@ -0,0 +1,178 @@ +# Copyright (c) 2022-2024, The Isaac Lab Project Developers. +# All rights reserved. +# +# SPDX-License-Identifier: BSD-3-Clause + +"""Script to benchmark loading multiple copies of a robot. + +.. code-block python + + ./isaaclab.sh -p source/standalone/benchmarks/benchmark_load_robot.py --num_envs 2048 --robot g1 --headless + +""" + +"""Launch Isaac Sim Simulator first.""" + +import argparse +import time + +from omni.isaac.lab.app import AppLauncher + +# add argparse arguments +parser = argparse.ArgumentParser(description="Benchmark loading different robots.") +parser.add_argument("--num_envs", type=int, default=32, help="Number of robots to simulate.") +parser.add_argument( + "--robot", + type=str, + choices=['anymal_d', 'h1', 'g1'], + default="h1", + help="Choose which robot to load: anymal_d, h1, or g1.", +) +# append AppLauncher cli args +AppLauncher.add_app_launcher_args(parser) +# parse the arguments +args_cli, _ = parser.parse_known_args() + +# Start the timer for app start +app_start_time_begin = time.perf_counter_ns() + +# launch omniverse app +app_launcher = AppLauncher(args_cli) +simulation_app = app_launcher.app + +# End the timer for app start +app_start_time_end = time.perf_counter_ns() + +print(f"[INFO]: App start time: {(app_start_time_end - app_start_time_begin) / 1e6:.2f} ms") + +"""Rest everything follows.""" + +# Start the timer for imports +imports_time_begin = time.perf_counter_ns() + +import torch + +import omni.isaac.lab.sim as sim_utils +from omni.isaac.lab.assets import ArticulationCfg, AssetBaseCfg +from omni.isaac.lab.scene import InteractiveScene, InteractiveSceneCfg +from omni.isaac.lab.sim import SimulationContext +from omni.isaac.lab.utils import configclass + +## +# Pre-defined configs +## +from omni.isaac.lab_assets import ANYMAL_D_CFG, G1_MINIMAL_CFG, H1_MINIMAL_CFG # isort:skip + + +# Stop the timer for imports +imports_time_end = time.perf_counter_ns() + +print(f"[INFO]: Imports time: {(imports_time_end - imports_time_begin) / 1e6:.2f} ms") + +@configclass +class RobotSceneCfg(InteractiveSceneCfg): + """Configuration for a simple scene with a robot.""" + + # ground plane + ground = AssetBaseCfg(prim_path="/World/defaultGroundPlane", spawn=sim_utils.GroundPlaneCfg()) + + # lights + dome_light = AssetBaseCfg( + prim_path="/World/Light", spawn=sim_utils.DomeLightCfg(intensity=3000.0, color=(0.75, 0.75, 0.75)) + ) + + # articulation + if args_cli.robot == "h1": + robot: ArticulationCfg = H1_MINIMAL_CFG.replace(prim_path="{ENV_REGEX_NS}/Robot") + elif args_cli.robot == "g1": + robot: ArticulationCfg = G1_MINIMAL_CFG.replace(prim_path="{ENV_REGEX_NS}/Robot") + elif args_cli.robot == "anymal_d": + robot: ArticulationCfg = ANYMAL_D_CFG.replace(prim_path="{ENV_REGEX_NS}/Robot") + else: + raise ValueError(f"Unsupported robot type: {args_cli.robot}.") + +def run_simulator(sim: sim_utils.SimulationContext, scene: InteractiveScene): + """Runs the simulation loop.""" + # Extract scene entities + # note: we only do this here for readability. + robot = scene["robot"] + # Define simulation stepping + sim_dt = sim.get_physics_dt() + count = 0 + + # Start the timer for creating the scene + step_time_begin = time.perf_counter_ns() + num_steps = 2000 + + # Simulation loop + for _ in range(num_steps): + # Reset + if count % 500 == 0: + # reset counter + count = 0 + # reset the scene entities + # root state + # we offset the root state by the origin since the states are written in simulation world frame + # if this is not done, then the robots will be spawned at the (0, 0, 0) of the simulation world + root_state = robot.data.default_root_state.clone() + root_state[:, :3] += scene.env_origins + robot.write_root_state_to_sim(root_state) + # set joint positions with some noise + joint_pos, joint_vel = robot.data.default_joint_pos.clone(), robot.data.default_joint_vel.clone() + joint_pos += torch.rand_like(joint_pos) * 0.1 + robot.write_joint_state_to_sim(joint_pos, joint_vel) + # clear internal buffers + scene.reset() + # Apply random action + # -- generate random joint efforts + efforts = torch.randn_like(robot.data.joint_pos) * 5.0 + # -- apply action to the robot + robot.set_joint_effort_target(efforts) + # -- write data to sim + scene.write_data_to_sim() + # Perform step + sim.step() + # Increment counter + count += 1 + # Update buffers + scene.update(sim_dt) + + # Stop the timer for reset + step_time_end = time.perf_counter_ns() + print(f"[INFO]: Per step time: {(step_time_end - step_time_begin) / num_steps / 1e6:.2f} ms") + + +def main(): + """Main function.""" + # Load kit helper + sim_cfg = sim_utils.SimulationCfg(device="cuda:0") + sim = SimulationContext(sim_cfg) + # Set main camera + sim.set_camera_view([2.5, 0.0, 4.0], [0.0, 0.0, 2.0]) + + # Start the timer for creating the scene + setup_time_begin = time.perf_counter_ns() + # Design scene + scene_cfg = RobotSceneCfg(num_envs=args_cli.num_envs, env_spacing=2.0) + scene = InteractiveScene(scene_cfg) + # Stop the timer for creating the scene + setup_time_end = time.perf_counter_ns() + print(f"[INFO]: Scene creation time: {(setup_time_end - setup_time_begin) / 1e6:.2f} ms") + + # Start the timer for reset + reset_time_begin = time.perf_counter_ns() + # Play the simulator + sim.reset() + # Stop the timer for reset + reset_time_end = time.perf_counter_ns() + print(f"[INFO]: Sim start time: {(reset_time_end - reset_time_begin) / 1e6:.2f} ms") + + # Run the simulator + run_simulator(sim, scene) + + +if __name__ == "__main__": + # run the main function + main() + # close sim app + simulation_app.close() From a972182b9b704caacb2acadb89ae001e2ee8af6c Mon Sep 17 00:00:00 2001 From: Mayank Mittal Date: Sat, 12 Oct 2024 01:13:57 +0200 Subject: [PATCH 011/111] Fixes formatting issues in the robot loading benchmark script --- .../benchmarks/benchmark_load_robot.py | 19 ++++++++----------- 1 file changed, 8 insertions(+), 11 deletions(-) diff --git a/source/standalone/benchmarks/benchmark_load_robot.py b/source/standalone/benchmarks/benchmark_load_robot.py index 65715c4648..3ac0345e37 100644 --- a/source/standalone/benchmarks/benchmark_load_robot.py +++ b/source/standalone/benchmarks/benchmark_load_robot.py @@ -22,9 +22,9 @@ parser = argparse.ArgumentParser(description="Benchmark loading different robots.") parser.add_argument("--num_envs", type=int, default=32, help="Number of robots to simulate.") parser.add_argument( - "--robot", - type=str, - choices=['anymal_d', 'h1', 'g1'], + "--robot", + type=str, + choices=["anymal_d", "h1", "g1"], default="h1", help="Choose which robot to load: anymal_d, h1, or g1.", ) @@ -69,6 +69,7 @@ print(f"[INFO]: Imports time: {(imports_time_end - imports_time_begin) / 1e6:.2f} ms") + @configclass class RobotSceneCfg(InteractiveSceneCfg): """Configuration for a simple scene with a robot.""" @@ -91,6 +92,7 @@ class RobotSceneCfg(InteractiveSceneCfg): else: raise ValueError(f"Unsupported robot type: {args_cli.robot}.") + def run_simulator(sim: sim_utils.SimulationContext, scene: InteractiveScene): """Runs the simulation loop.""" # Extract scene entities @@ -98,18 +100,15 @@ def run_simulator(sim: sim_utils.SimulationContext, scene: InteractiveScene): robot = scene["robot"] # Define simulation stepping sim_dt = sim.get_physics_dt() - count = 0 # Start the timer for creating the scene step_time_begin = time.perf_counter_ns() num_steps = 2000 # Simulation loop - for _ in range(num_steps): + for count in range(num_steps): # Reset if count % 500 == 0: - # reset counter - count = 0 # reset the scene entities # root state # we offset the root state by the origin since the states are written in simulation world frame @@ -132,11 +131,9 @@ def run_simulator(sim: sim_utils.SimulationContext, scene: InteractiveScene): scene.write_data_to_sim() # Perform step sim.step() - # Increment counter - count += 1 # Update buffers scene.update(sim_dt) - + # Stop the timer for reset step_time_end = time.perf_counter_ns() print(f"[INFO]: Per step time: {(step_time_end - step_time_begin) / num_steps / 1e6:.2f} ms") @@ -149,7 +146,7 @@ def main(): sim = SimulationContext(sim_cfg) # Set main camera sim.set_camera_view([2.5, 0.0, 4.0], [0.0, 0.0, 2.0]) - + # Start the timer for creating the scene setup_time_begin = time.perf_counter_ns() # Design scene From fb72d92a82331c45c14db7bc2771eb4e36c3e597 Mon Sep 17 00:00:00 2001 From: jtigue-bdai <166445701+jtigue-bdai@users.noreply.github.com> Date: Sat, 12 Oct 2024 03:30:25 -0400 Subject: [PATCH 012/111] Fixes device propogation for noise and adds noise tests (#1175) # Description This PR adds in logic to fix errors when noise config parameters are tensor based and do not have the correct device setting. This adds a check at the beginning of each noise function to correct the config parameters device if they are torch.tensors. In addition this PR adds tests for noise models. ## Type of change - Bug fix (non-breaking change which fixes an issue) ## Checklist - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [x] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [x] I have added tests that prove my fix is effective or that my feature works - [ ] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [x] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --- .../omni/isaac/lab/utils/noise/noise_model.py | 51 +++++++- .../omni.isaac.lab/test/utils/test_noise.py | 118 ++++++++++++++++++ 2 files changed, 166 insertions(+), 3 deletions(-) create mode 100644 source/extensions/omni.isaac.lab/test/utils/test_noise.py diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/utils/noise/noise_model.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/utils/noise/noise_model.py index 4bd2ff09f4..4f3e2e09c1 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/utils/noise/noise_model.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/utils/noise/noise_model.py @@ -18,7 +18,20 @@ def constant_noise(data: torch.Tensor, cfg: noise_cfg.ConstantNoiseCfg) -> torch.Tensor: - """Constant noise.""" + """Applies a constant noise bias to a given data set. + + Args: + data: The unmodified data set to apply noise to. + cfg: The configuration parameters for constant noise. + + Returns: + The data modified by the noise parameters provided. + """ + + # fix tensor device for bias on first call and update config parameters + if isinstance(cfg.bias, torch.Tensor): + cfg.bias = cfg.bias.to(device=data.device) + if cfg.operation == "add": return data + cfg.bias elif cfg.operation == "scale": @@ -30,7 +43,23 @@ def constant_noise(data: torch.Tensor, cfg: noise_cfg.ConstantNoiseCfg) -> torch def uniform_noise(data: torch.Tensor, cfg: noise_cfg.UniformNoiseCfg) -> torch.Tensor: - """Uniform noise.""" + """Applies a uniform noise to a given data set. + + Args: + data: The unmodified data set to apply noise to. + cfg: The configuration parameters for uniform noise. + + Returns: + The data modified by the noise parameters provided. + """ + + # fix tensor device for n_max on first call and update config parameters + if isinstance(cfg.n_max, torch.Tensor): + cfg.n_max = cfg.n_max.to(data.device) + # fix tensor device for n_min on first call and update config parameters + if isinstance(cfg.n_min, torch.Tensor): + cfg.n_min = cfg.n_min.to(data.device) + if cfg.operation == "add": return data + torch.rand_like(data) * (cfg.n_max - cfg.n_min) + cfg.n_min elif cfg.operation == "scale": @@ -42,7 +71,23 @@ def uniform_noise(data: torch.Tensor, cfg: noise_cfg.UniformNoiseCfg) -> torch.T def gaussian_noise(data: torch.Tensor, cfg: noise_cfg.GaussianNoiseCfg) -> torch.Tensor: - """Gaussian noise.""" + """Applies a gaussian noise to a given data set. + + Args: + data: The unmodified data set to apply noise to. + cfg: The configuration parameters for gaussian noise. + + Returns: + The data modified by the noise parameters provided. + """ + + # fix tensor device for mean on first call and update config parameters + if isinstance(cfg.mean, torch.Tensor): + cfg.mean = cfg.mean.to(data.device) + # fix tensor device for std on first call and update config parameters + if isinstance(cfg.std, torch.Tensor): + cfg.std = cfg.std.to(data.device) + if cfg.operation == "add": return data + cfg.mean + cfg.std * torch.randn_like(data) elif cfg.operation == "scale": diff --git a/source/extensions/omni.isaac.lab/test/utils/test_noise.py b/source/extensions/omni.isaac.lab/test/utils/test_noise.py new file mode 100644 index 0000000000..f5355d0856 --- /dev/null +++ b/source/extensions/omni.isaac.lab/test/utils/test_noise.py @@ -0,0 +1,118 @@ +# Copyright (c) 2022-2024, The Isaac Lab Project Developers. +# All rights reserved. +# +# SPDX-License-Identifier: BSD-3-Clause + +"""Launch Isaac Sim Simulator first.""" + +from omni.isaac.lab.app import AppLauncher, run_tests + +# launch omniverse app +app_launcher = AppLauncher(headless=True) +simulation_app = app_launcher.app + +"""Rest everything follows.""" + +import torch +import unittest + +import omni.isaac.lab.utils.noise as noise + + +class TestNoise(unittest.TestCase): + """Test different noise implementations.""" + + def test_gaussian_noise(self): + """Test guassian_noise function.""" + + for device in ["cpu", "cuda"]: + for noise_device in ["cpu", "cuda"]: + for op in ["add", "scale", "abs"]: + with self.subTest(device=device, noise_device=noise_device, operation=op): + # create random data set + data = torch.rand(10000, 3, device=device) + # define standard deviation and mean + std = torch.tensor([0.1, 0.2, 0.3], device=noise_device) + mean = torch.tensor([0.4, 0.5, 0.6], device=noise_device) + # create noise config + noise_cfg = noise.GaussianNoiseCfg(std=std, mean=mean, operation=op) + + for i in range(10): + # apply noise + noisy_data = noise_cfg.func(data, cfg=noise_cfg) + # calculate resulting noise compared to original data set + if op == "add": + std_result, mean_result = torch.std_mean(noisy_data - data, dim=0) + elif op == "scale": + std_result, mean_result = torch.std_mean(noisy_data / data, dim=0) + elif op == "abs": + std_result, mean_result = torch.std_mean(noisy_data, dim=0) + + self.assertTrue(noise_cfg.mean.device, device) + self.assertTrue(noise_cfg.std.device, device) + torch.testing.assert_close(noise_cfg.std, std_result, atol=1e-2, rtol=1e-2) + torch.testing.assert_close(noise_cfg.mean, mean_result, atol=1e-2, rtol=1e-2) + + def test_uniform_noise(self): + """Test uniform_noise function.""" + for device in ["cpu", "cuda"]: + for noise_device in ["cpu", "cuda"]: + for op in ["add", "scale", "abs"]: + with self.subTest(device=device, noise_device=noise_device, operation=op): + # create random data set + data = torch.rand(10000, 3, device=device) + # define uniform minimum and maximum + n_min = torch.tensor([0.1, 0.2, 0.3], device=noise_device) + n_max = torch.tensor([0.4, 0.5, 0.6], device=noise_device) + # create noise config + noise_cfg = noise.UniformNoiseCfg(n_max=n_max, n_min=n_min, operation=op) + + for i in range(10): + # apply noise + noisy_data = noise_cfg.func(data, cfg=noise_cfg) + # calculate resulting noise compared to original data set + if op == "add": + min_result, _ = torch.min(noisy_data - data, dim=0) + max_result, _ = torch.max(noisy_data - data, dim=0) + elif op == "scale": + min_result, _ = torch.min(torch.div(noisy_data, data), dim=0) + max_result, _ = torch.max(torch.div(noisy_data, data), dim=0) + elif op == "abs": + min_result, _ = torch.min(noisy_data, dim=0) + max_result, _ = torch.max(noisy_data, dim=0) + + self.assertTrue(noise_cfg.n_min.device, device) + self.assertTrue(noise_cfg.n_max.device, device) + self.assertTrue(all(torch.le(noise_cfg.n_min, min_result).tolist())) + self.assertTrue(all(torch.ge(noise_cfg.n_max, max_result).tolist())) + + def test_constant_noise(self): + """Test constant_noise""" + for device in ["cpu", "cuda"]: + for noise_device in ["cpu", "cuda"]: + for op in ["add", "scale", "abs"]: + with self.subTest(device=device, noise_device=noise_device, operation=op): + # create random data set + data = torch.rand(10000, 3, device=device) + # define a bias + bias = torch.tensor([0.1, 0.2, 0.3], device=noise_device) + # create noise config + noise_cfg = noise.ConstantNoiseCfg(bias=bias, operation=op) + + for i in range(10): + # apply noise + noisy_data = noise_cfg.func(data, cfg=noise_cfg) + # calculate resulting noise compared to original data set + if op == "add": + bias_result = noisy_data - data + elif op == "scale": + bias_result = noisy_data / data + elif op == "abs": + bias_result = noisy_data + + self.assertTrue(noise_cfg.bias.device, device) + torch.testing.assert_close(noise_cfg.bias.repeat(data.shape[0], 1), bias_result) + + +if __name__ == "__main__": + run_tests() From cc7112c62231ab284ba5a493bdb3ea527452cf8b Mon Sep 17 00:00:00 2001 From: Mayank Mittal <12863862+Mayankm96@users.noreply.github.com> Date: Sat, 12 Oct 2024 13:31:13 +0200 Subject: [PATCH 013/111] Removes extension startup messages from the Simulation App (#1217) # Description This MR disables terminal spamming when launching the app. With the flag `/app/enableStdoutOutput` disabled, we no longer have the app output when the kit extensions are startup. Fixes #1097, #196 ## Type of change - Breaking change (fix or feature that would cause existing functionality to not work as expected) ## Screenshots ``` ./isaaclab.sh -p source/standalone/environments/zero_agent.py --task Isaac-Velocity-Rough-Anymal-C-v0 --num_envs 32 ``` Output: ``` [INFO] Using python from: /home/mayank/mambaforge/envs/isaaclab-rsl/bin/python [INFO][AppLauncher]: Loading experience file: /home/mayank/git_nv/IsaacLab/source/extensions/omni.isaac.lab/omni/isaac/lab/app/../../../../../../apps/isaaclab.python.kit Loading user config located at: '/media/vulcan/packman-repo/chk/kit-kernel/106.1.0+release.140981.10a4b5c0.gl.linux-x86_64.release/data/Kit/Isaac-Sim/4.2/user.config.json' [Info] [carb] Logging to file: /media/vulcan/packman-repo/chk/kit-kernel/106.1.0+release.140981.10a4b5c0.gl.linux-x86_64.release/logs/Kit/Isaac-Sim/4.2/kit_20241011_180901.log 2024-10-11 16:09:01 [0ms] [Warning] [omni.kit.app.plugin] No crash reporter present, dumps uploading isn't available. |---------------------------------------------------------------------------------------------| | Driver Version: 535.183.01 | Graphics API: Vulkan |=============================================================================================| | GPU | Name | Active | LDA | GPU Memory | Vendor-ID | LUID | | | | | | | Device-ID | UUID | | | | | | | Bus-ID | | |---------------------------------------------------------------------------------------------| | 0 | NVIDIA RTX A6000 | Yes: 0 | | 49386 MB | 10de | 0 | | | | | | | 2230 | bffafd0e.. | | | | | | | 68 | | |=============================================================================================| | OS: 20.04.6 LTS (Focal Fossa) ubuntu, Version: 20.04.6, Kernel: 5.15.0-122-generic | XServer Vendor: The X.Org Foundation, XServer Version: 12013000 (1.20.13.0) | Processor: Intel(R) Core(TM) i9-9820X CPU @ 3.30GHz | Cores: 10 | Logical: 20 |---------------------------------------------------------------------------------------------| | Total Memory (MB): 63970 | Free Memory: 41524 | Total Page/Swap (MB): 2047 | Free Page/Swap: 2047 |---------------------------------------------------------------------------------------------| 2024-10-11 16:09:07 [6,565ms] [Warning] [omni.replicator.core.scripts.annotators] Annotator PostProcessDispatch is already registered, overwriting annotator template 2024-10-11 16:09:08 [7,613ms] [Warning] [omni.kit.widget.cache_indicator.cache_state_menu] Unable to detect Omniverse Cache Server. Consider installing it for better IO performance. [INFO]: Parsing configuration from: 2024-10-11 16:09:17 [16,685ms] [Warning] [omni.isaac.lab.envs.manager_based_env] Seed not set for the environment. The environment creation may not be deterministic. [INFO]: Base environment: Environment device : cuda:0 Environment seed : None Physics step-size : 0.005 Rendering step-size : 0.02 Environment step-size : 0.02 [INFO] Generating terrains based on curriculum took : 1.881988 seconds [INFO]: Time taken for scene creation : 4.564743 seconds [INFO]: Scene manager: Number of environments: 32 Environment spacing : 2.5 Source prim name : /World/envs/env_0 Global prim paths : ['/World/ground'] Replicate physics : True [INFO]: Starting the simulation. This may take a few seconds. Please wait... 2024-10-11 16:09:29 [27,861ms] [Warning] [omni.hydra.scene_delegate.plugin] Calling getBypassRenderSkelMeshProcessing for prim /World/envs/env_0/Robot/LF_THIGH/visuals.proto_mesh_1_id1 that has not been populated 2024-10-11 16:09:29 [27,880ms] [Warning] [omni.hydra] Mesh '/World/envs/env_0/Robot/base/visuals.proto_mesh_0_id0' has corrupted data in primvar 'st': buffer size 702 doesn't match expected size 12828 in faceVarying primvars [INFO]: Time taken for simulation start : 7.193578 seconds [INFO] Command Manager: contains 1 active terms. +------------------------------------------------+ | Active Command Terms | +-------+---------------+------------------------+ | Index | Name | Type | +-------+---------------+------------------------+ | 0 | base_velocity | UniformVelocityCommand | +-------+---------------+------------------------+ [INFO] Action Manager: contains 1 active terms. +------------------------------------+ | Active Action Terms (shape: 12) | +--------+-------------+-------------+ | Index | Name | Dimension | +--------+-------------+-------------+ | 0 | joint_pos | 12 | +--------+-------------+-------------+ Module omni.isaac.lab.utils.warp.kernels 6cb40f6 load on device 'cuda:0' took 0.44 ms [INFO] Observation Manager: contains 1 groups. +----------------------------------------------------------+ | Active Observation Terms in Group: 'policy' (shape: (235,)) | +-----------+--------------------------------+-------------+ | Index | Name | Shape | +-----------+--------------------------------+-------------+ | 0 | base_lin_vel | (3,) | | 1 | base_ang_vel | (3,) | | 2 | projected_gravity | (3,) | | 3 | velocity_commands | (3,) | | 4 | joint_pos | (12,) | | 5 | joint_vel | (12,) | | 6 | actions | (12,) | | 7 | height_scan | (187,) | +-----------+--------------------------------+-------------+ [INFO] Event Manager: contains 3 active terms. +--------------------------------------+ | Active Event Terms in Mode: 'startup' | +----------+---------------------------+ | Index | Name | +----------+---------------------------+ | 0 | physics_material | | 1 | add_base_mass | +----------+---------------------------+ +---------------------------------------+ | Active Event Terms in Mode: 'reset' | +--------+------------------------------+ | Index | Name | +--------+------------------------------+ | 0 | base_external_force_torque | | 1 | reset_base | | 2 | reset_robot_joints | +--------+------------------------------+ +----------------------------------------------+ | Active Event Terms in Mode: 'interval' | +-------+------------+-------------------------+ | Index | Name | Interval time range (s) | +-------+------------+-------------------------+ | 0 | push_robot | (10.0, 15.0) | +-------+------------+-------------------------+ [INFO] Termination Manager: contains 2 active terms. +---------------------------------+ | Active Termination Terms | +-------+--------------+----------+ | Index | Name | Time Out | +-------+--------------+----------+ | 0 | time_out | True | | 1 | base_contact | False | +-------+--------------+----------+ [INFO] Reward Manager: contains 11 active terms. +-----------------------------------------+ | Active Reward Terms | +-------+----------------------+----------+ | Index | Name | Weight | +-------+----------------------+----------+ | 0 | track_lin_vel_xy_exp | 1.0 | | 1 | track_ang_vel_z_exp | 0.5 | | 2 | lin_vel_z_l2 | -2.0 | | 3 | ang_vel_xy_l2 | -0.05 | | 4 | dof_torques_l2 | -1e-05 | | 5 | dof_acc_l2 | -2.5e-07 | | 6 | action_rate_l2 | -0.01 | | 7 | feet_air_time | 0.125 | | 8 | undesired_contacts | -1.0 | | 9 | flat_orientation_l2 | 0.0 | | 10 | dof_pos_limits | 0.0 | +-------+----------------------+----------+ [INFO] Curriculum Manager: contains 1 active terms. +---------------------------+ | Active Curriculum Terms | +--------+------------------+ | Index | Name | +--------+------------------+ | 0 | terrain_levels | +--------+------------------+ Creating window for environment. [INFO]: Completed setting up the environment... [INFO]: Gym observation space: Dict('policy': Box(-inf, inf, (32, 235), float32)) [INFO]: Gym action space: Box(-inf, inf, (32, 12), float32) ``` ## Checklist - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [x] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [ ] I have added tests that prove my fix is effective or that my feature works - [ ] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [x] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --- docs/source/refs/troubleshooting.rst | 20 +++++++++++++++++++ source/apps/isaaclab.python.headless.kit | 4 ++++ source/apps/isaaclab.python.kit | 7 +++++++ .../omni/isaac/lab/app/app_launcher.py | 17 +++++++++++++++- .../omni/isaac/lab/sim/simulation_context.py | 10 ++++++---- .../omni/isaac/lab/utils/warp/ops.py | 3 +++ 6 files changed, 56 insertions(+), 5 deletions(-) diff --git a/docs/source/refs/troubleshooting.rst b/docs/source/refs/troubleshooting.rst index 09830e8812..91c251c373 100644 --- a/docs/source/refs/troubleshooting.rst +++ b/docs/source/refs/troubleshooting.rst @@ -35,6 +35,26 @@ In the above example, the log file is located at ``.../logs/Kit/Isaac-Sim/2023.1 You can open this file to check the internal logs from the simulator. Also when reporting issues, please include this log file to help us debug the issue. +Changing logging channel levels for the simulator +------------------------------------------------- + +By default, the simulator logs messages at the ``WARN`` level and above on the terminal. You can change the logging +channel levels to get more detailed logs. The logging channel levels can be set through Omniverse's logging system. + +To obtain more detailed logs, you can run your application with the following flags: + +* ``--info``: This flag logs messages at the ``INFO`` level and above. +* ``--verbose``: This flag logs messages at the ``VERBOSE`` level and above. + +For instance, to run a standalone script with verbose logging, you can use the following command: + +.. code-block:: bash + + # Run the standalone script with info logging + ./isaaclab.sh -p source/standalone/tutorials/00_sim/create_empty.py --headless --info + +For more fine-grained control, you can modify the logging channels through the ``omni.log`` module. +For more information, please refer to its `documentation `__. Using CPU Scaling Governor for performance ------------------------------------------ diff --git a/source/apps/isaaclab.python.headless.kit b/source/apps/isaaclab.python.headless.kit index 9eace6a1a6..3435606b7b 100644 --- a/source/apps/isaaclab.python.headless.kit +++ b/source/apps/isaaclab.python.headless.kit @@ -34,6 +34,10 @@ renderer.active = "rtx" app.content.emptyStageOnStart = false +# Disable print outs on extension startup information +# this only disables the app print_and_log function +app.enableStdoutOutput = false + # Setting the port for the embedded http server exts."omni.services.transport.server.http".port = 8211 diff --git a/source/apps/isaaclab.python.kit b/source/apps/isaaclab.python.kit index df788530fa..fdf924a6ad 100644 --- a/source/apps/isaaclab.python.kit +++ b/source/apps/isaaclab.python.kit @@ -124,6 +124,10 @@ exts."omni.kit.menu.utils".logDeprecated = false # app.content.emptyStageOnStart = false app.file.ignoreUnsavedOnExit = true # prevents save dialog when exiting +# disable print outs on extension startup information +# this only disables the app print_and_log function +app.enableStdoutOutput = false + # deprecate support for old kit.ui.menu app.menu.legacy_mode = false # use omni.ui.Menu for the MenuBar @@ -137,6 +141,9 @@ exts."omni.kit.window.viewport".blockingGetViewportDrawable = false exts."omni.kit.test".includeTests = [ "*isaac*" ] +# set the default ros bridge to disable on startup +isaac.startup.ros_bridge_extension = "" + [settings.app.python] # These disable the kit app from also printing out python output, which gets confusing interceptSysStdOutput = false diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/app/app_launcher.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/app/app_launcher.py index 8f9f5adc19..0453cc4cc5 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/app/app_launcher.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/app/app_launcher.py @@ -254,7 +254,12 @@ def add_app_launcher_args(parser: argparse.ArgumentParser) -> None: arg_group.add_argument( "--verbose", # Note: This is read by SimulationApp through sys.argv action="store_true", - help="Enable verbose terminal output from the SimulationApp.", + help="Enable verbose-level log output from the SimulationApp.", + ) + arg_group.add_argument( + "--info", # Note: This is read by SimulationApp through sys.argv + action="store_true", + help="Enable info-level log output from the SimulationApp.", ) arg_group.add_argument( "--experience", @@ -552,6 +557,8 @@ def _config_resolution(self, launcher_args: dict): " The file does not exist." ) + # Resolve the absolute path of the experience file + self._sim_experience_file = os.path.abspath(self._sim_experience_file) print(f"[INFO][AppLauncher]: Loading experience file: {self._sim_experience_file}") # Remove all values from input keyword args which are not meant for SimulationApp # Assign all the passed settings to a dictionary for the simulation app @@ -572,8 +579,16 @@ def _create_app(self): for key in found_modules: hacked_modules[key] = sys.modules[key] del sys.modules[key] + + # disable sys stdout and stderr to avoid printing the warning messages + # this is mainly done to purge the print statements from the simulation app + if "--verbose" not in sys.argv and "--info" not in sys.argv: + sys.stdout = open(os.devnull, "w") # noqa: SIM115 # launch simulation app self._app = SimulationApp(self._sim_app_config, experience=self._sim_experience_file) + # enable sys stdout and stderr + sys.stdout = sys.__stdout__ + # add Isaac Lab modules back to sys.modules for key, value in hacked_modules.items(): sys.modules[key] = value diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/simulation_context.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/simulation_context.py index a8b4cd4fae..b00013a18d 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/simulation_context.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/simulation_context.py @@ -297,8 +297,8 @@ def get_version(self) -> tuple[int, int, int]: Operations - New utilities. """ - @staticmethod def set_camera_view( + self, eye: tuple[float, float, float], target: tuple[float, float, float], camera_prim_path: str = "/OmniverseKit_Persp", @@ -315,7 +315,9 @@ def set_camera_view( camera_prim_path: The path to the camera primitive in the stage. Defaults to "/OmniverseKit_Persp". """ - set_camera_view(eye, target, camera_prim_path) + # safe call only if we have a GUI or viewport rendering enabled + if self._has_gui or self._offscreen_render or self._render_viewport: + set_camera_view(eye, target, camera_prim_path) def set_render_mode(self, mode: RenderMode): """Change the current render mode of the simulation. @@ -614,7 +616,7 @@ def _app_control_on_stop_callback(self, event: carb.events.IEvent): if event.type == int(omni.timeline.TimelineEventType.STOP): # keep running the simulator when configured to not shutdown the app if self._has_gui and sys.exc_info()[0] is None: - self.app.print_and_log( + carb.log_warn( "Simulation is stopped. The app will keep running with physics disabled." " Press Ctrl+C or close the window to exit the app." ) @@ -649,7 +651,7 @@ def _app_control_on_stop_callback(self, event: carb.events.IEvent): omni.usd.get_context().close_stage() # print logging information - self.app.print_and_log("Simulation is stopped. Shutting down the app...") + print("[INFO]: Simulation is stopped. Shutting down the app.") # Cleanup any running tracy instances so data is not lost try: diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/utils/warp/ops.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/utils/warp/ops.py index 5c128fa1ea..23658152e0 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/utils/warp/ops.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/utils/warp/ops.py @@ -13,6 +13,9 @@ import warp as wp +# disable warp module initialization messages +wp.config.quiet = True +# initialize the warp module wp.init() from . import kernels From 1b8943c120cf863dbf1c93a5b1d25fd96c9df68f Mon Sep 17 00:00:00 2001 From: Pascal Roth <57946385+pascal-roth@users.noreply.github.com> Date: Sun, 13 Oct 2024 12:28:23 +0200 Subject: [PATCH 014/111] Removes additional sbatch and fixes default profile in cluster deployment (#1229) # Description In the slum workflow, currently, there was an unnecessary `sbatch` command; this PR removes it. In addition, the profile argument was marked as optional, but when a job was submitted, and job arguments were passed, it became necessary. This PR fixes this behavior. ## Type of change - Bug fix (non-breaking change which fixes an issue) ## Checklist - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [ ] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [ ] I have added tests that prove my fix is effective or that my feature works - [ ] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [x] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --- docker/cluster/cluster_interface.sh | 18 +++++++++++------- 1 file changed, 11 insertions(+), 7 deletions(-) diff --git a/docker/cluster/cluster_interface.sh b/docker/cluster/cluster_interface.sh index ec93eefee0..fd325e4ca4 100755 --- a/docker/cluster/cluster_interface.sh +++ b/docker/cluster/cluster_interface.sh @@ -62,11 +62,9 @@ submit_job() { case $CLUSTER_JOB_SCHEDULER in "SLURM") - CMD=sbatch job_script_file=submit_job_slurm.sh ;; "PBS") - CMD=bash job_script_file=submit_job_pbs.sh ;; *) @@ -75,7 +73,7 @@ submit_job() { ;; esac - ssh $CLUSTER_LOGIN "cd $CLUSTER_ISAACLAB_DIR && $CMD $CLUSTER_ISAACLAB_DIR/docker/cluster/$job_script_file \"$CLUSTER_ISAACLAB_DIR\" \"isaac-lab-$profile\" ${@}" + ssh $CLUSTER_LOGIN "cd $CLUSTER_ISAACLAB_DIR && bash $CLUSTER_ISAACLAB_DIR/docker/cluster/$job_script_file \"$CLUSTER_ISAACLAB_DIR\" \"isaac-lab-$profile\" ${@}" } #== @@ -162,11 +160,17 @@ case $command in scp $SCRIPT_DIR/exports/isaac-lab-$profile.tar $CLUSTER_LOGIN:$CLUSTER_SIF_PATH/isaac-lab-$profile.tar ;; job) - [ $# -ge 1 ] && profile=$1 && shift + if [ $# -ge 1 ]; then + passed_profile=$1 + if [ -f ".env.$passed_profile" ]; then + profile=$passed_profile + shift + fi + fi job_args="$@" - echo "Executing job command" - [ -n "$profile" ] && echo "Using profile: $profile" - [ -n "$job_args" ] && echo "Job arguments: $job_args" + echo "[INFO] Executing job command" + [ -n "$profile" ] && echo -e "\tUsing profile: $profile" + [ -n "$job_args" ] && echo -e "\tJob arguments: $job_args" source $SCRIPT_DIR/.env.cluster # Get current date and time current_datetime=$(date +"%Y%m%d_%H%M%S") From f879aa6a80e2b9e6dba1263e8f5938ccbaa65efc Mon Sep 17 00:00:00 2001 From: Wei Yang Date: Sun, 13 Oct 2024 03:40:10 -0700 Subject: [PATCH 015/111] Fixes the checkpoint loading error in RSL-RL training script (#1210) # Description An error of `No checkpoints in the directory` will throw when resume from a previous training with `--video` set. This is because a new log folder will be created before the check. This MR fixes this issue by loading the checkpoint before. Fixes #1209 ## Type of change - Bug fix (non-breaking change which fixes an issue) ## Checklist - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [ ] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [ ] I have added tests that prove my fix is effective or that my feature works - [ ] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [x] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --- CONTRIBUTORS.md | 1 + source/standalone/workflows/rsl_rl/train.py | 9 ++++++--- 2 files changed, 7 insertions(+), 3 deletions(-) diff --git a/CONTRIBUTORS.md b/CONTRIBUTORS.md index b84c3a0aa8..244b910786 100644 --- a/CONTRIBUTORS.md +++ b/CONTRIBUTORS.md @@ -63,6 +63,7 @@ Guidelines for modifications: * Rosario Scalise * Shafeef Omar * Vladimir Fokow +* Wei Yang * Xavier Nal * Yang Jin * Zhengyu Zhang diff --git a/source/standalone/workflows/rsl_rl/train.py b/source/standalone/workflows/rsl_rl/train.py index f02e0a3c0f..6c73798315 100644 --- a/source/standalone/workflows/rsl_rl/train.py +++ b/source/standalone/workflows/rsl_rl/train.py @@ -99,6 +99,11 @@ def main(env_cfg: ManagerBasedRLEnvCfg | DirectRLEnvCfg | DirectMARLEnvCfg, agen # create isaac environment env = gym.make(args_cli.task, cfg=env_cfg, render_mode="rgb_array" if args_cli.video else None) + + # save resume path before creating a new log_dir + if agent_cfg.resume: + resume_path = get_checkpoint_path(log_root_path, agent_cfg.load_run, agent_cfg.load_checkpoint) + # wrap for video recording if args_cli.video: video_kwargs = { @@ -122,10 +127,8 @@ def main(env_cfg: ManagerBasedRLEnvCfg | DirectRLEnvCfg | DirectMARLEnvCfg, agen runner = OnPolicyRunner(env, agent_cfg.to_dict(), log_dir=log_dir, device=agent_cfg.device) # write git state to logs runner.add_git_repo_to_log(__file__) - # save resume path before creating a new log_dir + # load the checkpoint if agent_cfg.resume: - # get path to previous checkpoint - resume_path = get_checkpoint_path(log_root_path, agent_cfg.load_run, agent_cfg.load_checkpoint) print(f"[INFO]: Loading model checkpoint from: {resume_path}") # load previously trained model runner.load(resume_path) From 8ee6c97265f19e08ec5a79abb9627236958b297e Mon Sep 17 00:00:00 2001 From: Alexander Poddubny <143108850+nv-apoddubny@users.noreply.github.com> Date: Mon, 14 Oct 2024 02:49:54 -0700 Subject: [PATCH 016/111] Makes pre and post merge pipelines more flexible on the Isaac SIM base image version (#1211) # Description Making the base image version a parameter so the pipelines can use different versions without the need to hardcode that. --- .aws/postmerge-ci-buildspec.yml | 2 +- .aws/premerge-ci-buildspec.yml | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/.aws/postmerge-ci-buildspec.yml b/.aws/postmerge-ci-buildspec.yml index e071d7db09..9958483c07 100644 --- a/.aws/postmerge-ci-buildspec.yml +++ b/.aws/postmerge-ci-buildspec.yml @@ -34,7 +34,7 @@ phases: docker login -u \$oauthtoken -p $NGC_TOKEN nvcr.io docker build -t $IMAGE_NAME:$COMBINED_TAG \ --build-arg ISAACSIM_BASE_IMAGE_ARG=$ISAACSIM_BASE_IMAGE \ - --build-arg ISAACSIM_VERSION_ARG=4.2.0 \ + --build-arg ISAACSIM_VERSION_ARG=$ISAACSIM_BASE_VERSION \ --build-arg ISAACSIM_ROOT_PATH_ARG=/isaac-sim \ --build-arg ISAACLAB_PATH_ARG=/workspace/isaaclab \ --build-arg DOCKER_USER_HOME_ARG=/root \ diff --git a/.aws/premerge-ci-buildspec.yml b/.aws/premerge-ci-buildspec.yml index 4fa2372b4e..744f92786a 100644 --- a/.aws/premerge-ci-buildspec.yml +++ b/.aws/premerge-ci-buildspec.yml @@ -69,7 +69,7 @@ phases: cd $SRC_DIR DOCKER_BUILDKIT=1 docker build -t isaac-lab-dev \ --build-arg ISAACSIM_BASE_IMAGE_ARG=$ISAACSIM_BASE_IMAGE \ - --build-arg ISAACSIM_VERSION_ARG=4.2.0 \ + --build-arg ISAACSIM_VERSION_ARG=$ISAACSIM_BASE_VERSION \ --build-arg ISAACSIM_ROOT_PATH_ARG=/isaac-sim \ --build-arg ISAACLAB_PATH_ARG=/workspace/isaaclab \ --build-arg DOCKER_USER_HOME_ARG=/root \ From 94f46109620e5393b3df8e9ff6f7640f296ffad0 Mon Sep 17 00:00:00 2001 From: Mayank Mittal <12863862+Mayankm96@users.noreply.github.com> Date: Mon, 14 Oct 2024 16:57:22 +0200 Subject: [PATCH 017/111] Disables backward pass compilation of warp kernels (#1222) # Description Many of the warp kernels don't need backward pass compilation. This MR disables the computation of the backward passes within the kernels. This should reduce the kernel compile times. Reference: https://nvidia.github.io/warp/configuration.html#kernel-settings ## Type of change - Bug fix (non-breaking change which fixes an issue) ## Checklist - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [x] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [ ] I have added tests that prove my fix is effective or that my feature works - [ ] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [x] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --- .../omni.isaac.lab/omni/isaac/lab/utils/warp/kernels.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/utils/warp/kernels.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/utils/warp/kernels.py index e401fc6e72..f7efbc78a6 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/utils/warp/kernels.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/utils/warp/kernels.py @@ -10,7 +10,7 @@ import warp as wp -@wp.kernel +@wp.kernel(enable_backward=False) def raycast_mesh_kernel( mesh: wp.uint64, ray_starts: wp.array(dtype=wp.vec3), @@ -75,7 +75,7 @@ def raycast_mesh_kernel( ray_face_id[tid] = f -@wp.kernel +@wp.kernel(enable_backward=False) def reshape_tiled_image( tiled_image_buffer: Any, batched_image: Any, From 69df26b7f9ddf8a8054d7e0941e1720bbc6600be Mon Sep 17 00:00:00 2001 From: Mayank Mittal <12863862+Mayankm96@users.noreply.github.com> Date: Mon, 14 Oct 2024 17:02:10 +0200 Subject: [PATCH 018/111] Switches from `carb` to `omni.log` for logging (#1215) # Description Earlier, we used [`Carbonite SDK`](https://docs.omniverse.nvidia.com/kit/docs/carbonite/latest/api/dir_carb_logging.html) to log directly. However, this has limited functionalities compared to [`omni.log`](https://docs.omniverse.nvidia.com/kit/docs/carbonite/latest/api/namespace_omni__log.html) in Omniverse. Using `omni.log`, you can fine-grain the channels and print levels better. Link to omni.log documentation: https://docs.omniverse.nvidia.com/kit/docs/carbonite/latest/docs/omni.log/Logging.html This MR migrates all `carb` references to the new API. ## Type of change - Bug fix (non-breaking change which fixes an issue) - Breaking change (fix or feature that would cause existing functionality to not work as expected) ## Screenshot Checking the performance: ``` ./isaaclab.sh -p source/standalone/benchmarks/benchmark_load_robot.py --num_envs 2048 --robot g1 --headless ``` **Before (carb logging)** [INFO]: App start time: 4676.57 ms [INFO]: Imports time: 2008.77 ms [INFO]: Scene creation time: 2966.36 ms [INFO]: Sim start time: 5782.76 ms [INFO]: Per step time: 15.80 ms **After (omni.log logging)** [INFO]: App start time: 4833.56 ms [INFO]: Imports time: 1983.67 ms [INFO]: Scene creation time: 2792.97 ms [INFO]: Sim start time: 5805.97 ms [INFO]: Per step time: 15.86 ms ## Checklist - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [x] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [ ] I have added tests that prove my fix is effective or that my feature works - [ ] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [x] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --- .../lab/assets/articulation/articulation.py | 26 +++++++++---------- .../deformable_object/deformable_object.py | 16 ++++++------ .../lab/assets/rigid_object/rigid_object.py | 10 +++---- .../omni/isaac/lab/envs/direct_marl_env.py | 6 ++--- .../omni/isaac/lab/envs/direct_rl_env.py | 6 ++--- .../omni/isaac/lab/envs/manager_based_env.py | 6 ++--- .../envs/mdp/actions/binary_joint_actions.py | 4 +-- .../lab/envs/mdp/actions/joint_actions.py | 4 +-- .../mdp/actions/joint_actions_to_limits.py | 4 +-- .../envs/mdp/actions/non_holonomic_actions.py | 6 ++--- .../envs/mdp/actions/task_space_actions.py | 6 ++--- .../omni/isaac/lab/managers/event_manager.py | 6 ++--- .../omni/isaac/lab/managers/manager_base.py | 4 +-- .../omni/isaac/lab/scene/interactive_scene.py | 4 +-- .../omni/isaac/lab/sensors/camera/camera.py | 2 +- .../frame_transformer/frame_transformer.py | 10 +++---- .../lab/sensors/ray_caster/ray_caster.py | 8 +++--- .../omni/isaac/lab/sim/schemas/schemas.py | 10 +++---- .../omni/isaac/lab/sim/simulation_context.py | 7 ++--- .../lab/sim/spawners/from_files/from_files.py | 4 +-- .../isaac/lab/sim/spawners/sensors/sensors.py | 4 +-- .../omni/isaac/lab/sim/utils.py | 12 ++++----- .../isaac/lab/terrains/terrain_generator.py | 6 ++--- .../check_floating_base_made_fixed.py | 4 +-- .../deps/isaacsim/check_legged_robot_clone.py | 4 +-- .../test/deps/isaacsim/check_ref_count.py | 4 +-- .../robomimic_data_collector.py | 8 +++--- .../state_machine/open_cabinet_sm.py | 16 +++--------- .../teleoperation/teleop_se3_agent.py | 4 +-- 29 files changed, 102 insertions(+), 109 deletions(-) diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/articulation/articulation.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/articulation/articulation.py index 9357d90ca5..a604254caa 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/articulation/articulation.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/articulation/articulation.py @@ -13,8 +13,8 @@ from prettytable import PrettyTable from typing import TYPE_CHECKING -import carb import omni.isaac.core.utils.stage as stage_utils +import omni.log import omni.physics.tensors.impl.api as physx from omni.isaac.core.utils.types import ArticulationActions from pxr import PhysxSchema, UsdPhysics @@ -542,7 +542,7 @@ def write_joint_limits_to_sim( # update default joint pos to stay within the new limits if torch.any((self._data.default_joint_pos < limits[..., 0]) | (self._data.default_joint_pos > limits[..., 1])): self._data.default_joint_pos = torch.clamp(self._data.default_joint_pos, limits[..., 0], limits[..., 1]) - carb.log_warn( + omni.log.warn( "Some default joint positions are outside of the range of the new joint limits. Default joint positions" " will be clamped to be within the new joint limits." ) @@ -925,13 +925,13 @@ def _initialize_impl(self): raise RuntimeError(f"Failed to create articulation at: {self.cfg.prim_path}. Please check PhysX logs.") # log information about the articulation - carb.log_info(f"Articulation initialized at: {self.cfg.prim_path} with root '{root_prim_path_expr}'.") - carb.log_info(f"Is fixed root: {self.is_fixed_base}") - carb.log_info(f"Number of bodies: {self.num_bodies}") - carb.log_info(f"Body names: {self.body_names}") - carb.log_info(f"Number of joints: {self.num_joints}") - carb.log_info(f"Joint names: {self.joint_names}") - carb.log_info(f"Number of fixed tendons: {self.num_fixed_tendons}") + omni.log.info(f"Articulation initialized at: {self.cfg.prim_path} with root '{root_prim_path_expr}'.") + omni.log.info(f"Is fixed root: {self.is_fixed_base}") + omni.log.info(f"Number of bodies: {self.num_bodies}") + omni.log.info(f"Body names: {self.body_names}") + omni.log.info(f"Number of joints: {self.num_joints}") + omni.log.info(f"Joint names: {self.joint_names}") + omni.log.info(f"Number of fixed tendons: {self.num_fixed_tendons}") # container for data access self._data = ArticulationData(self.root_physx_view, self.device) @@ -1142,7 +1142,7 @@ def _process_actuators_cfg(self): velocity_limit=usd_velocity_limit[:, joint_ids], ) # log information on actuator groups - carb.log_info( + omni.log.info( f"Actuator collection: {actuator_name} with model '{actuator_cfg.class_type.__name__}' and" f" joint names: {joint_names} [{joint_ids}]." ) @@ -1177,7 +1177,7 @@ def _process_actuators_cfg(self): # perform some sanity checks to ensure actuators are prepared correctly total_act_joints = sum(actuator.num_joints for actuator in self.actuators.values()) if total_act_joints != (self.num_joints - self.num_fixed_tendons): - carb.log_warn( + omni.log.warn( "Not all actuators are configured! Total number of actuated joints not equal to number of" f" joints available: {total_act_joints} != {self.num_joints - self.num_fixed_tendons}." ) @@ -1336,7 +1336,7 @@ def _log_articulation_joint_info(self): effort_limits[index], ]) # convert table to string - carb.log_info(f"Simulation parameters for joints in {self.cfg.prim_path}:\n" + table.get_string()) + omni.log.info(f"Simulation parameters for joints in {self.cfg.prim_path}:\n" + table.get_string()) # read out all tendon parameters from simulation if self.num_fixed_tendons > 0: @@ -1372,4 +1372,4 @@ def _log_articulation_joint_info(self): ft_offsets[index], ]) # convert table to string - carb.log_info(f"Simulation parameters for tendons in {self.cfg.prim_path}:\n" + tendon_table.get_string()) + omni.log.info(f"Simulation parameters for tendons in {self.cfg.prim_path}:\n" + tendon_table.get_string()) diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/deformable_object/deformable_object.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/deformable_object/deformable_object.py index 4a57c316c9..065dd7be18 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/deformable_object/deformable_object.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/deformable_object/deformable_object.py @@ -9,7 +9,7 @@ from collections.abc import Sequence from typing import TYPE_CHECKING -import carb +import omni.log import omni.physics.tensors.impl.api as physx from pxr import PhysxSchema, UsdShade @@ -305,7 +305,7 @@ def _initialize_impl(self): material_prim = mat_prim break if material_prim is None: - carb.log_info( + omni.log.info( f"Failed to find a deformable material binding for '{root_prim.GetPath().pathString}'." " The material properties will be set to default values and are not modifiable at runtime." " If you want to modify the material properties, please ensure that the material is bound" @@ -341,14 +341,14 @@ def _initialize_impl(self): self._material_physx_view = None # log information about the deformable body - carb.log_info(f"Deformable body initialized at: {root_prim_path_expr}") - carb.log_info(f"Number of instances: {self.num_instances}") - carb.log_info(f"Number of bodies: {self.num_bodies}") + omni.log.info(f"Deformable body initialized at: {root_prim_path_expr}") + omni.log.info(f"Number of instances: {self.num_instances}") + omni.log.info(f"Number of bodies: {self.num_bodies}") if self._material_physx_view is not None: - carb.log_info(f"Deformable material initialized at: {material_prim_path_expr}") - carb.log_info(f"Number of instances: {self._material_physx_view.count}") + omni.log.info(f"Deformable material initialized at: {material_prim_path_expr}") + omni.log.info(f"Number of instances: {self._material_physx_view.count}") else: - carb.log_info("No deformable material found. Material properties will be set to default values.") + omni.log.info("No deformable material found. Material properties will be set to default values.") # container for data access self._data = DeformableObjectData(self.root_physx_view, self.device) diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/rigid_object/rigid_object.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/rigid_object/rigid_object.py index 328a3e76c6..e44ee7eddf 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/rigid_object/rigid_object.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/rigid_object/rigid_object.py @@ -9,7 +9,7 @@ from collections.abc import Sequence from typing import TYPE_CHECKING -import carb +import omni.log import omni.physics.tensors.impl.api as physx from pxr import UsdPhysics @@ -299,10 +299,10 @@ def _initialize_impl(self): raise RuntimeError(f"Failed to create rigid body at: {self.cfg.prim_path}. Please check PhysX logs.") # log information about the rigid body - carb.log_info(f"Rigid body initialized at: {self.cfg.prim_path} with root '{root_prim_path_expr}'.") - carb.log_info(f"Number of instances: {self.num_instances}") - carb.log_info(f"Number of bodies: {self.num_bodies}") - carb.log_info(f"Body names: {self.body_names}") + omni.log.info(f"Rigid body initialized at: {self.cfg.prim_path} with root '{root_prim_path_expr}'.") + omni.log.info(f"Number of instances: {self.num_instances}") + omni.log.info(f"Number of bodies: {self.num_bodies}") + omni.log.info(f"Body names: {self.body_names}") # container for data access self._data = RigidObjectData(self.root_physx_view, self.device) diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_marl_env.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_marl_env.py index ab7cb5e3c0..2fad4a0243 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_marl_env.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_marl_env.py @@ -16,9 +16,9 @@ from collections.abc import Sequence from typing import Any, ClassVar -import carb import omni.isaac.core.utils.torch as torch_utils import omni.kit.app +import omni.log from omni.isaac.version import get_version from omni.isaac.lab.managers import EventManager @@ -83,7 +83,7 @@ def __init__(self, cfg: DirectMARLEnvCfg, render_mode: str | None = None, **kwar if self.cfg.seed is not None: self.cfg.seed = self.seed(self.cfg.seed) else: - carb.log_warn("Seed not set for the environment. The environment creation may not be deterministic.") + omni.log.warn("Seed not set for the environment. The environment creation may not be deterministic.") # create a simulation context to control the simulator if SimulationContext.instance() is None: @@ -105,7 +105,7 @@ def __init__(self, cfg: DirectMARLEnvCfg, render_mode: str | None = None, **kwar f"({self.cfg.decimation}). Multiple multiple render calls will happen for each environment step." "If this is not intended, set the render interval to be equal to the decimation." ) - carb.log_warn(msg) + omni.log.warn(msg) # generate scene with Timer("[INFO]: Time taken for scene creation", "scene_creation"): diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_rl_env.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_rl_env.py index 656bf3e2dc..8564b4a916 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_rl_env.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_rl_env.py @@ -16,9 +16,9 @@ from collections.abc import Sequence from typing import Any, ClassVar -import carb import omni.isaac.core.utils.torch as torch_utils import omni.kit.app +import omni.log from omni.isaac.version import get_version from omni.isaac.lab.managers import EventManager @@ -88,7 +88,7 @@ def __init__(self, cfg: DirectRLEnvCfg, render_mode: str | None = None, **kwargs if self.cfg.seed is not None: self.cfg.seed = self.seed(self.cfg.seed) else: - carb.log_warn("Seed not set for the environment. The environment creation may not be deterministic.") + omni.log.warn("Seed not set for the environment. The environment creation may not be deterministic.") # create a simulation context to control the simulator if SimulationContext.instance() is None: @@ -110,7 +110,7 @@ def __init__(self, cfg: DirectRLEnvCfg, render_mode: str | None = None, **kwargs f"({self.cfg.decimation}). Multiple multiple render calls will happen for each environment step." "If this is not intended, set the render interval to be equal to the decimation." ) - carb.log_warn(msg) + omni.log.warn(msg) # generate scene with Timer("[INFO]: Time taken for scene creation", "scene_creation"): diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/manager_based_env.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/manager_based_env.py index 4cc1b86b8c..2e4ac663dc 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/manager_based_env.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/manager_based_env.py @@ -8,8 +8,8 @@ from collections.abc import Sequence from typing import Any -import carb import omni.isaac.core.utils.torch as torch_utils +import omni.log from omni.isaac.lab.managers import ActionManager, EventManager, ObservationManager from omni.isaac.lab.scene import InteractiveScene @@ -78,7 +78,7 @@ def __init__(self, cfg: ManagerBasedEnvCfg): if self.cfg.seed is not None: self.cfg.seed = self.seed(self.cfg.seed) else: - carb.log_warn("Seed not set for the environment. The environment creation may not be deterministic.") + omni.log.warn("Seed not set for the environment. The environment creation may not be deterministic.") # create a simulation context to control the simulator if SimulationContext.instance() is None: @@ -106,7 +106,7 @@ def __init__(self, cfg: ManagerBasedEnvCfg): f"({self.cfg.decimation}). Multiple multiple render calls will happen for each environment step. " "If this is not intended, set the render interval to be equal to the decimation." ) - carb.log_warn(msg) + omni.log.warn(msg) # counter for simulation steps self._sim_step_counter = 0 diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/actions/binary_joint_actions.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/actions/binary_joint_actions.py index 73b2353add..5c2ba3fa15 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/actions/binary_joint_actions.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/actions/binary_joint_actions.py @@ -9,7 +9,7 @@ from collections.abc import Sequence from typing import TYPE_CHECKING -import carb +import omni.log import omni.isaac.lab.utils.string as string_utils from omni.isaac.lab.assets.articulation import Articulation @@ -52,7 +52,7 @@ def __init__(self, cfg: actions_cfg.BinaryJointActionCfg, env: ManagerBasedEnv) self._joint_ids, self._joint_names = self._asset.find_joints(self.cfg.joint_names) self._num_joints = len(self._joint_ids) # log the resolved joint names for debugging - carb.log_info( + omni.log.info( f"Resolved joint names for the action term {self.__class__.__name__}:" f" {self._joint_names} [{self._joint_ids}]" ) diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/actions/joint_actions.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/actions/joint_actions.py index d0ebd20d2b..ee5586b7f2 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/actions/joint_actions.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/actions/joint_actions.py @@ -9,7 +9,7 @@ from collections.abc import Sequence from typing import TYPE_CHECKING -import carb +import omni.log import omni.isaac.lab.utils.string as string_utils from omni.isaac.lab.assets.articulation import Articulation @@ -61,7 +61,7 @@ def __init__(self, cfg: actions_cfg.JointActionCfg, env: ManagerBasedEnv) -> Non ) self._num_joints = len(self._joint_ids) # log the resolved joint names for debugging - carb.log_info( + omni.log.info( f"Resolved joint names for the action term {self.__class__.__name__}:" f" {self._joint_names} [{self._joint_ids}]" ) diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/actions/joint_actions_to_limits.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/actions/joint_actions_to_limits.py index 81f4a82184..4345b4dec6 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/actions/joint_actions_to_limits.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/actions/joint_actions_to_limits.py @@ -9,7 +9,7 @@ from collections.abc import Sequence from typing import TYPE_CHECKING -import carb +import omni.log import omni.isaac.lab.utils.math as math_utils import omni.isaac.lab.utils.string as string_utils @@ -53,7 +53,7 @@ def __init__(self, cfg: actions_cfg.JointPositionToLimitsActionCfg, env: Manager self._joint_ids, self._joint_names = self._asset.find_joints(self.cfg.joint_names) self._num_joints = len(self._joint_ids) # log the resolved joint names for debugging - carb.log_info( + omni.log.info( f"Resolved joint names for the action term {self.__class__.__name__}:" f" {self._joint_names} [{self._joint_ids}]" ) diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/actions/non_holonomic_actions.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/actions/non_holonomic_actions.py index 6344ad256a..fc9ed89d6e 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/actions/non_holonomic_actions.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/actions/non_holonomic_actions.py @@ -9,7 +9,7 @@ from collections.abc import Sequence from typing import TYPE_CHECKING -import carb +import omni.log from omni.isaac.lab.assets.articulation import Articulation from omni.isaac.lab.managers.action_manager import ActionTerm @@ -88,11 +88,11 @@ def __init__(self, cfg: actions_cfg.NonHolonomicActionCfg, env: ManagerBasedEnv) self._joint_ids = [x_joint_id[0], y_joint_id[0], yaw_joint_id[0]] self._joint_names = [x_joint_name[0], y_joint_name[0], yaw_joint_name[0]] # log info for debugging - carb.log_info( + omni.log.info( f"Resolved joint names for the action term {self.__class__.__name__}:" f" {self._joint_names} [{self._joint_ids}]" ) - carb.log_info( + omni.log.info( f"Resolved body name for the action term {self.__class__.__name__}: {self._body_name} [{self._body_idx}]" ) diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/actions/task_space_actions.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/actions/task_space_actions.py index e350514b91..96154116c8 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/actions/task_space_actions.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/actions/task_space_actions.py @@ -9,7 +9,7 @@ from collections.abc import Sequence from typing import TYPE_CHECKING -import carb +import omni.log import omni.isaac.lab.utils.math as math_utils from omni.isaac.lab.assets.articulation import Articulation @@ -70,11 +70,11 @@ def __init__(self, cfg: actions_cfg.DifferentialInverseKinematicsActionCfg, env: self._jacobi_joint_ids = [i + 6 for i in self._joint_ids] # log info for debugging - carb.log_info( + omni.log.info( f"Resolved joint names for the action term {self.__class__.__name__}:" f" {self._joint_names} [{self._joint_ids}]" ) - carb.log_info( + omni.log.info( f"Resolved body name for the action term {self.__class__.__name__}: {self._body_name} [{self._body_idx}]" ) # Avoid indexing across all joints for efficiency diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/event_manager.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/event_manager.py index e8aa7407ed..9843164ba0 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/event_manager.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/event_manager.py @@ -12,7 +12,7 @@ from prettytable import PrettyTable from typing import TYPE_CHECKING -import carb +import omni.log from .manager_base import ManagerBase, ManagerTermBase from .manager_term_cfg import EventTermCfg @@ -157,7 +157,7 @@ def apply( """ # check if mode is valid if mode not in self._mode_term_names: - carb.log_warn(f"Event mode '{mode}' is not defined. Skipping event.") + omni.log.warn(f"Event mode '{mode}' is not defined. Skipping event.") return # check if mode is interval and dt is not provided if mode == "interval" and dt is None: @@ -324,7 +324,7 @@ def _prepare_terms(self): ) if term_cfg.mode != "reset" and term_cfg.min_step_count_between_reset != 0: - carb.log_warn( + omni.log.warn( f"Event term '{term_name}' has 'min_step_count_between_reset' set to a non-zero value" " but the mode is not 'reset'. Ignoring the 'min_step_count_between_reset' value." ) diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/manager_base.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/manager_base.py index a11d0f6fdf..2bc9236cab 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/manager_base.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/manager_base.py @@ -11,7 +11,7 @@ from collections.abc import Sequence from typing import TYPE_CHECKING, Any -import carb +import omni.log import omni.isaac.lab.utils.string as string_utils from omni.isaac.lab.utils import string_to_callable @@ -251,7 +251,7 @@ def _resolve_common_term_cfg(self, term_name: str, term_cfg: ManagerTermBaseCfg, if value.body_ids is not None: msg += f"\n\tBody names: {value.body_names} [{value.body_ids}]" # print the information - carb.log_info(msg) + omni.log.info(msg) # store the entity term_cfg.params[key] = value diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/scene/interactive_scene.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/scene/interactive_scene.py index 8c4b81aaff..85775ba425 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/scene/interactive_scene.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/scene/interactive_scene.py @@ -171,7 +171,7 @@ def clone_environments(self, copy_from_source: bool = False): carb_settings_iface = carb.settings.get_settings() has_multi_assets = carb_settings_iface.get("/isaaclab/spawn/multi_assets") if has_multi_assets and self.cfg.replicate_physics: - carb.log_warn( + omni.log.warn( "Varying assets might have been spawned under different environments." " However, the replicate physics flag is enabled in the 'InteractiveScene' configuration." " This may adversely affect PhysX parsing. We recommend disabling this property." @@ -239,7 +239,7 @@ def physics_scene_path(self) -> str: for prim in self.stage.Traverse(): if prim.HasAPI(PhysxSchema.PhysxSceneAPI): self._physics_scene_path = prim.GetPrimPath().pathString - carb.log_info(f"Physics scene prim path: {self._physics_scene_path}") + omni.log.info(f"Physics scene prim path: {self._physics_scene_path}") break if self._physics_scene_path is None: raise RuntimeError("No physics scene found! Please make sure one exists.") diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/camera/camera.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/camera/camera.py index e5692887d3..49bbbc7ca0 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/camera/camera.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/camera/camera.py @@ -251,7 +251,7 @@ def set_intrinsic_matrices( # TODO: Adjust to handle aperture offsets once supported by omniverse # Internal ticket from rendering team: OM-42611 if params["horizontal_aperture_offset"] > 1e-4 or params["vertical_aperture_offset"] > 1e-4: - carb.log_warn("Camera aperture offsets are not supported by Omniverse. These parameters are ignored.") + omni.log.warn("Camera aperture offsets are not supported by Omniverse. These parameters are ignored.") # change data for corresponding camera index sensor_prim = self._sensor_prims[i] diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/frame_transformer/frame_transformer.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/frame_transformer/frame_transformer.py index 87205cf4cd..62f52ea345 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/frame_transformer/frame_transformer.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/frame_transformer/frame_transformer.py @@ -10,7 +10,7 @@ from collections.abc import Sequence from typing import TYPE_CHECKING -import carb +import omni.log import omni.physics.tensors.impl.api as physx from pxr import UsdPhysics @@ -114,10 +114,10 @@ def _initialize_impl(self): self._apply_source_frame_offset = True # Handle source frame offsets if is_identity_pose(source_frame_offset_pos, source_frame_offset_quat): - carb.log_verbose(f"No offset application needed for source frame as it is identity: {self.cfg.prim_path}") + omni.log.verbose(f"No offset application needed for source frame as it is identity: {self.cfg.prim_path}") self._apply_source_frame_offset = False else: - carb.log_verbose(f"Applying offset to source frame as it is not identity: {self.cfg.prim_path}") + omni.log.verbose(f"Applying offset to source frame as it is not identity: {self.cfg.prim_path}") # Store offsets as tensors (duplicating each env's offsets for ease of multiplication later) self._source_frame_offset_pos = source_frame_offset_pos.unsqueeze(0).repeat(self._num_envs, 1) self._source_frame_offset_quat = source_frame_offset_quat.unsqueeze(0).repeat(self._num_envs, 1) @@ -194,12 +194,12 @@ def _initialize_impl(self): target_offsets[frame_name] = {"pos": offset_pos, "quat": offset_quat} if not self._apply_target_frame_offset: - carb.log_info( + omni.log.info( f"No offsets application needed from '{self.cfg.prim_path}' to target frames as all" f" are identity: {frames[1:]}" ) else: - carb.log_info( + omni.log.info( f"Offsets application needed from '{self.cfg.prim_path}' to the following target frames:" f" {non_identity_offset_frames}" ) diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/ray_caster/ray_caster.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/ray_caster/ray_caster.py index d4ad21b004..8be96c358d 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/ray_caster/ray_caster.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/ray_caster/ray_caster.py @@ -11,7 +11,7 @@ from collections.abc import Sequence from typing import TYPE_CHECKING, ClassVar -import carb +import omni.log import omni.physics.tensors.impl.api as physx import warp as wp from omni.isaac.core.prims import XFormPrimView @@ -144,7 +144,7 @@ def _initialize_impl(self): else: self._view = XFormPrimView(self.cfg.prim_path, reset_xform_properties=False) found_supported_prim_class = True - carb.log_warn(f"The prim at path {prim.GetPath().pathString} is not a physics prim! Using XFormPrimView.") + omni.log.warn(f"The prim at path {prim.GetPath().pathString} is not a physics prim! Using XFormPrimView.") # check if prim view class is found if not found_supported_prim_class: raise RuntimeError(f"Failed to find a valid prim view class for the prim paths: {self.cfg.prim_path}") @@ -188,14 +188,14 @@ def _initialize_warp_meshes(self): indices = np.asarray(mesh_prim.GetFaceVertexIndicesAttr().Get()) wp_mesh = convert_to_warp_mesh(points, indices, device=self.device) # print info - carb.log_info( + omni.log.info( f"Read mesh prim: {mesh_prim.GetPath()} with {len(points)} vertices and {len(indices)} faces." ) else: mesh = make_plane(size=(2e6, 2e6), height=0.0, center_zero=True) wp_mesh = convert_to_warp_mesh(mesh.vertices, mesh.faces, device=self.device) # print info - carb.log_info(f"Created infinite plane mesh prim: {mesh_prim.GetPath()}.") + omni.log.info(f"Created infinite plane mesh prim: {mesh_prim.GetPath()}.") # add the warp mesh to the list RayCaster.meshes[mesh_prim_path] = wp_mesh diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/schemas/schemas.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/schemas/schemas.py index 31a608d579..a39ba10a57 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/schemas/schemas.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/schemas/schemas.py @@ -6,8 +6,8 @@ # needed to import for allowing type-hinting: Usd.Stage | None from __future__ import annotations -import carb import omni.isaac.core.utils.stage as stage_utils +import omni.log import omni.physx.scripts.utils as physx_utils from omni.physx.scripts import deformableUtils as deformable_utils from pxr import PhysxSchema, Usd, UsdPhysics @@ -131,12 +131,12 @@ def modify_articulation_root_properties( # if we found a fixed joint, enable/disable it based on the input # otherwise, create a fixed joint between the world and the root link if existing_fixed_joint_prim is not None: - carb.log_info( + omni.log.info( f"Found an existing fixed joint for the articulation: '{prim_path}'. Setting it to: {fix_root_link}." ) existing_fixed_joint_prim.GetJointEnabledAttr().Set(fix_root_link) elif fix_root_link: - carb.log_info(f"Creating a fixed joint for the articulation: '{prim_path}'.") + omni.log.info(f"Creating a fixed joint for the articulation: '{prim_path}'.") # note: we have to assume that the root prim is a rigid body, # i.e. we don't handle the case where the root prim is not a rigid body but has articulation api on it @@ -500,10 +500,10 @@ def activate_contact_sensors(prim_path: str, threshold: float = 0.0, stage: Usd. rb.CreateSleepThresholdAttr().Set(0.0) # add contact report API with threshold of zero if not child_prim.HasAPI(PhysxSchema.PhysxContactReportAPI): - carb.log_verbose(f"Adding contact report API to prim: '{child_prim.GetPrimPath()}'") + omni.log.verbose(f"Adding contact report API to prim: '{child_prim.GetPrimPath()}'") cr_api = PhysxSchema.PhysxContactReportAPI.Apply(child_prim) else: - carb.log_verbose(f"Contact report API already exists on prim: '{child_prim.GetPrimPath()}'") + omni.log.verbose(f"Contact report API already exists on prim: '{child_prim.GetPrimPath()}'") cr_api = PhysxSchema.PhysxContactReportAPI.Get(stage, child_prim.GetPrimPath()) # set threshold to zero cr_api.CreateThresholdAttr().Set(threshold) diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/simulation_context.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/simulation_context.py index b00013a18d..315ad18d47 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/simulation_context.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/simulation_context.py @@ -16,6 +16,7 @@ import carb import omni.isaac.core.utils.stage as stage_utils +import omni.log import omni.physx from omni.isaac.core.simulation_context import SimulationContext as _SimulationContext from omni.isaac.core.utils.viewports import set_camera_view @@ -338,7 +339,7 @@ def set_render_mode(self, mode: RenderMode): """ # check if mode change is possible -- not possible when no GUI is available if not self._has_gui: - carb.log_warn( + omni.log.warn( f"Cannot change render mode when GUI is disabled. Using the default render mode: {self.render_mode}." ) return @@ -616,7 +617,7 @@ def _app_control_on_stop_callback(self, event: carb.events.IEvent): if event.type == int(omni.timeline.TimelineEventType.STOP): # keep running the simulator when configured to not shutdown the app if self._has_gui and sys.exc_info()[0] is None: - carb.log_warn( + omni.log.warn( "Simulation is stopped. The app will keep running with physics disabled." " Press Ctrl+C or close the window to exit the app." ) @@ -760,7 +761,7 @@ def build_simulation_context( yield sim except Exception: - carb.log_error(traceback.format_exc()) + omni.log.error(traceback.format_exc()) raise finally: if not sim.has_gui(): diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/spawners/from_files/from_files.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/spawners/from_files/from_files.py index cab6bf06c9..cbd9932b97 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/spawners/from_files/from_files.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/spawners/from_files/from_files.py @@ -7,10 +7,10 @@ from typing import TYPE_CHECKING -import carb import omni.isaac.core.utils.prims as prim_utils import omni.isaac.core.utils.stage as stage_utils import omni.kit.commands +import omni.log from pxr import Gf, Sdf, Usd from omni.isaac.lab.sim import converters, schemas @@ -226,7 +226,7 @@ def _spawn_from_usd_file( scale=cfg.scale, ) else: - carb.log_warn(f"A prim already exists at prim path: '{prim_path}'.") + omni.log.warn(f"A prim already exists at prim path: '{prim_path}'.") # modify variants if hasattr(cfg, "variants") and cfg.variants is not None: diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/spawners/sensors/sensors.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/spawners/sensors/sensors.py index aa649b7e89..b05f804ce8 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/spawners/sensors/sensors.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/spawners/sensors/sensors.py @@ -7,9 +7,9 @@ from typing import TYPE_CHECKING -import carb import omni.isaac.core.utils.prims as prim_utils import omni.kit.commands +import omni.log from pxr import Sdf, Usd from omni.isaac.lab.sim.utils import clone @@ -104,7 +104,7 @@ def spawn_camera( # TODO: Adjust to handle aperture offsets once supported by omniverse # Internal ticket from rendering team: OM-42611 if cfg.horizontal_aperture_offset > 1e-4 or cfg.vertical_aperture_offset > 1e-4: - carb.log_warn("Camera aperture offsets are not supported by Omniverse. These parameters will be ignored.") + omni.log.warn("Camera aperture offsets are not supported by Omniverse. These parameters will be ignored.") # custom attributes in the config that are not USD Camera parameters non_usd_cfg_param_names = [ diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/utils.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/utils.py index 0828e4887a..526e4244e1 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/utils.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/utils.py @@ -13,9 +13,9 @@ from collections.abc import Callable from typing import TYPE_CHECKING, Any -import carb import omni.isaac.core.utils.stage as stage_utils import omni.kit.commands +import omni.log from omni.isaac.cloner import Cloner from pxr import PhysxSchema, Sdf, Usd, UsdGeom, UsdPhysics, UsdShade @@ -70,7 +70,7 @@ def safe_set_attribute_on_usd_schema(schema_api: Usd.APISchemaBase, name: str, v else: # think: do we ever need to create the attribute if it doesn't exist? # currently, we are not doing this since the schemas are already created with some defaults. - carb.log_error(f"Attribute '{attr_name}' does not exist on prim '{schema_api.GetPath()}'.") + omni.log.error(f"Attribute '{attr_name}' does not exist on prim '{schema_api.GetPath()}'.") raise TypeError(f"Attribute '{attr_name}' does not exist on prim '{schema_api.GetPath()}'.") @@ -189,7 +189,7 @@ def wrapper(prim_path: str | Sdf.Path, *args, **kwargs): count_success += 1 # check if we were successful in applying the function to any prim if count_success == 0: - carb.log_warn( + omni.log.warn( f"Could not perform '{func.__name__}' on any prims under: '{prim_path}'." " This might be because of the following reasons:" "\n\t(1) The desired attribute does not exist on any of the prims." @@ -391,7 +391,7 @@ def bind_physics_material( has_deformable_body = prim.HasAPI(PhysxSchema.PhysxDeformableBodyAPI) has_particle_system = prim.IsA(PhysxSchema.PhysxParticleSystem) if not (has_physics_scene_api or has_collider or has_deformable_body or has_particle_system): - carb.log_verbose( + omni.log.verbose( f"Cannot apply physics material '{material_path}' on prim '{prim_path}'. It is neither a" " PhysX scene, collider, a deformable body, nor a particle system." ) @@ -851,14 +851,14 @@ class TableVariants: for variant_set_name, variant_selection in variants.items(): # Check if the variant set exists on the prim. if not existing_variant_sets.HasVariantSet(variant_set_name): - carb.log_warn(f"Variant set '{variant_set_name}' does not exist on prim '{prim_path}'.") + omni.log.warn(f"Variant set '{variant_set_name}' does not exist on prim '{prim_path}'.") continue variant_set = existing_variant_sets.GetVariantSet(variant_set_name) # Only set the variant selection if it is different from the current selection. if variant_set.GetVariantSelection() != variant_selection: variant_set.SetVariantSelection(variant_selection) - carb.log_info( + omni.log.info( f"Setting variant selection '{variant_selection}' for variant set '{variant_set_name}' on" f" prim '{prim_path}'." ) diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/terrains/terrain_generator.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/terrains/terrain_generator.py index abd411a856..e91b51f117 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/terrains/terrain_generator.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/terrains/terrain_generator.py @@ -8,7 +8,7 @@ import torch import trimesh -import carb +import omni.log from omni.isaac.lab.utils.dict import dict_to_md5_hash from omni.isaac.lab.utils.io import dump_yaml @@ -119,7 +119,7 @@ def __init__(self, cfg: TerrainGeneratorCfg, device: str = "cpu"): # throw a warning if the cache is enabled but the seed is not set if self.cfg.use_cache and self.cfg.seed is None: - carb.log_warn( + omni.log.warn( "Cache is enabled but the seed is not set. The terrain generation will not be reproducible." " Please set the seed in the terrain generator configuration to make the generation reproducible." ) @@ -295,7 +295,7 @@ def _add_sub_terrain( """ # sample flat patches if specified if sub_terrain_cfg.flat_patch_sampling is not None: - carb.log_info(f"Sampling flat patches for sub-terrain at (row, col): ({row}, {col})") + omni.log.info(f"Sampling flat patches for sub-terrain at (row, col): ({row}, {col})") # convert the mesh to warp mesh wp_mesh = convert_to_warp_mesh(mesh.vertices, mesh.faces, device=self.device) # sample flat patches based on each patch configuration for that sub-terrain diff --git a/source/extensions/omni.isaac.lab/test/deps/isaacsim/check_floating_base_made_fixed.py b/source/extensions/omni.isaac.lab/test/deps/isaacsim/check_floating_base_made_fixed.py index d77f037eb3..b2a4471133 100644 --- a/source/extensions/omni.isaac.lab/test/deps/isaacsim/check_floating_base_made_fixed.py +++ b/source/extensions/omni.isaac.lab/test/deps/isaacsim/check_floating_base_made_fixed.py @@ -32,11 +32,11 @@ import torch -import carb import omni.isaac.core.utils.nucleus as nucleus_utils import omni.isaac.core.utils.prims as prim_utils import omni.isaac.core.utils.stage as stage_utils import omni.kit.commands +import omni.log import omni.physx from omni.isaac.core.articulations import ArticulationView from omni.isaac.core.utils.carb import set_carb_setting @@ -50,7 +50,7 @@ "Unable to perform Nucleus login on Omniverse. Assets root path is not set.\n" "\tPlease check: https://docs.omniverse.nvidia.com/app_isaacsim/app_isaacsim/overview.html#omniverse-nucleus" ) - carb.log_error(msg) + omni.log.error(msg) raise RuntimeError(msg) diff --git a/source/extensions/omni.isaac.lab/test/deps/isaacsim/check_legged_robot_clone.py b/source/extensions/omni.isaac.lab/test/deps/isaacsim/check_legged_robot_clone.py index 628872496b..8edc29071d 100644 --- a/source/extensions/omni.isaac.lab/test/deps/isaacsim/check_legged_robot_clone.py +++ b/source/extensions/omni.isaac.lab/test/deps/isaacsim/check_legged_robot_clone.py @@ -43,7 +43,7 @@ import os import torch -import carb +import omni.log try: import omni.isaac.nucleus as nucleus_utils @@ -62,7 +62,7 @@ "Unable to perform Nucleus login on Omniverse. Assets root path is not set.\n" "\tPlease check: https://docs.omniverse.nvidia.com/app_isaacsim/app_isaacsim/overview.html#omniverse-nucleus" ) - carb.log_error(msg) + omni.log.error(msg) raise RuntimeError(msg) diff --git a/source/extensions/omni.isaac.lab/test/deps/isaacsim/check_ref_count.py b/source/extensions/omni.isaac.lab/test/deps/isaacsim/check_ref_count.py index 7d2e91acd7..49bf581f27 100644 --- a/source/extensions/omni.isaac.lab/test/deps/isaacsim/check_ref_count.py +++ b/source/extensions/omni.isaac.lab/test/deps/isaacsim/check_ref_count.py @@ -37,7 +37,7 @@ import gc import torch # noqa: F401 -import carb +import omni.log try: import omni.isaac.nucleus as nucleus_utils @@ -55,7 +55,7 @@ "Unable to perform Nucleus login on Omniverse. Assets root path is not set.\n" "\tPlease check: https://docs.omniverse.nvidia.com/app_isaacsim/app_isaacsim/overview.html#omniverse-nucleus" ) - carb.log_error(msg) + omni.log.error(msg) raise RuntimeError(msg) diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/utils/data_collector/robomimic_data_collector.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/utils/data_collector/robomimic_data_collector.py index 5ef34f3c34..e0bab3b454 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/utils/data_collector/robomimic_data_collector.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/utils/data_collector/robomimic_data_collector.py @@ -15,7 +15,7 @@ import torch from collections.abc import Iterable -import carb +import omni.log class RobomimicDataCollector: @@ -148,10 +148,10 @@ def add(self, key: str, value: np.ndarray | torch.Tensor): """ # check if data should be recorded if self._is_first_interaction: - carb.log_warn("Please call reset before adding new data. Calling reset...") + omni.log.warn("Please call reset before adding new data. Calling reset...") self.reset() if self._is_stop: - carb.log_warn(f"Desired number of demonstrations collected: {self._demo_count} >= {self._num_demos}.") + omni.log.warn(f"Desired number of demonstrations collected: {self._demo_count} >= {self._num_demos}.") return # check datatype if isinstance(value, torch.Tensor): @@ -192,7 +192,7 @@ def flush(self, env_ids: Iterable[int] = (0,)): """ # check that data is being recorded if self._h5_file_stream is None or self._h5_data_group is None: - carb.log_error("No file stream has been opened. Please call reset before flushing data.") + omni.log.error("No file stream has been opened. Please call reset before flushing data.") return # iterate over each environment and add their data diff --git a/source/standalone/environments/state_machine/open_cabinet_sm.py b/source/standalone/environments/state_machine/open_cabinet_sm.py index f1e9b12fab..ad40653fca 100644 --- a/source/standalone/environments/state_machine/open_cabinet_sm.py +++ b/source/standalone/environments/state_machine/open_cabinet_sm.py @@ -40,10 +40,8 @@ import gymnasium as gym import torch -import traceback from collections.abc import Sequence -import carb import warp as wp from omni.isaac.lab.sensors import FrameTransformer @@ -313,13 +311,7 @@ def main(): if __name__ == "__main__": - try: - # run the main execution - main() - except Exception as err: - carb.log_error(err) - carb.log_error(traceback.format_exc()) - raise - finally: - # close sim app - simulation_app.close() + # run the main execution + main() + # close sim app + simulation_app.close() diff --git a/source/standalone/environments/teleoperation/teleop_se3_agent.py b/source/standalone/environments/teleoperation/teleop_se3_agent.py index ef3dc49e09..6361bd5f45 100644 --- a/source/standalone/environments/teleoperation/teleop_se3_agent.py +++ b/source/standalone/environments/teleoperation/teleop_se3_agent.py @@ -35,7 +35,7 @@ import gymnasium as gym import torch -import carb +import omni.log from omni.isaac.lab.devices import Se3Gamepad, Se3Keyboard, Se3SpaceMouse from omni.isaac.lab.managers import TerminationTermCfg as DoneTerm @@ -77,7 +77,7 @@ def main(): env = gym.make(args_cli.task, cfg=env_cfg) # check environment name (for reach , we don't allow the gripper) if "Reach" in args_cli.task: - carb.log_warn( + omni.log.warn( f"The environment '{args_cli.task}' does not support gripper control. The device command will be ignored." ) From 517c4c14f633ad9507f4d5bf20325f0600ccb273 Mon Sep 17 00:00:00 2001 From: Sergei Sergienko Date: Mon, 14 Oct 2024 18:34:34 +0300 Subject: [PATCH 019/111] Excludes cache files from vscode explorer (#1131) Small quality of life change that excludes cache files from VSCode File Explorer when attached to sim container. --- .vscode/tools/settings.template.json | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/.vscode/tools/settings.template.json b/.vscode/tools/settings.template.json index 7d696c44b8..41e7130cda 100644 --- a/.vscode/tools/settings.template.json +++ b/.vscode/tools/settings.template.json @@ -1,4 +1,9 @@ { + "files.exclude": { + "**/.mypy_cache": true, + "**/__pycache__": true, + "**/*.egg-info": true + }, "files.associations": { "*.tpp": "cpp", "*.kit": "toml", From db04a2e4914e07620d0e1583891cdbc45a3a603e Mon Sep 17 00:00:00 2001 From: David Hoeller Date: Tue, 15 Oct 2024 10:15:53 +0200 Subject: [PATCH 020/111] Adds doc building step on push (#1234) # Description * Adds doc building on push so it can be checked that the docs build correctly on any branch * Adds `omni.log` to the sphinx import mock list ## Type of change - Bug fix (non-breaking change which fixes an issue) - New feature (non-breaking change which adds functionality) ## Checklist - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [ ] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [ ] I have added tests that prove my fix is effective or that my feature works - [ ] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [ ] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --- .github/workflows/docs.yaml | 61 ++++++++++++++++++++----------------- docs/conf.py | 1 + 2 files changed, 34 insertions(+), 28 deletions(-) diff --git a/.github/workflows/docs.yaml b/.github/workflows/docs.yaml index 2465869832..4c6a89143b 100644 --- a/.github/workflows/docs.yaml +++ b/.github/workflows/docs.yaml @@ -3,45 +3,50 @@ name: Build & deploy docs on: [push] jobs: + build-docs: + name: Build Docs + runs-on: ubuntu-latest + + steps: + - name: Checkout code + uses: actions/checkout@v2 + + - name: Setup python + uses: actions/setup-python@v2 + with: + python-version: "3.10" + architecture: x64 + + - name: Install dev requirements + working-directory: ./docs + run: pip install -r requirements.txt + + - name: Generate docs + working-directory: ./docs + run: make html + check-secrets: name: Check secrets runs-on: ubuntu-latest outputs: - trigger-build: ${{ steps.trigger-build.outputs.defined }} + trigger-deploy: ${{ steps.trigger-deploy.outputs.defined }} steps: - - id: trigger-build + - id: trigger-deploy env: REPO_NAME: ${{ secrets.REPO_NAME }} BRANCH_REF: ${{ secrets.BRANCH_REF }} if: "${{ github.repository == env.REPO_NAME && github.ref == env.BRANCH_REF }}" run: echo "defined=true" >> "$GITHUB_OUTPUT" - build-docs: - name: Build and deploy documentation + deploy-docs: + name: Deploy Docs runs-on: ubuntu-latest - needs: [check-secrets] - if: needs.check-secrets.outputs.trigger-build == 'true' + needs: [check-secrets, build-docs] + if: needs.check-secrets.outputs.trigger-deploy == 'true' steps: - - name: Checkout code - uses: actions/checkout@v2 - - - name: Setup python - uses: actions/setup-python@v2 - with: - python-version: "3.10" - architecture: x64 - - - name: Install dev requirements - working-directory: ./docs - run: pip install -r requirements.txt - - - name: Generate docs - working-directory: ./docs - run: make html - - - name: Deploy to gh-pages - uses: peaceiris/actions-gh-pages@v3 - with: - github_token: ${{ secrets.GITHUB_TOKEN }} - publish_dir: ./docs/_build/html + - name: Deploy to gh-pages + uses: peaceiris/actions-gh-pages@v3 + with: + github_token: ${{ secrets.GITHUB_TOKEN }} + publish_dir: ./docs/_build/html diff --git a/docs/conf.py b/docs/conf.py index ca1fa9a075..a30e673280 100644 --- a/docs/conf.py +++ b/docs/conf.py @@ -127,6 +127,7 @@ "warp", "pxr", "omni.kit", + "omni.log", "omni.usd", "omni.client", "omni.physx", From 665b3358cb4b27d7bf547b30a8875d08ffccf99a Mon Sep 17 00:00:00 2001 From: lgulich <22480644+lgulich@users.noreply.github.com> Date: Tue, 15 Oct 2024 01:34:23 -0700 Subject: [PATCH 021/111] Adds better error message for invalid actuator parameters (#1235) # Description Adds better error message for invalid values. - New feature (non-breaking change which adds functionality) ## Checklist - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [ ] I have made corresponding changes to the documentation - [ ] My changes generate no new warnings - [ ] I have added tests that prove my fix is effective or that my feature works - [ ] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [ ] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --- .../omni/isaac/lab/actuators/actuator_base.py | 10 ++++++++-- 1 file changed, 8 insertions(+), 2 deletions(-) diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/actuators/actuator_base.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/actuators/actuator_base.py index 4d53fc048b..67926fce31 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/actuators/actuator_base.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/actuators/actuator_base.py @@ -221,7 +221,10 @@ def _parse_joint_parameter( # note: need to specify type to be safe (e.g. values are ints, but we want floats) param[:, indices] = torch.tensor(values, dtype=torch.float, device=self._device) else: - raise TypeError(f"Invalid type for parameter value: {type(cfg_value)}. Expected float or dict.") + raise TypeError( + f"Invalid type for parameter value: {type(cfg_value)} for " + + f"actuator on joints {self.joint_names}. Expected float or dict." + ) elif default_value is not None: if isinstance(default_value, (float, int)): # if float, then use the same value for all joints @@ -230,7 +233,10 @@ def _parse_joint_parameter( # if tensor, then use the same tensor for all joints param[:] = default_value.float() else: - raise TypeError(f"Invalid type for default value: {type(default_value)}. Expected float or Tensor.") + raise TypeError( + f"Invalid type for default value: {type(default_value)} for " + + f"actuator on joints {self.joint_names}. Expected float or Tensor." + ) else: raise ValueError("The parameter value is None and no default value is provided.") From 30c21674a21792463566c61877f3f1e40912ea6d Mon Sep 17 00:00:00 2001 From: David Hoeller Date: Tue, 15 Oct 2024 13:55:09 +0200 Subject: [PATCH 022/111] Fixes GitHub action for docs deployment (#1239) # Description The docs were not deployed properly. ## Type of change - Bug fix (non-breaking change which fixes an issue) ## Checklist - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [ ] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [ ] I have added tests that prove my fix is effective or that my feature works - [ ] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [x] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --- .github/workflows/docs.yaml | 12 ++++++++++++ 1 file changed, 12 insertions(+) diff --git a/.github/workflows/docs.yaml b/.github/workflows/docs.yaml index 4c6a89143b..b0ceb6bff7 100644 --- a/.github/workflows/docs.yaml +++ b/.github/workflows/docs.yaml @@ -25,6 +25,12 @@ jobs: working-directory: ./docs run: make html + - name: Upload docs artifact + uses: actions/upload-artifact@v4 + with: + name: docs-html + path: ./docs/_build/html + check-secrets: name: Check secrets runs-on: ubuntu-latest @@ -45,6 +51,12 @@ jobs: if: needs.check-secrets.outputs.trigger-deploy == 'true' steps: + - name: Download docs artifact + uses: actions/download-artifact@v4 + with: + name: docs-html + path: ./docs/_build/html + - name: Deploy to gh-pages uses: peaceiris/actions-gh-pages@v3 with: From e3ea4c5cdd499c3d8a00d06223c40fb06846366a Mon Sep 17 00:00:00 2001 From: lgulich <22480644+lgulich@users.noreply.github.com> Date: Tue, 15 Oct 2024 07:36:51 -0700 Subject: [PATCH 023/111] Fixes typos in render interval warning messages (#1237) # Description Fixes typos in render interval warning messages ## Type of change - Bug fix (non-breaking change which fixes an issue) ## Checklist - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [ ] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [ ] I have added tests that prove my fix is effective or that my feature works - [ ] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [x] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --- .../omni.isaac.lab/omni/isaac/lab/envs/direct_marl_env.py | 2 +- .../omni.isaac.lab/omni/isaac/lab/envs/direct_rl_env.py | 2 +- .../omni.isaac.lab/omni/isaac/lab/envs/manager_based_env.py | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_marl_env.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_marl_env.py index 2fad4a0243..f58a80dd47 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_marl_env.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_marl_env.py @@ -102,7 +102,7 @@ def __init__(self, cfg: DirectMARLEnvCfg, render_mode: str | None = None, **kwar if self.cfg.sim.render_interval < self.cfg.decimation: msg = ( f"The render interval ({self.cfg.sim.render_interval}) is smaller than the decimation " - f"({self.cfg.decimation}). Multiple multiple render calls will happen for each environment step." + f"({self.cfg.decimation}). Multiple render calls will happen for each environment step." "If this is not intended, set the render interval to be equal to the decimation." ) omni.log.warn(msg) diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_rl_env.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_rl_env.py index 8564b4a916..5663977fda 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_rl_env.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_rl_env.py @@ -107,7 +107,7 @@ def __init__(self, cfg: DirectRLEnvCfg, render_mode: str | None = None, **kwargs if self.cfg.sim.render_interval < self.cfg.decimation: msg = ( f"The render interval ({self.cfg.sim.render_interval}) is smaller than the decimation " - f"({self.cfg.decimation}). Multiple multiple render calls will happen for each environment step." + f"({self.cfg.decimation}). Multiple render calls will happen for each environment step." "If this is not intended, set the render interval to be equal to the decimation." ) omni.log.warn(msg) diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/manager_based_env.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/manager_based_env.py index 2e4ac663dc..9b2991a521 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/manager_based_env.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/manager_based_env.py @@ -103,7 +103,7 @@ def __init__(self, cfg: ManagerBasedEnvCfg): if self.cfg.sim.render_interval < self.cfg.decimation: msg = ( f"The render interval ({self.cfg.sim.render_interval}) is smaller than the decimation " - f"({self.cfg.decimation}). Multiple multiple render calls will happen for each environment step. " + f"({self.cfg.decimation}). Multiple render calls will happen for each environment step. " "If this is not intended, set the render interval to be equal to the decimation." ) omni.log.warn(msg) From 15a2c508cc39f7c1dcef15e4948f86896e0d58bb Mon Sep 17 00:00:00 2001 From: Pascal Roth <57946385+pascal-roth@users.noreply.github.com> Date: Tue, 15 Oct 2024 16:56:57 +0200 Subject: [PATCH 024/111] Updates tested docker and apptainer versions for cluster deployment (#1230) # Description The cluster workflow succeeded with a newer version of apptainer and docker. This PR removes the error when not the specific old versions are used and instead prints a warning once non-tested versions are deployed. ## Type of change - Bug fix (non-breaking change which fixes an issue) - This change requires a documentation update ## Checklist - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [x] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [ ] I have added tests that prove my fix is effective or that my feature works - [ ] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [x] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --- docker/cluster/cluster_interface.sh | 29 ++++++++++++++++++++++------- docs/source/deployment/cluster.rst | 13 +++++-------- 2 files changed, 27 insertions(+), 15 deletions(-) diff --git a/docker/cluster/cluster_interface.sh b/docker/cluster/cluster_interface.sh index fd325e4ca4..96bdc49b3d 100755 --- a/docker/cluster/cluster_interface.sh +++ b/docker/cluster/cluster_interface.sh @@ -16,8 +16,18 @@ SCRIPT_DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )" #== # Functions #== +# Function to display warnings in red +display_warning() { + echo -e "\033[31mWARNING: $1\033[0m" +} + +# Helper function to compare version numbers +version_gte() { + # Returns 0 if the first version is greater than or equal to the second, otherwise 1 + [ "$(printf '%s\n' "$1" "$2" | sort -V | head -n 1)" == "$2" ] +} + # Function to check docker versions -# If docker version is more than 25, the script errors out. check_docker_version() { # check if docker is installed if ! command -v docker &> /dev/null; then @@ -28,12 +38,17 @@ check_docker_version() { docker_version=$(docker --version | awk '{ print $3 }') apptainer_version=$(apptainer --version | awk '{ print $3 }') - # Check if version is above 25.xx - if [ "$(echo "${docker_version}" | cut -d '.' -f 1)" -ge 25 ]; then - echo "[ERROR]: Docker version ${docker_version} is not compatible with Apptainer version ${apptainer_version}. Exiting." - exit 1 + # Check if Docker version is exactly 24.0.7 or Apptainer version is exactly 1.2.5 + if [ "$docker_version" = "24.0.7" ] && [ "$apptainer_version" = "1.2.5" ]; then + echo "[INFO]: Docker version ${docker_version} and Apptainer version ${apptainer_version} are tested and compatible." + + # Check if Docker version is >= 27.0.0 and Apptainer version is >= 1.3.4 + elif version_gte "$docker_version" "27.0.0" && version_gte "$apptainer_version" "1.3.4"; then + echo "[INFO]: Docker version ${docker_version} and Apptainer version ${apptainer_version} are tested and compatible." + + # Else, display a warning for non-tested versions else - echo "[INFO]: Building singularity with docker version: ${docker_version} and Apptainer version: ${apptainer_version}." + display_warning "Docker version ${docker_version} and Apptainer version ${apptainer_version} are non-tested versions. There could be issues, please try to update them. More info: https://isaac-sim.github.io/IsaacLab/source/deployment/cluster.html" fi } @@ -139,7 +154,7 @@ case $command in fi # Check if Docker image exists check_image_exists isaac-lab-$profile:latest - # Check if Docker version is greater than 25 + # Check docker and apptainer version check_docker_version # source env file to get cluster login and path information source $SCRIPT_DIR/.env.cluster diff --git a/docs/source/deployment/cluster.rst b/docs/source/deployment/cluster.rst index beae7ef438..467fda90f4 100644 --- a/docs/source/deployment/cluster.rst +++ b/docs/source/deployment/cluster.rst @@ -45,15 +45,13 @@ development machine and the cluster. Such a connection will simplify the file tr the user cluster password from being requested multiple times. .. attention:: - The workflow has been tested with ``apptainer version 1.2.5-1.el7`` and ``docker version 24.0.7``. + The workflow has been tested with: - - ``apptainer``: - There have been reported binding issues with previous versions (such as ``apptainer version 1.1.3-1.el7``). Please - ensure that you are using the latest version. - - ``Docker``: - The latest versions (``25.x``) cannot be used as they are not compatible yet with apptainer/ singularity. + - ``apptainer version 1.2.5-1.el7`` and ``docker version 24.0.7`` + - ``apptainer version 1.3.4`` and ``docker version 27.3.1`` + + In the case of issues, please try to switch to those versions. - We are waiting for an update from the apptainer team. To track this issue, please check the `forum post`_. Configuring the cluster parameters ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ @@ -211,4 +209,3 @@ The above will, in addition, also render videos of the training progress and sto .. _apptainer: https://apptainer.org/ .. _documentation: https://www.apptainer.org/docs/admin/main/installation.html#install-ubuntu-packages .. _SLURM documentation: https://www.slurm.schedmd.com/sbatch.html -.. _forum post: https://forums.docker.com/t/trouble-after-upgrade-to-docker-ce-25-0-1-on-debian-12/139613 From a4118d7f9be827f8755ee71ea922928bb6c4a314 Mon Sep 17 00:00:00 2001 From: Toni-SM Date: Wed, 16 Oct 2024 21:59:05 -0400 Subject: [PATCH 025/111] Support other gymnasium spaces in Direct workflow (#1117) # Description This PR add supports for different Gymnasium spaces (`Box`, `Discrete`, `MultiDiscrete`, `Tuple` and `Dict`) to define observation, action and state spaces in the direct workflow. See https://github.com/isaac-sim/IsaacLab/issues/864#issuecomment-2351819930 ## Type of change - New feature (non-breaking change which adds functionality) - This change requires a documentation update ## Checklist - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [x] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [x] I have added tests that prove my fix is effective or that my feature works - [x] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [x] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --- docs/source/features/hydra.rst | 2 +- .../migration/migrating_from_isaacgymenvs.rst | 18 +-- .../migrating_from_omniisaacgymenvs.rst | 18 +-- .../snippets/tutorial_modify_direct_rl_env.py | 4 +- .../03_envs/create_direct_rl_env.rst | 6 +- .../omni.isaac.lab/config/extension.toml | 2 +- .../omni.isaac.lab/docs/CHANGELOG.rst | 19 +++ .../omni/isaac/lab/envs/__init__.py | 2 +- .../omni/isaac/lab/envs/common.py | 4 + .../omni/isaac/lab/envs/direct_marl_env.py | 61 ++++++--- .../isaac/lab/envs/direct_marl_env_cfg.py | 97 +++++++++++++- .../omni/isaac/lab/envs/direct_rl_env.py | 38 ++++-- .../omni/isaac/lab/envs/direct_rl_env_cfg.py | 97 +++++++++++++- .../omni/isaac/lab/envs/utils/__init__.py | 6 + .../lab/envs/{utils.py => utils/marl.py} | 73 +++++++---- .../omni/isaac/lab/envs/utils/spaces.py | 92 +++++++++++++ .../test/envs/test_spaces_utils.py | 122 ++++++++++++++++++ .../config/extension.toml | 2 +- .../omni.isaac.lab_tasks/docs/CHANGELOG.rst | 13 ++ .../allegro_hand/allegro_hand_env_cfg.py | 6 +- .../isaac/lab_tasks/direct/ant/ant_env.py | 6 +- .../lab_tasks/direct/anymal_c/anymal_c_env.py | 15 ++- .../cart_double_pendulum_env.py | 6 +- .../direct/cartpole/cartpole_camera_env.py | 45 +------ .../lab_tasks/direct/cartpole/cartpole_env.py | 6 +- .../franka_cabinet/franka_cabinet_env.py | 6 +- .../lab_tasks/direct/humanoid/humanoid_env.py | 6 +- .../direct/quadcopter/quadcopter_env.py | 9 +- .../direct/shadow_hand/shadow_hand_env_cfg.py | 12 +- .../shadow_hand/shadow_hand_vision_env.py | 4 +- .../shadow_hand_over_env_cfg.py | 6 +- .../utils/wrappers/rsl_rl/vecenv_wrapper.py | 8 +- .../test/test_environments.py | 17 +-- .../test/test_multi_agent_environments.py | 15 +-- 34 files changed, 645 insertions(+), 198 deletions(-) create mode 100644 source/extensions/omni.isaac.lab/omni/isaac/lab/envs/utils/__init__.py rename source/extensions/omni.isaac.lab/omni/isaac/lab/envs/{utils.py => utils/marl.py} (76%) create mode 100644 source/extensions/omni.isaac.lab/omni/isaac/lab/envs/utils/spaces.py create mode 100644 source/extensions/omni.isaac.lab/test/envs/test_spaces_utils.py diff --git a/docs/source/features/hydra.rst b/docs/source/features/hydra.rst index 2fa5d2d706..89673dbe35 100644 --- a/docs/source/features/hydra.rst +++ b/docs/source/features/hydra.rst @@ -115,7 +115,7 @@ For example, for the configuration of the Cartpole camera depth environment: :emphasize-lines: 16 If the user were to modify the width of the camera, i.e. ``env.tiled_camera.width=128``, then the parameter -``env.num_observations=10240`` (1*80*128) must be updated and given as input as well. +``env.observation_space=[80,128,1]`` must be updated and given as input as well. Similarly, the ``__post_init__`` method is not updated with the command line inputs. In the ``LocomotionVelocityRoughEnvCfg``, for example, the post init update is as follows: diff --git a/docs/source/migration/migrating_from_isaacgymenvs.rst b/docs/source/migration/migrating_from_isaacgymenvs.rst index c903d83c3d..2073854d32 100644 --- a/docs/source/migration/migrating_from_isaacgymenvs.rst +++ b/docs/source/migration/migrating_from_isaacgymenvs.rst @@ -45,9 +45,9 @@ Below is an example skeleton of a task config class: # env decimation = 2 episode_length_s = 5.0 - num_actions = 1 - num_observations = 4 - num_states = 0 + action_space = 1 + observation_space = 4 + state_space = 0 # task-specific parameters ... @@ -135,9 +135,9 @@ The following parameters must be set for each environment config: decimation = 2 episode_length_s = 5.0 - num_actions = 1 - num_observations = 4 - num_states = 0 + action_space = 1 + observation_space = 4 + state_space = 0 Note that the maximum episode length parameter (now ``episode_length_s``) is in seconds instead of steps as it was in IsaacGymEnvs. To convert between step count to seconds, use the equation: @@ -569,9 +569,9 @@ Task Config | | decimation = 2 | | asset: | episode_length_s = 5.0 | | assetRoot: "../../assets" | action_scale = 100.0 # [N] | -| assetFileName: "urdf/cartpole.urdf" | num_actions = 1 | -| | num_observations = 4 | -| enableCameraSensors: False | num_states = 0 | +| assetFileName: "urdf/cartpole.urdf" | action_space = 1 | +| | observation_space = 4 | +| enableCameraSensors: False | state_space = 0 | | | # reset | | sim: | max_cart_pos = 3.0 | | dt: 0.0166 # 1/60 s | initial_pole_angle_range = [-0.25, 0.25] | diff --git a/docs/source/migration/migrating_from_omniisaacgymenvs.rst b/docs/source/migration/migrating_from_omniisaacgymenvs.rst index 50f9d5b9d6..cbda1e8d45 100644 --- a/docs/source/migration/migrating_from_omniisaacgymenvs.rst +++ b/docs/source/migration/migrating_from_omniisaacgymenvs.rst @@ -46,9 +46,9 @@ Below is an example skeleton of a task config class: # env decimation = 2 episode_length_s = 5.0 - num_actions = 1 - num_observations = 4 - num_states = 0 + action_space = 1 + observation_space = 4 + state_space = 0 # task-specific parameters ... @@ -158,9 +158,9 @@ The following parameters must be set for each environment config: decimation = 2 episode_length_s = 5.0 - num_actions = 1 - num_observations = 4 - num_states = 0 + action_space = 1 + observation_space = 4 + state_space = 0 RL Config Setup @@ -501,9 +501,9 @@ Task config in Isaac Lab can be split into the main task configuration class and | clipObservations: 5.0 | decimation = 2 | | clipActions: 1.0 | episode_length_s = 5.0 | | controlFrequencyInv: 2 # 60 Hz | action_scale = 100.0 # [N] | -| | num_actions = 1 | -| sim: | num_observations = 4 | -| | num_states = 0 | +| | action_space = 1 | +| sim: | observation_space = 4 | +| | state_space = 0 | | dt: 0.0083 # 1/120 s | # reset | | use_gpu_pipeline: ${eq:${...pipeline},"gpu"} | max_cart_pos = 3.0 | | gravity: [0.0, 0.0, -9.81] | initial_pole_angle_range = [-0.25, 0.25] | diff --git a/docs/source/refs/snippets/tutorial_modify_direct_rl_env.py b/docs/source/refs/snippets/tutorial_modify_direct_rl_env.py index 8073886840..215ef3bd4f 100644 --- a/docs/source/refs/snippets/tutorial_modify_direct_rl_env.py +++ b/docs/source/refs/snippets/tutorial_modify_direct_rl_env.py @@ -28,8 +28,8 @@ # [end-h1_env-import] # [start-h1_env-spaces] -num_actions = 19 -num_observations = 69 +action_space = 19 +observation_space = 69 # [end-h1_env-spaces] # [start-h1_env-robot] diff --git a/docs/source/tutorials/03_envs/create_direct_rl_env.rst b/docs/source/tutorials/03_envs/create_direct_rl_env.rst index ab5136106a..a4b945be9d 100644 --- a/docs/source/tutorials/03_envs/create_direct_rl_env.rst +++ b/docs/source/tutorials/03_envs/create_direct_rl_env.rst @@ -48,9 +48,9 @@ config should define the number of actions and observations for the environment. @configclass class CartpoleEnvCfg(DirectRLEnvCfg): ... - num_actions = 1 - num_observations = 4 - num_states = 0 + action_space = 1 + observation_space = 4 + state_space = 0 The config class can also be used to define task-specific attributes, such as scaling for reward terms and thresholds for reset conditions. diff --git a/source/extensions/omni.isaac.lab/config/extension.toml b/source/extensions/omni.isaac.lab/config/extension.toml index 517ac00610..a633e64fb8 100644 --- a/source/extensions/omni.isaac.lab/config/extension.toml +++ b/source/extensions/omni.isaac.lab/config/extension.toml @@ -1,7 +1,7 @@ [package] # Note: Semantic Versioning is used: https://semver.org/ -version = "0.25.1" +version = "0.25.2" # Description title = "Isaac Lab framework for Robot Learning" diff --git a/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst b/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst index e78abdb068..12e4b5b45a 100644 --- a/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst +++ b/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst @@ -1,6 +1,25 @@ Changelog --------- +0.25.2 (2024-10-16) +~~~~~~~~~~~~~~~~~~~~ + +Added +^^^^^ + +* Added support for different Gymnasium spaces (``Box``, ``Discrete``, ``MultiDiscrete``, ``Tuple`` and ``Dict``) + to define observation, action and state spaces in the direct workflow. +* Added :meth:`sample_space` to environment utils to sample supported spaces where data containers are torch tensors. + +Changed +^^^^^^^ + +* Mark the :attr:`num_observations`, :attr:`num_actions` and :attr:`num_states` in :class:`DirectRLEnvCfg` as deprecated + in favor of :attr:`observation_space`, :attr:`action_space` and :attr:`state_space` respectively. +* Mark the :attr:`num_observations`, :attr:`num_actions` and :attr:`num_states` in :class:`DirectMARLEnvCfg` as deprecated + in favor of :attr:`observation_spaces`, :attr:`action_spaces` and :attr:`state_space` respectively. + + 0.25.1 (2024-10-10) ~~~~~~~~~~~~~~~~~~~ diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/__init__.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/__init__.py index 97701e50cc..667c0b5049 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/__init__.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/__init__.py @@ -52,4 +52,4 @@ from .manager_based_env_cfg import ManagerBasedEnvCfg from .manager_based_rl_env import ManagerBasedRLEnv from .manager_based_rl_env_cfg import ManagerBasedRLEnvCfg -from .utils import multi_agent_to_single_agent, multi_agent_with_one_agent +from .utils.marl import multi_agent_to_single_agent, multi_agent_with_one_agent diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/common.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/common.py index d0c99f8ad8..7d6b02d309 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/common.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/common.py @@ -5,6 +5,7 @@ from __future__ import annotations +import gymnasium as gym import torch from typing import Dict, Literal, TypeVar @@ -62,6 +63,9 @@ class ViewerCfg: # Types. ## +SpaceType = TypeVar("SpaceType", gym.spaces.Space, int, set, tuple, list, dict) +"""A sentinel object to indicate a valid space type to specify states, observations and actions.""" + VecEnvObs = Dict[str, torch.Tensor | Dict[str, torch.Tensor]] """Observation returned by the environment. diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_marl_env.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_marl_env.py index f58a80dd47..5bcedb0591 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_marl_env.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_marl_env.py @@ -14,6 +14,7 @@ import weakref from abc import abstractmethod from collections.abc import Sequence +from dataclasses import MISSING from typing import Any, ClassVar import omni.isaac.core.utils.torch as torch_utils @@ -30,6 +31,7 @@ from .common import ActionType, AgentID, EnvStepReturn, ObsType, StateType from .direct_marl_env_cfg import DirectMARLEnvCfg from .ui import ViewportCameraController +from .utils.spaces import sample_space, spec_to_gym_space class DirectMARLEnv: @@ -164,10 +166,6 @@ def __init__(self, cfg: DirectMARLEnvCfg, render_mode: str | None = None, **kwar # -- init buffers self.episode_length_buf = torch.zeros(self.num_envs, device=self.device, dtype=torch.long) self.reset_buf = torch.zeros(self.num_envs, dtype=torch.bool, device=self.sim.device) - self.actions = { - agent: torch.zeros(self.num_envs, self.cfg.num_actions[agent], device=self.sim.device) - for agent in self.cfg.possible_agents - } # setup the observation, state and action spaces self._configure_env_spaces() @@ -406,16 +404,19 @@ def state(self) -> StateType | None: """Returns the state for the environment. The state-space is used for centralized training or asymmetric actor-critic architectures. It is configured - using the :attr:`DirectMARLEnvCfg.num_states` parameter. + using the :attr:`DirectMARLEnvCfg.state_space` parameter. Returns: - The states for the environment, or None if :attr:`DirectMARLEnvCfg.num_states` parameter is zero. + The states for the environment, or None if :attr:`DirectMARLEnvCfg.state_space` parameter is zero. """ - if not self.cfg.num_states: + if not self.cfg.state_space: return None # concatenate and return the observations as state - if self.cfg.num_states < 0: - self.state_buf = torch.cat([self.obs_dict[agent] for agent in self.cfg.possible_agents], dim=-1) + # FIXME: This implementation assumes the spaces are fundamental ones. Fix it to support composite spaces + if isinstance(self.cfg.state_space, int) and self.cfg.state_space < 0: + self.state_buf = torch.cat( + [self.obs_dict[agent].reshape(self.num_envs, -1) for agent in self.cfg.possible_agents], dim=-1 + ) # compute and return custom environment state else: self.state_buf = self._get_states() @@ -568,25 +569,45 @@ def _configure_env_spaces(self): self.agents = self.cfg.possible_agents self.possible_agents = self.cfg.possible_agents + # show deprecation message and overwrite configuration + if self.cfg.num_actions is not None: + omni.log.warn("DirectMARLEnvCfg.num_actions is deprecated. Use DirectMARLEnvCfg.action_spaces instead.") + if isinstance(self.cfg.action_spaces, type(MISSING)): + self.cfg.action_spaces = self.cfg.num_actions + if self.cfg.num_observations is not None: + omni.log.warn( + "DirectMARLEnvCfg.num_observations is deprecated. Use DirectMARLEnvCfg.observation_spaces instead." + ) + if isinstance(self.cfg.observation_spaces, type(MISSING)): + self.cfg.observation_spaces = self.cfg.num_observations + if self.cfg.num_states is not None: + omni.log.warn("DirectMARLEnvCfg.num_states is deprecated. Use DirectMARLEnvCfg.state_space instead.") + if isinstance(self.cfg.state_space, type(MISSING)): + self.cfg.state_space = self.cfg.num_states + # set up observation and action spaces self.observation_spaces = { - agent: gym.spaces.Box(low=-np.inf, high=np.inf, shape=(self.cfg.num_observations[agent],)) - for agent in self.cfg.possible_agents + agent: spec_to_gym_space(self.cfg.observation_spaces[agent]) for agent in self.cfg.possible_agents } self.action_spaces = { - agent: gym.spaces.Box(low=-np.inf, high=np.inf, shape=(self.cfg.num_actions[agent],)) - for agent in self.cfg.possible_agents + agent: spec_to_gym_space(self.cfg.action_spaces[agent]) for agent in self.cfg.possible_agents } # set up state space - if not self.cfg.num_states: + if not self.cfg.state_space: self.state_space = None - if self.cfg.num_states < 0: - self.state_space = gym.spaces.Box( - low=-np.inf, high=np.inf, shape=(sum(self.cfg.num_observations.values()),) + if isinstance(self.cfg.state_space, int) and self.cfg.state_space < 0: + self.state_space = gym.spaces.flatten_space( + gym.spaces.Tuple([self.observation_spaces[agent] for agent in self.cfg.possible_agents]) ) else: - self.state_space = gym.spaces.Box(low=-np.inf, high=np.inf, shape=(self.cfg.num_states,)) + self.state_space = spec_to_gym_space(self.cfg.state_space) + + # instantiate actions (needed for tasks for which the observations computation is dependent on the actions) + self.actions = { + agent: sample_space(self.action_spaces[agent], self.sim.device, batch_size=self.num_envs, fill_value=0) + for agent in self.cfg.possible_agents + } def _reset_idx(self, env_ids: Sequence[int]): """Reset environments based on specified indices. @@ -664,8 +685,8 @@ def _get_observations(self) -> dict[AgentID, ObsType]: def _get_states(self) -> StateType: """Compute and return the states for the environment. - This method is only called (and therefore has to be implemented) when the :attr:`DirectMARLEnvCfg.num_states` - parameter is greater than zero. + This method is only called (and therefore has to be implemented) when the :attr:`DirectMARLEnvCfg.state_space` + parameter is not a number less than or equal to zero. Returns: The states for the environment. diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_marl_env_cfg.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_marl_env_cfg.py index 3dcf364f5c..40ecb64297 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_marl_env_cfg.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_marl_env_cfg.py @@ -10,7 +10,7 @@ from omni.isaac.lab.utils import configclass from omni.isaac.lab.utils.noise import NoiseModelCfg -from .common import AgentID, ViewerCfg +from .common import AgentID, SpaceType, ViewerCfg from .ui import BaseEnvWindow @@ -104,11 +104,39 @@ class DirectMARLEnvCfg: Please refer to the :class:`omni.isaac.lab.managers.EventManager` class for more details. """ - num_observations: dict[AgentID, int] = MISSING - """The dimension of the observation space from each agent.""" + observation_spaces: dict[AgentID, SpaceType] = MISSING + """Observation space definition for each agent. + + The space can be defined either using Gymnasium :py:mod:`~gymnasium.spaces` (when a more detailed + specification of the space is desired) or basic Python data types (for simplicity). + + .. list-table:: + :header-rows: 1 + + * - Gymnasium space + - Python data type + * - :class:`~gymnasium.spaces.Box` + - Integer or list of integers (e.g.: ``7``, ``[64, 64, 3]``) + * - :class:`~gymnasium.spaces.Discrete` + - Single-element set (e.g.: ``{2}``) + * - :class:`~gymnasium.spaces.MultiDiscrete` + - List of single-element sets (e.g.: ``[{2}, {5}]``) + * - :class:`~gymnasium.spaces.Dict` + - Dictionary (e.g.: ``{"joints": 7, "rgb": [64, 64, 3], "gripper": {2}}``) + * - :class:`~gymnasium.spaces.Tuple` + - Tuple (e.g.: ``(7, [64, 64, 3], {2})``) + """ - num_states: int = MISSING - """The dimension of the state space from each environment instance. + num_observations: dict[AgentID, int] | None = None + """The dimension of the observation space for each agent. + + .. warning:: + + This attribute is deprecated. Use :attr:`~omni.isaac.lab.envs.DirectMARLEnvCfg.observation_spaces` instead. + """ + + state_space: SpaceType = MISSING + """State space definition. The following values are supported: @@ -116,6 +144,33 @@ class DirectMARLEnvCfg: * 0: No state-space will be constructed (`state_space` is None). This is useful to save computational resources when the algorithm to be trained does not need it. * greater than 0: Custom state-space dimension to be provided by the task implementation. + + The space can be defined either using Gymnasium :py:mod:`~gymnasium.spaces` (when a more detailed + specification of the space is desired) or basic Python data types (for simplicity). + + .. list-table:: + :header-rows: 1 + + * - Gymnasium space + - Python data type + * - :class:`~gymnasium.spaces.Box` + - Integer or list of integers (e.g.: ``7``, ``[64, 64, 3]``) + * - :class:`~gymnasium.spaces.Discrete` + - Single-element set (e.g.: ``{2}``) + * - :class:`~gymnasium.spaces.MultiDiscrete` + - List of single-element sets (e.g.: ``[{2}, {5}]``) + * - :class:`~gymnasium.spaces.Dict` + - Dictionary (e.g.: ``{"joints": 7, "rgb": [64, 64, 3], "gripper": {2}}``) + * - :class:`~gymnasium.spaces.Tuple` + - Tuple (e.g.: ``(7, [64, 64, 3], {2})``) + """ + + num_states: int | None = None + """The dimension of the state space from each environment instance. + + .. warning:: + + This attribute is deprecated. Use :attr:`~omni.isaac.lab.envs.DirectMARLEnvCfg.state_space` instead. """ observation_noise_model: dict[AgentID, NoiseModelCfg | None] | None = None @@ -124,8 +179,36 @@ class DirectMARLEnvCfg: Please refer to the :class:`omni.isaac.lab.utils.noise.NoiseModel` class for more details. """ - num_actions: dict[AgentID, int] = MISSING - """The dimension of the action space for each agent.""" + action_spaces: dict[AgentID, SpaceType] = MISSING + """Action space definition for each agent. + + The space can be defined either using Gymnasium :py:mod:`~gymnasium.spaces` (when a more detailed + specification of the space is desired) or basic Python data types (for simplicity). + + .. list-table:: + :header-rows: 1 + + * - Gymnasium space + - Python data type + * - :class:`~gymnasium.spaces.Box` + - Integer or list of integers (e.g.: ``7``, ``[64, 64, 3]``) + * - :class:`~gymnasium.spaces.Discrete` + - Single-element set (e.g.: ``{2}``) + * - :class:`~gymnasium.spaces.MultiDiscrete` + - List of single-element sets (e.g.: ``[{2}, {5}]``) + * - :class:`~gymnasium.spaces.Dict` + - Dictionary (e.g.: ``{"joints": 7, "rgb": [64, 64, 3], "gripper": {2}}``) + * - :class:`~gymnasium.spaces.Tuple` + - Tuple (e.g.: ``(7, [64, 64, 3], {2})``) + """ + + num_actions: dict[AgentID, int] | None = None + """The dimension of the action space for each agent. + + .. warning:: + + This attribute is deprecated. Use :attr:`~omni.isaac.lab.envs.DirectMARLEnvCfg.action_spaces` instead. + """ action_noise_model: dict[AgentID, NoiseModelCfg | None] | None = None """The noise model applied to the actions provided to the environment. Default is None, which means no noise is added. diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_rl_env.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_rl_env.py index 5663977fda..2a0e88cb63 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_rl_env.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_rl_env.py @@ -14,6 +14,7 @@ import weakref from abc import abstractmethod from collections.abc import Sequence +from dataclasses import MISSING from typing import Any, ClassVar import omni.isaac.core.utils.torch as torch_utils @@ -30,6 +31,7 @@ from .common import VecEnvObs, VecEnvStepReturn from .direct_rl_env_cfg import DirectRLEnvCfg from .ui import ViewportCameraController +from .utils.spaces import sample_space, spec_to_gym_space class DirectRLEnv(gym.Env): @@ -171,7 +173,6 @@ def __init__(self, cfg: DirectRLEnvCfg, render_mode: str | None = None, **kwargs self.reset_terminated = torch.zeros(self.num_envs, device=self.device, dtype=torch.bool) self.reset_time_outs = torch.zeros_like(self.reset_terminated) self.reset_buf = torch.zeros(self.num_envs, dtype=torch.bool, device=self.sim.device) - self.actions = torch.zeros(self.num_envs, self.cfg.num_actions, device=self.sim.device) # setup the action and observation spaces for Gym self._configure_gym_env_spaces() @@ -507,27 +508,40 @@ def set_debug_vis(self, debug_vis: bool) -> bool: def _configure_gym_env_spaces(self): """Configure the action and observation spaces for the Gym environment.""" - # observation space (unbounded since we don't impose any limits) - self.num_actions = self.cfg.num_actions - self.num_observations = self.cfg.num_observations - self.num_states = self.cfg.num_states + # show deprecation message and overwrite configuration + if self.cfg.num_actions is not None: + omni.log.warn("DirectRLEnvCfg.num_actions is deprecated. Use DirectRLEnvCfg.action_space instead.") + if isinstance(self.cfg.action_space, type(MISSING)): + self.cfg.action_space = self.cfg.num_actions + if self.cfg.num_observations is not None: + omni.log.warn( + "DirectRLEnvCfg.num_observations is deprecated. Use DirectRLEnvCfg.observation_space instead." + ) + if isinstance(self.cfg.observation_space, type(MISSING)): + self.cfg.observation_space = self.cfg.num_observations + if self.cfg.num_states is not None: + omni.log.warn("DirectRLEnvCfg.num_states is deprecated. Use DirectRLEnvCfg.state_space instead.") + if isinstance(self.cfg.state_space, type(MISSING)): + self.cfg.state_space = self.cfg.num_states # set up spaces self.single_observation_space = gym.spaces.Dict() - self.single_observation_space["policy"] = gym.spaces.Box( - low=-np.inf, high=np.inf, shape=(self.num_observations,) - ) - self.single_action_space = gym.spaces.Box(low=-np.inf, high=np.inf, shape=(self.num_actions,)) + self.single_observation_space["policy"] = spec_to_gym_space(self.cfg.observation_space) + self.single_action_space = spec_to_gym_space(self.cfg.action_space) # batch the spaces for vectorized environments self.observation_space = gym.vector.utils.batch_space(self.single_observation_space["policy"], self.num_envs) self.action_space = gym.vector.utils.batch_space(self.single_action_space, self.num_envs) # optional state space for asymmetric actor-critic architectures - if self.num_states > 0: - self.single_observation_space["critic"] = gym.spaces.Box(low=-np.inf, high=np.inf, shape=(self.num_states,)) + self.state_space = None + if self.cfg.state_space > 0: + self.single_observation_space["critic"] = spec_to_gym_space(self.cfg.state_space) self.state_space = gym.vector.utils.batch_space(self.single_observation_space["critic"], self.num_envs) + # instantiate actions (needed for tasks for which the observations computation is dependent on the actions) + self.actions = sample_space(self.single_action_space, self.sim.device, batch_size=self.num_envs, fill_value=0) + def _reset_idx(self, env_ids: Sequence[int]): """Reset environments based on specified indices. @@ -601,7 +615,7 @@ def _get_states(self) -> VecEnvObs | None: """Compute and return the states for the environment. The state-space is used for asymmetric actor-critic architectures. It is configured - using the :attr:`DirectRLEnvCfg.num_states` parameter. + using the :attr:`DirectRLEnvCfg.state_space` parameter. Returns: The states for the environment. If the environment does not have a state-space, the function diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_rl_env_cfg.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_rl_env_cfg.py index ad8c6c18c8..e86b366cc2 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_rl_env_cfg.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_rl_env_cfg.py @@ -10,7 +10,7 @@ from omni.isaac.lab.utils import configclass from omni.isaac.lab.utils.noise import NoiseModelCfg -from .common import ViewerCfg +from .common import SpaceType, ViewerCfg from .ui import BaseEnvWindow @@ -104,13 +104,68 @@ class DirectRLEnvCfg: Please refer to the :class:`omni.isaac.lab.managers.EventManager` class for more details. """ - num_observations: int = MISSING - """The dimension of the observation space from each environment instance.""" + observation_space: SpaceType = MISSING + """Observation space definition. + + The space can be defined either using Gymnasium :py:mod:`~gymnasium.spaces` (when a more detailed + specification of the space is desired) or basic Python data types (for simplicity). + + .. list-table:: + :header-rows: 1 + + * - Gymnasium space + - Python data type + * - :class:`~gymnasium.spaces.Box` + - Integer or list of integers (e.g.: ``7``, ``[64, 64, 3]``) + * - :class:`~gymnasium.spaces.Discrete` + - Single-element set (e.g.: ``{2}``) + * - :class:`~gymnasium.spaces.MultiDiscrete` + - List of single-element sets (e.g.: ``[{2}, {5}]``) + * - :class:`~gymnasium.spaces.Dict` + - Dictionary (e.g.: ``{"joints": 7, "rgb": [64, 64, 3], "gripper": {2}}``) + * - :class:`~gymnasium.spaces.Tuple` + - Tuple (e.g.: ``(7, [64, 64, 3], {2})``) + """ + + num_observations: int | None = None + """The dimension of the observation space from each environment instance. + + .. warning:: + + This attribute is deprecated. Use :attr:`~omni.isaac.lab.envs.DirectRLEnvCfg.observation_space` instead. + """ - num_states: int = 0 - """The dimension of the state-space from each environment instance. Default is 0, which means no state-space is defined. + state_space: SpaceType = MISSING + """State space definition. This is useful for asymmetric actor-critic and defines the observation space for the critic. + + The space can be defined either using Gymnasium :py:mod:`~gymnasium.spaces` (when a more detailed + specification of the space is desired) or basic Python data types (for simplicity). + + .. list-table:: + :header-rows: 1 + + * - Gymnasium space + - Python data type + * - :class:`~gymnasium.spaces.Box` + - Integer or list of integers (e.g.: ``7``, ``[64, 64, 3]``) + * - :class:`~gymnasium.spaces.Discrete` + - Single-element set (e.g.: ``{2}``) + * - :class:`~gymnasium.spaces.MultiDiscrete` + - List of single-element sets (e.g.: ``[{2}, {5}]``) + * - :class:`~gymnasium.spaces.Dict` + - Dictionary (e.g.: ``{"joints": 7, "rgb": [64, 64, 3], "gripper": {2}}``) + * - :class:`~gymnasium.spaces.Tuple` + - Tuple (e.g.: ``(7, [64, 64, 3], {2})``) + """ + + num_states: int | None = None + """The dimension of the state-space from each environment instance. + + .. warning:: + + This attribute is deprecated. Use :attr:`~omni.isaac.lab.envs.DirectRLEnvCfg.state_space` instead. """ observation_noise_model: NoiseModelCfg | None = None @@ -119,8 +174,36 @@ class DirectRLEnvCfg: Please refer to the :class:`omni.isaac.lab.utils.noise.NoiseModel` class for more details. """ - num_actions: int = MISSING - """The dimension of the action space for each environment.""" + action_space: SpaceType = MISSING + """Action space definition. + + The space can be defined either using Gymnasium :py:mod:`~gymnasium.spaces` (when a more detailed + specification of the space is desired) or basic Python data types (for simplicity). + + .. list-table:: + :header-rows: 1 + + * - Gymnasium space + - Python data type + * - :class:`~gymnasium.spaces.Box` + - Integer or list of integers (e.g.: ``7``, ``[64, 64, 3]``) + * - :class:`~gymnasium.spaces.Discrete` + - Single-element set (e.g.: ``{2}``) + * - :class:`~gymnasium.spaces.MultiDiscrete` + - List of single-element sets (e.g.: ``[{2}, {5}]``) + * - :class:`~gymnasium.spaces.Dict` + - Dictionary (e.g.: ``{"joints": 7, "rgb": [64, 64, 3], "gripper": {2}}``) + * - :class:`~gymnasium.spaces.Tuple` + - Tuple (e.g.: ``(7, [64, 64, 3], {2})``) + """ + + num_actions: int | None = None + """The dimension of the action space for each environment. + + .. warning:: + + This attribute is deprecated. Use :attr:`~omni.isaac.lab.envs.DirectRLEnvCfg.action_space` instead. + """ action_noise_model: NoiseModelCfg | None = None """The noise model applied to the actions provided to the environment. Default is None, which means no noise is added. diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/utils/__init__.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/utils/__init__.py new file mode 100644 index 0000000000..913e1edb90 --- /dev/null +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/utils/__init__.py @@ -0,0 +1,6 @@ +# Copyright (c) 2022-2024, The Isaac Lab Project Developers. +# All rights reserved. +# +# SPDX-License-Identifier: BSD-3-Clause + +"""Sub-package for environment utils.""" diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/utils.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/utils/marl.py similarity index 76% rename from source/extensions/omni.isaac.lab/omni/isaac/lab/envs/utils.py rename to source/extensions/omni.isaac.lab/omni/isaac/lab/envs/utils/marl.py index cacbdeaf81..46519048ae 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/utils.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/utils/marl.py @@ -9,9 +9,9 @@ import torch from typing import Any -from .common import ActionType, AgentID, EnvStepReturn, ObsType, StateType, VecEnvObs, VecEnvStepReturn -from .direct_marl_env import DirectMARLEnv -from .direct_rl_env import DirectRLEnv +from ..common import ActionType, AgentID, EnvStepReturn, ObsType, StateType, VecEnvObs, VecEnvStepReturn +from ..direct_marl_env import DirectMARLEnv +from ..direct_rl_env import DirectRLEnv def multi_agent_to_single_agent(env: DirectMARLEnv, state_as_observation: bool = False) -> DirectRLEnv: @@ -39,7 +39,7 @@ def multi_agent_to_single_agent(env: DirectMARLEnv, state_as_observation: bool = Raises: AssertionError: If the environment state cannot be used as observation since it was explicitly defined - as unconstructed (:attr:`DirectMARLEnvCfg.num_states`). + as unconstructed (:attr:`DirectMARLEnvCfg.state_space`). """ class Env(DirectRLEnv): @@ -49,7 +49,7 @@ def __init__(self, env: DirectMARLEnv) -> None: # check if it is possible to use the multi-agent environment state as single-agent observation self._state_as_observation = state_as_observation if self._state_as_observation: - assert self.env.cfg.num_states != 0, ( + assert self.env.cfg.state_space != 0, ( "The environment state cannot be used as observation since it was explicitly defined as" " unconstructed" ) @@ -58,18 +58,17 @@ def __init__(self, env: DirectMARLEnv) -> None: self.cfg = self.env.cfg self.sim = self.env.sim self.scene = self.env.scene - self.num_actions = sum(self.env.cfg.num_actions.values()) - self.num_observations = sum(self.env.cfg.num_observations.values()) - self.num_states = self.env.cfg.num_states self.single_observation_space = gym.spaces.Dict() if self._state_as_observation: self.single_observation_space["policy"] = self.env.state_space else: - self.single_observation_space["policy"] = gym.spaces.Box( - low=-np.inf, high=np.inf, shape=(self.num_observations,) + self.single_observation_space["policy"] = gym.spaces.flatten_space( + gym.spaces.Tuple([self.env.observation_spaces[agent] for agent in self.env.possible_agents]) ) - self.single_action_space = gym.spaces.Box(low=-np.inf, high=np.inf, shape=(self.num_actions,)) + self.single_action_space = gym.spaces.flatten_space( + gym.spaces.Tuple([self.env.action_spaces[agent] for agent in self.env.possible_agents]) + ) # batch the spaces for vectorized environments self.observation_space = gym.vector.utils.batch_space( @@ -84,18 +83,25 @@ def reset(self, seed: int | None = None, options: dict[str, Any] | None = None) if self._state_as_observation: obs = {"policy": self.env.state()} # concatenate agents' observations + # FIXME: This implementation assumes the spaces are fundamental ones. Fix it to support composite spaces else: - obs = {"policy": torch.cat([obs[agent] for agent in self.env.possible_agents], dim=-1)} + obs = { + "policy": torch.cat( + [obs[agent].reshape(self.num_envs, -1) for agent in self.env.possible_agents], dim=-1 + ) + } return obs, extras def step(self, action: torch.Tensor) -> VecEnvStepReturn: # split single-agent actions to build the multi-agent ones + # FIXME: This implementation assumes the spaces are fundamental ones. Fix it to support composite spaces index = 0 _actions = {} for agent in self.env.possible_agents: - _actions[agent] = action[:, index : index + self.env.cfg.num_actions[agent]] - index += self.env.cfg.num_actions[agent] + delta = gym.spaces.flatdim(self.env.action_spaces[agent]) + _actions[agent] = action[:, index : index + delta] + index += delta # step the environment obs, rewards, terminated, time_outs, extras = self.env.step(_actions) @@ -104,8 +110,13 @@ def step(self, action: torch.Tensor) -> VecEnvStepReturn: if self._state_as_observation: obs = {"policy": self.env.state()} # concatenate agents' observations + # FIXME: This implementation assumes the spaces are fundamental ones. Fix it to support composite spaces else: - obs = {"policy": torch.cat([obs[agent] for agent in self.env.possible_agents], dim=-1)} + obs = { + "policy": torch.cat( + [obs[agent].reshape(self.num_envs, -1) for agent in self.env.possible_agents], dim=-1 + ) + } # process environment outputs to return single-agent data rewards = sum(rewards.values()) @@ -147,7 +158,7 @@ def multi_agent_with_one_agent(env: DirectMARLEnv, state_as_observation: bool = Raises: AssertionError: If the environment state cannot be used as observation since it was explicitly defined - as unconstructed (:attr:`DirectMARLEnvCfg.num_states`). + as unconstructed (:attr:`DirectMARLEnvCfg.state_space`). """ class Env(DirectMARLEnv): @@ -157,7 +168,7 @@ def __init__(self, env: DirectMARLEnv) -> None: # check if it is possible to use the multi-agent environment state as agent observation self._state_as_observation = state_as_observation if self._state_as_observation: - assert self.env.cfg.num_states != 0, ( + assert self.env.cfg.state_space != 0, ( "The environment state cannot be used as observation since it was explicitly defined as" " unconstructed" ) @@ -170,13 +181,13 @@ def __init__(self, env: DirectMARLEnv) -> None: self._exported_observation_spaces = {self._agent_id: self.env.state_space} else: self._exported_observation_spaces = { - self._agent_id: gym.spaces.Box( - low=-np.inf, high=np.inf, shape=(sum(self.env.cfg.num_observations.values()),) + self._agent_id: gym.spaces.flatten_space( + gym.spaces.Tuple([self.env.observation_spaces[agent] for agent in self.env.possible_agents]) ) } self._exported_action_spaces = { - self._agent_id: gym.spaces.Box( - low=-np.inf, high=np.inf, shape=(sum(self.env.cfg.num_actions.values()),) + self._agent_id: gym.spaces.flatten_space( + gym.spaces.Tuple([self.env.action_spaces[agent] for agent in self.env.possible_agents]) ) } @@ -208,18 +219,25 @@ def reset( if self._state_as_observation: obs = {self._agent_id: self.env.state()} # concatenate agents' observations + # FIXME: This implementation assumes the spaces are fundamental ones. Fix it to support composite spaces else: - obs = {self._agent_id: torch.cat([obs[agent] for agent in self.env.possible_agents], dim=-1)} + obs = { + self._agent_id: torch.cat( + [obs[agent].reshape(self.num_envs, -1) for agent in self.env.possible_agents], dim=-1 + ) + } return obs, extras def step(self, actions: dict[AgentID, ActionType]) -> EnvStepReturn: # split agent actions to build the multi-agent ones + # FIXME: This implementation assumes the spaces are fundamental ones. Fix it to support composite spaces index = 0 _actions = {} for agent in self.env.possible_agents: - _actions[agent] = actions[self._agent_id][:, index : index + self.env.cfg.num_actions[agent]] - index += self.env.cfg.num_actions[agent] + delta = gym.spaces.flatdim(self.env.action_spaces[agent]) + _actions[agent] = actions[self._agent_id][:, index : index + delta] + index += delta # step the environment obs, rewards, terminated, time_outs, extras = self.env.step(_actions) @@ -228,8 +246,13 @@ def step(self, actions: dict[AgentID, ActionType]) -> EnvStepReturn: if self._state_as_observation: obs = {self._agent_id: self.env.state()} # concatenate agents' observations + # FIXME: This implementation assumes the spaces are fundamental ones. Fix it to support composite spaces else: - obs = {self._agent_id: torch.cat([obs[agent] for agent in self.env.possible_agents], dim=-1)} + obs = { + self._agent_id: torch.cat( + [obs[agent].reshape(self.num_envs, -1) for agent in self.env.possible_agents], dim=-1 + ) + } # process environment outputs to return agent data rewards = {self._agent_id: sum(rewards.values())} diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/utils/spaces.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/utils/spaces.py new file mode 100644 index 0000000000..8604392ec6 --- /dev/null +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/utils/spaces.py @@ -0,0 +1,92 @@ +# Copyright (c) 2022-2024, The Isaac Lab Project Developers. +# All rights reserved. +# +# SPDX-License-Identifier: BSD-3-Clause + +import gymnasium as gym +import numpy as np +import torch +from typing import Any + +from ..common import SpaceType + + +def spec_to_gym_space(spec: SpaceType) -> gym.spaces.Space: + """Generate an appropriate Gymnasium space according to the given space specification. + + Args: + spec: Space specification. + + Returns: + Gymnasium space. + + Raises: + ValueError: If the given space specification is not valid/supported. + """ + if isinstance(spec, gym.spaces.Space): + return spec + # fundamental spaces + # Box + elif isinstance(spec, int): + return gym.spaces.Box(low=-np.inf, high=np.inf, shape=(spec,)) + elif isinstance(spec, list) and all(isinstance(x, int) for x in spec): + return gym.spaces.Box(low=-np.inf, high=np.inf, shape=spec) + # Discrete + elif isinstance(spec, set) and len(spec) == 1: + return gym.spaces.Discrete(n=next(iter(spec))) + # MultiDiscrete + elif isinstance(spec, list) and all(isinstance(x, set) and len(x) == 1 for x in spec): + return gym.spaces.MultiDiscrete(nvec=[next(iter(x)) for x in spec]) + # composite spaces + # Tuple + elif isinstance(spec, tuple): + return gym.spaces.Tuple([spec_to_gym_space(x) for x in spec]) + # Dict + elif isinstance(spec, dict): + return gym.spaces.Dict({k: spec_to_gym_space(v) for k, v in spec.items()}) + raise ValueError(f"Unsupported space specification: {spec}") + + +def sample_space(space: gym.spaces.Space, device: str, batch_size: int = -1, fill_value: float | None = None) -> Any: + """Sample a Gymnasium space where the data container are PyTorch tensors. + + Args: + space: Gymnasium space. + device: The device where the tensor should be created. + batch_size: Batch size. If the specified value is greater than zero, a batched space will be created and sampled from it. + fill_value: The value to fill the created tensors with. If None (default value), tensors will keep their random values. + + Returns: + Tensorized sampled space. + """ + + def tensorize(s, x): + if isinstance(s, gym.spaces.Box): + tensor = torch.tensor(x, device=device, dtype=torch.float32).reshape(batch_size, *s.shape) + if fill_value is not None: + tensor.fill_(fill_value) + return tensor + elif isinstance(s, gym.spaces.Discrete): + if isinstance(x, np.ndarray): + tensor = torch.tensor(x, device=device, dtype=torch.int64).reshape(batch_size, 1) + if fill_value is not None: + tensor.fill_(int(fill_value)) + return tensor + elif isinstance(x, np.number) or type(x) in [int, float]: + tensor = torch.tensor([x], device=device, dtype=torch.int64).reshape(batch_size, 1) + if fill_value is not None: + tensor.fill_(int(fill_value)) + return tensor + elif isinstance(s, gym.spaces.MultiDiscrete): + if isinstance(x, np.ndarray): + tensor = torch.tensor(x, device=device, dtype=torch.int64).reshape(batch_size, *s.shape) + if fill_value is not None: + tensor.fill_(int(fill_value)) + return tensor + elif isinstance(s, gym.spaces.Dict): + return {k: tensorize(_s, x[k]) for k, _s in s.items()} + elif isinstance(s, gym.spaces.Tuple): + return tuple([tensorize(_s, v) for _s, v in zip(s, x)]) + + sample = (gym.vector.utils.batch_space(space, batch_size) if batch_size > 0 else space).sample() + return tensorize(space, sample) diff --git a/source/extensions/omni.isaac.lab/test/envs/test_spaces_utils.py b/source/extensions/omni.isaac.lab/test/envs/test_spaces_utils.py new file mode 100644 index 0000000000..274f0de650 --- /dev/null +++ b/source/extensions/omni.isaac.lab/test/envs/test_spaces_utils.py @@ -0,0 +1,122 @@ +# Copyright (c) 2022-2024, The Isaac Lab Project Developers. +# All rights reserved. +# +# SPDX-License-Identifier: BSD-3-Clause + +# ignore private usage of variables warning +# pyright: reportPrivateUsage=none + +from __future__ import annotations + +"""Launch Isaac Sim Simulator first.""" + +from omni.isaac.lab.app import AppLauncher, run_tests + +# Can set this to False to see the GUI for debugging +HEADLESS = True + +# launch omniverse app +app_launcher = AppLauncher(headless=HEADLESS) +simulation_app = app_launcher.app + +"""Rest everything follows.""" + +import numpy as np +import torch +import unittest +from gymnasium.spaces import Box, Dict, Discrete, MultiDiscrete, Tuple + +from omni.isaac.lab.envs.utils.spaces import sample_space, spec_to_gym_space + + +class TestSpacesUtils(unittest.TestCase): + """Test for spaces utils' functions""" + + """ + Tests + """ + + def test_spec_to_gym_space(self): + # fundamental spaces + # Box + space = spec_to_gym_space(1) + self.assertIsInstance(space, Box) + self.assertEqual(space.shape, (1,)) + space = spec_to_gym_space([1, 2, 3, 4, 5]) + self.assertIsInstance(space, Box) + self.assertEqual(space.shape, (1, 2, 3, 4, 5)) + space = spec_to_gym_space(Box(low=-1.0, high=1.0, shape=(1, 2))) + self.assertIsInstance(space, Box) + # Discrete + space = spec_to_gym_space({2}) + self.assertIsInstance(space, Discrete) + self.assertEqual(space.n, 2) + space = spec_to_gym_space(Discrete(2)) + self.assertIsInstance(space, Discrete) + # MultiDiscrete + space = spec_to_gym_space([{1}, {2}, {3}]) + self.assertIsInstance(space, MultiDiscrete) + self.assertEqual(space.nvec.shape, (3,)) + space = spec_to_gym_space(MultiDiscrete(np.array([1, 2, 3]))) + self.assertIsInstance(space, MultiDiscrete) + # composite spaces + # Tuple + space = spec_to_gym_space(([1, 2, 3, 4, 5], {2}, [{1}, {2}, {3}])) + self.assertIsInstance(space, Tuple) + self.assertEqual(len(space), 3) + self.assertIsInstance(space[0], Box) + self.assertIsInstance(space[1], Discrete) + self.assertIsInstance(space[2], MultiDiscrete) + space = spec_to_gym_space(Tuple((Box(-1, 1, shape=(1,)), Discrete(2)))) + self.assertIsInstance(space, Tuple) + # Dict + space = spec_to_gym_space({"box": [1, 2, 3, 4, 5], "discrete": {2}, "multi_discrete": [{1}, {2}, {3}]}) + self.assertIsInstance(space, Dict) + self.assertEqual(len(space), 3) + self.assertIsInstance(space["box"], Box) + self.assertIsInstance(space["discrete"], Discrete) + self.assertIsInstance(space["multi_discrete"], MultiDiscrete) + space = spec_to_gym_space(Dict({"box": Box(-1, 1, shape=(1,)), "discrete": Discrete(2)})) + self.assertIsInstance(space, Dict) + + def test_sample_space(self): + device = "cpu" + # fundamental spaces + # Box + sample = sample_space(Box(low=-1.0, high=1.0, shape=(1, 2)), device, batch_size=1) + self.assertIsInstance(sample, torch.Tensor) + self._check_tensorized(sample, batch_size=1) + # Discrete + sample = sample_space(Discrete(2), device, batch_size=2) + self.assertIsInstance(sample, torch.Tensor) + self._check_tensorized(sample, batch_size=2) + # MultiDiscrete + sample = sample_space(MultiDiscrete(np.array([1, 2, 3])), device, batch_size=3) + self.assertIsInstance(sample, torch.Tensor) + self._check_tensorized(sample, batch_size=3) + # composite spaces + # Tuple + sample = sample_space(Tuple((Box(-1, 1, shape=(1,)), Discrete(2))), device, batch_size=4) + self.assertIsInstance(sample, (tuple, list)) + self._check_tensorized(sample, batch_size=4) + # Dict + sample = sample_space(Dict({"box": Box(-1, 1, shape=(1,)), "discrete": Discrete(2)}), device, batch_size=5) + self.assertIsInstance(sample, dict) + self._check_tensorized(sample, batch_size=5) + + """ + Helper functions. + """ + + def _check_tensorized(self, sample, batch_size): + if isinstance(sample, (tuple, list)): + list(map(self._check_tensorized, sample, [batch_size] * len(sample))) + elif isinstance(sample, dict): + list(map(self._check_tensorized, sample.values(), [batch_size] * len(sample))) + else: + self.assertIsInstance(sample, torch.Tensor) + self.assertEqual(sample.shape[0], batch_size) + + +if __name__ == "__main__": + run_tests() diff --git a/source/extensions/omni.isaac.lab_tasks/config/extension.toml b/source/extensions/omni.isaac.lab_tasks/config/extension.toml index 89ca646936..a6ecb7a56c 100644 --- a/source/extensions/omni.isaac.lab_tasks/config/extension.toml +++ b/source/extensions/omni.isaac.lab_tasks/config/extension.toml @@ -1,7 +1,7 @@ [package] # Note: Semantic Versioning is used: https://semver.org/ -version = "0.10.5" +version = "0.10.7" # Description title = "Isaac Lab Environments" diff --git a/source/extensions/omni.isaac.lab_tasks/docs/CHANGELOG.rst b/source/extensions/omni.isaac.lab_tasks/docs/CHANGELOG.rst index 2614630bd7..b3ba0a77fd 100644 --- a/source/extensions/omni.isaac.lab_tasks/docs/CHANGELOG.rst +++ b/source/extensions/omni.isaac.lab_tasks/docs/CHANGELOG.rst @@ -1,11 +1,24 @@ Changelog --------- +0.10.7 (2024-10-02) +~~~~~~~~~~~~~~~~~~~ + +Changed +^^^^^^^ + +* Replace deprecated :attr:`num_observations`, :attr:`num_actions` and :attr:`num_states` in single-agent direct tasks + by :attr:`observation_space`, :attr:`action_space` and :attr:`state_space` respectively. +* Replace deprecated :attr:`num_observations`, :attr:`num_actions` and :attr:`num_states` in multi-agent direct tasks + by :attr:`observation_spaces`, :attr:`action_spaces` and :attr:`state_space` respectively. + + 0.10.6 (2024-09-25) ~~~~~~~~~~~~~~~~~~~ Added ^^^^^ + * Added ``Isaac-Cartpole-RGB-Camera-v0`` and ``Isaac-Cartpole-Depth-Camera-v0`` manager based camera cartpole environments. diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/allegro_hand/allegro_hand_env_cfg.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/allegro_hand/allegro_hand_env_cfg.py index b83b6782a6..b5c53a91d3 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/allegro_hand/allegro_hand_env_cfg.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/allegro_hand/allegro_hand_env_cfg.py @@ -22,9 +22,9 @@ class AllegroHandEnvCfg(DirectRLEnvCfg): # env decimation = 4 episode_length_s = 10.0 - num_actions = 16 - num_observations = 124 # (full) - num_states = 0 + action_space = 16 + observation_space = 124 # (full) + state_space = 0 asymmetric_obs = False obs_type = "full" # simulation diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/ant/ant_env.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/ant/ant_env.py index 8bf6d6bcc9..42f57127ee 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/ant/ant_env.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/ant/ant_env.py @@ -24,9 +24,9 @@ class AntEnvCfg(DirectRLEnvCfg): episode_length_s = 15.0 decimation = 2 action_scale = 0.5 - num_actions = 8 - num_observations = 36 - num_states = 0 + action_space = 8 + observation_space = 36 + state_space = 0 # simulation sim: SimulationCfg = SimulationCfg(dt=1 / 120, render_interval=decimation) diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/anymal_c/anymal_c_env.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/anymal_c/anymal_c_env.py index 5490bb0dd3..ca1f61c54a 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/anymal_c/anymal_c_env.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/anymal_c/anymal_c_env.py @@ -5,6 +5,7 @@ from __future__ import annotations +import gymnasium as gym import torch import omni.isaac.lab.envs.mdp as mdp @@ -59,9 +60,9 @@ class AnymalCFlatEnvCfg(DirectRLEnvCfg): episode_length_s = 20.0 decimation = 4 action_scale = 0.5 - num_actions = 12 - num_observations = 48 - num_states = 0 + action_space = 12 + observation_space = 48 + state_space = 0 # simulation sim: SimulationCfg = SimulationCfg( @@ -118,7 +119,7 @@ class AnymalCFlatEnvCfg(DirectRLEnvCfg): @configclass class AnymalCRoughEnvCfg(AnymalCFlatEnvCfg): # env - num_observations = 235 + observation_space = 235 terrain = TerrainImporterCfg( prim_path="/World/ground", @@ -160,8 +161,10 @@ def __init__(self, cfg: AnymalCFlatEnvCfg | AnymalCRoughEnvCfg, render_mode: str super().__init__(cfg, render_mode, **kwargs) # Joint position command (deviation from default joint positions) - self._actions = torch.zeros(self.num_envs, self.cfg.num_actions, device=self.device) - self._previous_actions = torch.zeros(self.num_envs, self.cfg.num_actions, device=self.device) + self._actions = torch.zeros(self.num_envs, gym.spaces.flatdim(self.single_action_space), device=self.device) + self._previous_actions = torch.zeros( + self.num_envs, gym.spaces.flatdim(self.single_action_space), device=self.device + ) # X/Y linear velocity and yaw angular velocity commands self._commands = torch.zeros(self.num_envs, 3, device=self.device) diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/cart_double_pendulum/cart_double_pendulum_env.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/cart_double_pendulum/cart_double_pendulum_env.py index 0b606fe899..ad8c616940 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/cart_double_pendulum/cart_double_pendulum_env.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/cart_double_pendulum/cart_double_pendulum_env.py @@ -27,9 +27,9 @@ class CartDoublePendulumEnvCfg(DirectMARLEnvCfg): decimation = 2 episode_length_s = 5.0 possible_agents = ["cart", "pendulum"] - num_actions = {"cart": 1, "pendulum": 1} - num_observations = {"cart": 4, "pendulum": 3} - num_states = -1 + action_spaces = {"cart": 1, "pendulum": 1} + observation_spaces = {"cart": 4, "pendulum": 3} + state_space = -1 # simulation sim: SimulationCfg = SimulationCfg(dt=1 / 120, render_interval=decimation) diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/cartpole/cartpole_camera_env.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/cartpole/cartpole_camera_env.py index b2a1b1e303..dc7db07030 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/cartpole/cartpole_camera_env.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/cartpole/cartpole_camera_env.py @@ -5,9 +5,7 @@ from __future__ import annotations -import gymnasium as gym import math -import numpy as np import torch from collections.abc import Sequence @@ -29,9 +27,6 @@ class CartpoleRGBCameraEnvCfg(DirectRLEnvCfg): decimation = 2 episode_length_s = 5.0 action_scale = 100.0 # [N] - num_actions = 1 - num_channels = 3 - num_states = 0 # simulation sim: SimulationCfg = SimulationCfg(dt=1 / 120, render_interval=decimation) @@ -52,9 +47,13 @@ class CartpoleRGBCameraEnvCfg(DirectRLEnvCfg): width=80, height=80, ) - num_observations = num_channels * tiled_camera.height * tiled_camera.width write_image_to_file = False + # spaces + action_space = 1 + state_space = 0 + observation_space = [tiled_camera.height, tiled_camera.width, 3] + # change viewer settings viewer = ViewerCfg(eye=(20.0, 20.0, 20.0)) @@ -87,9 +86,8 @@ class CartpoleDepthCameraEnvCfg(CartpoleRGBCameraEnvCfg): height=80, ) - # env - num_channels = 1 - num_observations = num_channels * tiled_camera.height * tiled_camera.width + # spaces + observation_space = [tiled_camera.height, tiled_camera.width, 1] class CartpoleCameraEnv(DirectRLEnv): @@ -118,35 +116,6 @@ def close(self): """Cleanup for the environment.""" super().close() - def _configure_gym_env_spaces(self): - """Configure the action and observation spaces for the Gym environment.""" - # observation space (unbounded since we don't impose any limits) - self.num_actions = self.cfg.num_actions - self.num_observations = self.cfg.num_observations - self.num_states = self.cfg.num_states - - # set up spaces - self.single_observation_space = gym.spaces.Dict() - self.single_observation_space["policy"] = gym.spaces.Box( - low=-np.inf, - high=np.inf, - shape=(self.cfg.tiled_camera.height, self.cfg.tiled_camera.width, self.cfg.num_channels), - ) - if self.num_states > 0: - self.single_observation_space["critic"] = gym.spaces.Box( - low=-np.inf, - high=np.inf, - shape=(self.cfg.tiled_camera.height, self.cfg.tiled_camera.width, self.cfg.num_channels), - ) - self.single_action_space = gym.spaces.Box(low=-np.inf, high=np.inf, shape=(self.num_actions,)) - - # batch the spaces for vectorized environments - self.observation_space = gym.vector.utils.batch_space(self.single_observation_space, self.num_envs) - self.action_space = gym.vector.utils.batch_space(self.single_action_space, self.num_envs) - - # RL specifics - self.actions = torch.zeros(self.num_envs, self.num_actions, device=self.sim.device) - def _setup_scene(self): """Setup the scene with the cartpole and camera.""" self._cartpole = Articulation(self.cfg.robot_cfg) diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/cartpole/cartpole_env.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/cartpole/cartpole_env.py index 44926e95f9..534fb26443 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/cartpole/cartpole_env.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/cartpole/cartpole_env.py @@ -27,9 +27,9 @@ class CartpoleEnvCfg(DirectRLEnvCfg): decimation = 2 episode_length_s = 5.0 action_scale = 100.0 # [N] - num_actions = 1 - num_observations = 4 - num_states = 0 + action_space = 1 + observation_space = 4 + state_space = 0 # simulation sim: SimulationCfg = SimulationCfg(dt=1 / 120, render_interval=decimation) diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/franka_cabinet/franka_cabinet_env.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/franka_cabinet/franka_cabinet_env.py index 4eb01953fe..3a6a480ed0 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/franka_cabinet/franka_cabinet_env.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/franka_cabinet/franka_cabinet_env.py @@ -28,9 +28,9 @@ class FrankaCabinetEnvCfg(DirectRLEnvCfg): # env episode_length_s = 8.3333 # 500 timesteps decimation = 2 - num_actions = 9 - num_observations = 23 - num_states = 0 + action_space = 9 + observation_space = 23 + state_space = 0 # simulation sim: SimulationCfg = SimulationCfg( diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/humanoid/humanoid_env.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/humanoid/humanoid_env.py index bfaf8f8190..2a4d330e6a 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/humanoid/humanoid_env.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/humanoid/humanoid_env.py @@ -24,9 +24,9 @@ class HumanoidEnvCfg(DirectRLEnvCfg): episode_length_s = 15.0 decimation = 2 action_scale = 1.0 - num_actions = 21 - num_observations = 75 - num_states = 0 + action_space = 21 + observation_space = 75 + state_space = 0 # simulation sim: SimulationCfg = SimulationCfg(dt=1 / 120, render_interval=decimation) diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/quadcopter/quadcopter_env.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/quadcopter/quadcopter_env.py index c6df659ec6..97156618f1 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/quadcopter/quadcopter_env.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/quadcopter/quadcopter_env.py @@ -5,6 +5,7 @@ from __future__ import annotations +import gymnasium as gym import torch import omni.isaac.lab.sim as sim_utils @@ -50,9 +51,9 @@ class QuadcopterEnvCfg(DirectRLEnvCfg): # env episode_length_s = 10.0 decimation = 2 - num_actions = 4 - num_observations = 12 - num_states = 0 + action_space = 4 + observation_space = 12 + state_space = 0 debug_vis = True ui_window_class_type = QuadcopterEnvWindow @@ -105,7 +106,7 @@ def __init__(self, cfg: QuadcopterEnvCfg, render_mode: str | None = None, **kwar super().__init__(cfg, render_mode, **kwargs) # Total thrust and moment applied to the base of the quadcopter - self._actions = torch.zeros(self.num_envs, self.cfg.num_actions, device=self.device) + self._actions = torch.zeros(self.num_envs, gym.spaces.flatdim(self.single_action_space), device=self.device) self._thrust = torch.zeros(self.num_envs, 1, 3, device=self.device) self._moment = torch.zeros(self.num_envs, 1, 3, device=self.device) # Goal position diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/shadow_hand/shadow_hand_env_cfg.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/shadow_hand/shadow_hand_env_cfg.py index f4b8407296..af88124792 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/shadow_hand/shadow_hand_env_cfg.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/shadow_hand/shadow_hand_env_cfg.py @@ -119,9 +119,9 @@ class ShadowHandEnvCfg(DirectRLEnvCfg): # env decimation = 2 episode_length_s = 10.0 - num_actions = 20 - num_observations = 157 # (full) - num_states = 0 + action_space = 20 + observation_space = 157 # (full) + state_space = 0 asymmetric_obs = False obs_type = "full" @@ -232,9 +232,9 @@ class ShadowHandOpenAIEnvCfg(ShadowHandEnvCfg): # env decimation = 3 episode_length_s = 8.0 - num_actions = 20 - num_observations = 42 - num_states = 187 + action_space = 20 + observation_space = 42 + state_space = 187 asymmetric_obs = True obs_type = "openai" # simulation diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/shadow_hand/shadow_hand_vision_env.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/shadow_hand/shadow_hand_vision_env.py index b025bfb052..492074d8a9 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/shadow_hand/shadow_hand_vision_env.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/shadow_hand/shadow_hand_vision_env.py @@ -48,8 +48,8 @@ class ShadowHandVisionEnvCfg(ShadowHandEnvCfg): feature_extractor = FeatureExtractorCfg() # env - num_observations = 164 + 27 # state observation + vision CNN embedding - num_states = 187 + 27 # asymettric states + vision CNN embedding + observation_space = 164 + 27 # state observation + vision CNN embedding + state_space = 187 + 27 # asymettric states + vision CNN embedding @configclass diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/shadow_hand_over/shadow_hand_over_env_cfg.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/shadow_hand_over/shadow_hand_over_env_cfg.py index d6dbb3d6a2..d3a7c33b3f 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/shadow_hand_over/shadow_hand_over_env_cfg.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/shadow_hand_over/shadow_hand_over_env_cfg.py @@ -118,9 +118,9 @@ class ShadowHandOverEnvCfg(DirectMARLEnvCfg): decimation = 2 episode_length_s = 7.5 possible_agents = ["right_hand", "left_hand"] - num_actions = {"right_hand": 20, "left_hand": 20} - num_observations = {"right_hand": 157, "left_hand": 157} - num_states = 290 + action_spaces = {"right_hand": 20, "left_hand": 20} + observation_spaces = {"right_hand": 157, "left_hand": 157} + state_space = 290 # simulation sim: SimulationCfg = SimulationCfg( diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/utils/wrappers/rsl_rl/vecenv_wrapper.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/utils/wrappers/rsl_rl/vecenv_wrapper.py index 0badd08c31..0dedef9ef0 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/utils/wrappers/rsl_rl/vecenv_wrapper.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/utils/wrappers/rsl_rl/vecenv_wrapper.py @@ -70,19 +70,19 @@ def __init__(self, env: ManagerBasedRLEnv | DirectRLEnv): if hasattr(self.unwrapped, "action_manager"): self.num_actions = self.unwrapped.action_manager.total_action_dim else: - self.num_actions = self.unwrapped.num_actions + self.num_actions = gym.spaces.flatdim(self.unwrapped.single_action_space) if hasattr(self.unwrapped, "observation_manager"): self.num_obs = self.unwrapped.observation_manager.group_obs_dim["policy"][0] else: - self.num_obs = self.unwrapped.num_observations + self.num_obs = gym.spaces.flatdim(self.unwrapped.single_observation_space["policy"]) # -- privileged observations if ( hasattr(self.unwrapped, "observation_manager") and "critic" in self.unwrapped.observation_manager.group_obs_dim ): self.num_privileged_obs = self.unwrapped.observation_manager.group_obs_dim["critic"][0] - elif hasattr(self.unwrapped, "num_states"): - self.num_privileged_obs = self.unwrapped.num_states + elif hasattr(self.unwrapped, "num_states") and "critic" in self.unwrapped.single_observation_space: + self.num_privileged_obs = gym.spaces.flatdim(self.unwrapped.single_observation_space["critic"]) else: self.num_privileged_obs = 0 # reset at the start since the RSL-RL runner does not call reset diff --git a/source/extensions/omni.isaac.lab_tasks/test/test_environments.py b/source/extensions/omni.isaac.lab_tasks/test/test_environments.py index 9e92e26156..993b776a81 100644 --- a/source/extensions/omni.isaac.lab_tasks/test/test_environments.py +++ b/source/extensions/omni.isaac.lab_tasks/test/test_environments.py @@ -22,6 +22,7 @@ import omni.usd from omni.isaac.lab.envs import ManagerBasedRLEnvCfg +from omni.isaac.lab.envs.utils import sample_space import omni.isaac.lab_tasks # noqa: F401 from omni.isaac.lab_tasks.utils.parse_cfg import parse_env_cfg @@ -108,12 +109,12 @@ def _check_random_actions(self, task_name: str, device: str, num_envs: int, num_ # simulate environment for num_steps steps with torch.inference_mode(): for _ in range(num_steps): - # sample actions from -1 to 1 - actions = 2 * torch.rand(env.action_space.shape, device=env.unwrapped.device) - 1 + # sample actions according to the defined space + actions = sample_space(env.single_action_space, device=env.unwrapped.device, batch_size=num_envs) # apply actions transition = env.step(actions) # check signals - for data in transition: + for data in transition[:-1]: # exclude info self.assertTrue(self._check_valid_tensor(data), msg=f"Invalid data: {data}") # close the environment @@ -131,14 +132,10 @@ def _check_valid_tensor(data: torch.Tensor | dict) -> bool: """ if isinstance(data, torch.Tensor): return not torch.any(torch.isnan(data)) + elif isinstance(data, (tuple, list)): + return all(TestEnvironments._check_valid_tensor(value) for value in data) elif isinstance(data, dict): - valid_tensor = True - for value in data.values(): - if isinstance(value, dict): - valid_tensor &= TestEnvironments._check_valid_tensor(value) - elif isinstance(value, torch.Tensor): - valid_tensor &= not torch.any(torch.isnan(value)) - return valid_tensor + return all(TestEnvironments._check_valid_tensor(value) for value in data.values()) else: raise ValueError(f"Input data of invalid type: {type(data)}.") diff --git a/source/extensions/omni.isaac.lab_tasks/test/test_multi_agent_environments.py b/source/extensions/omni.isaac.lab_tasks/test/test_multi_agent_environments.py index 19fcd88936..2f543a84e3 100644 --- a/source/extensions/omni.isaac.lab_tasks/test/test_multi_agent_environments.py +++ b/source/extensions/omni.isaac.lab_tasks/test/test_multi_agent_environments.py @@ -21,6 +21,7 @@ import omni.usd from omni.isaac.lab.envs import DirectMARLEnv, DirectMARLEnvCfg +from omni.isaac.lab.envs.utils import sample_space import omni.isaac.lab_tasks # noqa: F401 from omni.isaac.lab_tasks.utils.parse_cfg import parse_env_cfg @@ -104,9 +105,9 @@ def _check_random_actions(self, task_name: str, device: str, num_envs: int, num_ # simulate environment for num_steps steps with torch.inference_mode(): for _ in range(num_steps): - # sample actions from -1 to 1 + # sample actions according to the defined space actions = { - agent: 2 * torch.rand(env.action_space(agent).shape, device=env.unwrapped.device) - 1 + agent: sample_space(env.action_spaces[agent], device=env.unwrapped.device) for agent in env.unwrapped.possible_agents } # apply actions @@ -131,14 +132,10 @@ def _check_valid_tensor(data: torch.Tensor | dict) -> bool: """ if isinstance(data, torch.Tensor): return not torch.any(torch.isnan(data)) + elif isinstance(data, (tuple, list)): + return all(TestEnvironments._check_valid_tensor(value) for value in data) elif isinstance(data, dict): - valid_tensor = True - for value in data.values(): - if isinstance(value, dict): - valid_tensor &= TestEnvironments._check_valid_tensor(value) - elif isinstance(value, torch.Tensor): - valid_tensor &= not torch.any(torch.isnan(value)) - return valid_tensor + return all(TestEnvironments._check_valid_tensor(value) for value in data.values()) else: raise ValueError(f"Input data of invalid type: {type(data)}.") From 0bccd886c19a9891c0b6bdd37e13f338eacc0bba Mon Sep 17 00:00:00 2001 From: Sheikh Dawood Date: Fri, 18 Oct 2024 05:15:12 -0500 Subject: [PATCH 026/111] Adds versioning to the docs (#1247) # Description Adds versioning to the docs. Users can now choose a specific tag from version v1.0.0 onwards. ## Type of change - New feature (non-breaking change which adds functionality) ## Checklist - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [x] I have made corresponding changes to the documentation - [ ] My changes generate no new warnings - [ ] I have added tests that prove my fix is effective or that my feature works - [ ] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [x] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --- .github/workflows/docs.yaml | 79 +++++++++-------- CONTRIBUTORS.md | 1 + docs/Makefile | 16 ++-- docs/README.md | 85 ++++++++++++++----- docs/_redirect/index.html | 8 ++ docs/_templates/versioning.html | 21 +++++ docs/conf.py | 22 ++++- .../sphinx-multiversion-license.txt | 25 ++++++ docs/make.bat | 71 +++++++++++----- docs/requirements.txt | 2 + isaaclab.bat | 4 +- isaaclab.sh | 4 +- 12 files changed, 245 insertions(+), 93 deletions(-) create mode 100644 docs/_redirect/index.html create mode 100644 docs/_templates/versioning.html create mode 100644 docs/licenses/dependencies/sphinx-multiversion-license.txt diff --git a/.github/workflows/docs.yaml b/.github/workflows/docs.yaml index b0ceb6bff7..92f854ac96 100644 --- a/.github/workflows/docs.yaml +++ b/.github/workflows/docs.yaml @@ -1,6 +1,8 @@ name: Build & deploy docs -on: [push] +on: + push: + pull_request: jobs: build-docs: @@ -8,28 +10,35 @@ jobs: runs-on: ubuntu-latest steps: - - name: Checkout code - uses: actions/checkout@v2 + - name: Checkout code + uses: actions/checkout@v2 - - name: Setup python - uses: actions/setup-python@v2 - with: - python-version: "3.10" - architecture: x64 + - name: Setup python + uses: actions/setup-python@v2 + with: + python-version: "3.10" + architecture: x64 - - name: Install dev requirements - working-directory: ./docs - run: pip install -r requirements.txt + - name: Install dev requirements + working-directory: ./docs + run: pip install -r requirements.txt - - name: Generate docs - working-directory: ./docs - run: make html + - name: Check branch docs building + if: ${{ github.event_name == 'pull_request' }} + working-directory: ./docs + run: make current-docs - - name: Upload docs artifact - uses: actions/upload-artifact@v4 - with: - name: docs-html - path: ./docs/_build/html + - name: Generate multi-version docs + working-directory: ./docs + run: | + git fetch --prune --unshallow --tags + make multi-docs + + - name: Upload docs artifact + uses: actions/upload-artifact@v4 + with: + name: docs-html + path: ./docs/_build check-secrets: name: Check secrets @@ -37,12 +46,12 @@ jobs: outputs: trigger-deploy: ${{ steps.trigger-deploy.outputs.defined }} steps: - - id: trigger-deploy - env: - REPO_NAME: ${{ secrets.REPO_NAME }} - BRANCH_REF: ${{ secrets.BRANCH_REF }} - if: "${{ github.repository == env.REPO_NAME && github.ref == env.BRANCH_REF }}" - run: echo "defined=true" >> "$GITHUB_OUTPUT" + - id: trigger-deploy + env: + REPO_NAME: ${{ secrets.REPO_NAME }} + BRANCH_REF: ${{ secrets.BRANCH_REF }} + if: "${{ github.repository == env.REPO_NAME && github.ref == env.BRANCH_REF }}" + run: echo "defined=true" >> "$GITHUB_OUTPUT" deploy-docs: name: Deploy Docs @@ -51,14 +60,14 @@ jobs: if: needs.check-secrets.outputs.trigger-deploy == 'true' steps: - - name: Download docs artifact - uses: actions/download-artifact@v4 - with: - name: docs-html - path: ./docs/_build/html + - name: Download docs artifact + uses: actions/download-artifact@v4 + with: + name: docs-html + path: ./docs/_build - - name: Deploy to gh-pages - uses: peaceiris/actions-gh-pages@v3 - with: - github_token: ${{ secrets.GITHUB_TOKEN }} - publish_dir: ./docs/_build/html + - name: Deploy to gh-pages + uses: peaceiris/actions-gh-pages@v3 + with: + github_token: ${{ secrets.GITHUB_TOKEN }} + publish_dir: ./docs/_build diff --git a/CONTRIBUTORS.md b/CONTRIBUTORS.md index 244b910786..3c345a9d31 100644 --- a/CONTRIBUTORS.md +++ b/CONTRIBUTORS.md @@ -28,6 +28,7 @@ Guidelines for modifications: * Mayank Mittal * Nikita Rudin * Pascal Roth +* Sheikh Dawood ## Contributors diff --git a/docs/Makefile b/docs/Makefile index d4bb2cbb9e..ce33dad503 100644 --- a/docs/Makefile +++ b/docs/Makefile @@ -8,13 +8,11 @@ SPHINXBUILD ?= sphinx-build SOURCEDIR = . BUILDDIR = _build -# Put it first so that "make" without argument is like "make help". -help: - @$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O) +.PHONY: multi-docs +multi-docs: + @sphinx-multiversion "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) + @cp _redirect/index.html $(BUILDDIR)/index.html -.PHONY: help Makefile - -# Catch-all target: route all unknown targets to Sphinx using the new -# "make mode" option. $(O) is meant as a shortcut for $(SPHINXOPTS). -%: Makefile - @$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O) +.PHONY: current-docs +current-docs: + @$(SPHINXBUILD) "$(SOURCEDIR)" "$(BUILDDIR)/current" $(SPHINXOPTS) diff --git a/docs/README.md b/docs/README.md index c154e0ad0f..69a77a48d9 100644 --- a/docs/README.md +++ b/docs/README.md @@ -1,30 +1,75 @@ # Building Documentation -We use [Sphinx](https://www.sphinx-doc.org/en/master/) with the [Book Theme](https://sphinx-book-theme.readthedocs.io/en/stable/) for maintaining the documentation. +We use [Sphinx](https://www.sphinx-doc.org/en/master/) with the [Book Theme](https://sphinx-book-theme.readthedocs.io/en/stable/) for maintaining and generating our documentation. -> **Note:** To build the documentation, we recommend creating a virtual environment to avoid any conflicts with system installed dependencies. +> **Note:** To avoid dependency conflicts, we strongly recommend using a Python virtual environment to isolate the required dependencies from your system's global Python environment. -Execute the following instructions to build the documentation (assumed from the top of the repository): +## Current-Version Documentation -1. Install the dependencies for [Sphinx](https://www.sphinx-doc.org/en/master/): +This section describes how to build the documentation for the current version of the project. - ```bash - # enter the location where this readme exists - cd docs - # install dependencies - pip install -r requirements.txt - ``` +

+Linux -2. Generate the documentation file via: +```bash +# 1. Navigate to the docs directory and install dependencies +cd docs +pip install -r requirements.txt - ```bash - # make the html version - make html - ``` +# 2. Build the current documentation +make current-docs -3. The documentation is now available at `docs/_build/html/index.html`: +# 3. Open the current docs +xdg-open _build/current/index.html +``` +
- ```bash - # open on default browser - xdg-open _build/html/index.html - ``` +
Windows + +```batch +:: 1. Navigate to the docs directory and install dependencies +cd docs +pip install -r requirements.txt + +:: 2. Build the current documentation +make current-docs + +:: 3. Open the current docs +start _build\current\index.html +``` +
+ + +## Multi-Version Documentation + +This section describes how to build the multi-version documentation, which includes previous tags and the main branch. + +
Linux + +```bash +# 1. Navigate to the docs directory and install dependencies +cd docs +pip install -r requirements.txt + +# 2. Build the multi-version documentation +make multi-docs + +# 3. Open the multi-version docs +xdg-open _build/index.html +``` +
+ +
Windows + +```batch +:: 1. Navigate to the docs directory and install dependencies +cd docs +pip install -r requirements.txt + +:: 2. Build the multi-version documentation +make multi-docs + +:: 3. Open the multi-version docs +start _build\index.html +``` +
diff --git a/docs/_redirect/index.html b/docs/_redirect/index.html new file mode 100644 index 0000000000..5208597ed1 --- /dev/null +++ b/docs/_redirect/index.html @@ -0,0 +1,8 @@ + + + + Redirecting to the latest Isaac Lab documentation + + + + diff --git a/docs/_templates/versioning.html b/docs/_templates/versioning.html new file mode 100644 index 0000000000..eb67be60e1 --- /dev/null +++ b/docs/_templates/versioning.html @@ -0,0 +1,21 @@ +{% if versions %} + +{% endif %} diff --git a/docs/conf.py b/docs/conf.py index a30e673280..4c7a777559 100644 --- a/docs/conf.py +++ b/docs/conf.py @@ -54,6 +54,8 @@ "sphinxcontrib.icon", "sphinx_copybutton", "sphinx_design", + "sphinx_tabs.tabs", # backwards compatibility for building docs on v1.0.0 + "sphinx_multiversion", ] # mathjax hacks @@ -115,7 +117,7 @@ # List of patterns, relative to source directory, that match files and # directories to ignore when looking for source files. # This pattern also affects html_static_path and html_extra_path. -exclude_patterns = ["_build", "Thumbs.db", ".DS_Store", "README.md", "licenses/*"] +exclude_patterns = ["_build", "_redirect", "_templates", "Thumbs.db", ".DS_Store", "README.md", "licenses/*"] # Mock out modules that are not available on RTD autodoc_mock_imports = [ @@ -190,7 +192,7 @@ import sphinx_book_theme -html_title = "Isaac Lab documentation" +html_title = "Isaac Lab Documentation" html_theme_path = [sphinx_book_theme.get_html_theme_path()] html_theme = "sphinx_book_theme" html_favicon = "source/_static/favicon.ico" @@ -213,7 +215,7 @@ "show_toc_level": 1, "use_sidenotes": True, "logo": { - "text": "Isaac Lab documentation", + "text": "Isaac Lab Documentation", "image_light": "source/_static/NVIDIA-logo-white.png", "image_dark": "source/_static/NVIDIA-logo-black.png", }, @@ -240,7 +242,19 @@ "icon_links_label": "Quick Links", } -html_sidebars = {"**": ["navbar-logo.html", "icon-links.html", "search-field.html", "sbt-sidebar-nav.html"]} +templates_path = [ + "_templates", +] + +# Whitelist pattern for remotes +smv_remote_whitelist = r"^.*$" +# Whitelist pattern for branches (set to None to ignore all branches) +smv_branch_whitelist = os.getenv("SMV_BRANCH_WHITELIST", r"^(main|devel)$") +# Whitelist pattern for tags (set to None to ignore all tags) +smv_tag_whitelist = os.getenv("SMV_TAG_WHITELIST", r"^v[1-9]\d*\.\d+\.\d+$") +html_sidebars = { + "**": ["navbar-logo.html", "versioning.html", "icon-links.html", "search-field.html", "sbt-sidebar-nav.html"] +} # -- Advanced configuration ------------------------------------------------- diff --git a/docs/licenses/dependencies/sphinx-multiversion-license.txt b/docs/licenses/dependencies/sphinx-multiversion-license.txt new file mode 100644 index 0000000000..172d6b3f5d --- /dev/null +++ b/docs/licenses/dependencies/sphinx-multiversion-license.txt @@ -0,0 +1,25 @@ +BSD 2-Clause License + +Copyright (c) 2020, Jan Holthuis +All rights reserved. + +Redistribution and use in source and binary forms, with or without +modification, are permitted provided that the following conditions are met: + +1. Redistributions of source code must retain the above copyright notice, this + list of conditions and the following disclaimer. + +2. Redistributions in binary form must reproduce the above copyright notice, + this list of conditions and the following disclaimer in the documentation + and/or other materials provided with the distribution. + +THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" +AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE +IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE +DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE +FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL +DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR +SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER +CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, +OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE +OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. diff --git a/docs/make.bat b/docs/make.bat index 2119f51099..cdaf22f257 100644 --- a/docs/make.bat +++ b/docs/make.bat @@ -2,34 +2,63 @@ pushd %~dp0 -REM Command file for Sphinx documentation +REM Command file to build Sphinx documentation -if "%SPHINXBUILD%" == "" ( - set SPHINXBUILD=sphinx-build -) set SOURCEDIR=. set BUILDDIR=_build -if "%1" == "" goto help - -%SPHINXBUILD% >NUL 2>NUL -if errorlevel 9009 ( - echo. - echo.The 'sphinx-build' command was not found. Make sure you have Sphinx - echo.installed, then set the SPHINXBUILD environment variable to point - echo.to the full path of the 'sphinx-build' executable. Alternatively you - echo.may add the Sphinx directory to PATH. - echo. - echo.If you don't have Sphinx installed, grab it from - echo.http://sphinx-doc.org/ - exit /b 1 +REM Check if a specific target was passed +if "%1" == "multi-docs" ( + REM Check if SPHINXBUILD is set, if not default to sphinx-multiversion + if "%SPHINXBUILD%" == "" ( + set SPHINXBUILD=sphinx-multiversion + ) + %SPHINXBUILD% >NUL 2>NUL + if errorlevel 9009 ( + echo. + echo.The 'sphinx-multiversion' command was not found. Make sure you have Sphinx + echo.installed, then set the SPHINXBUILD environment variable to point + echo.to the full path of the 'sphinx-multiversion' executable. Alternatively you + echo.may add the Sphinx directory to PATH. + echo. + echo.If you don't have Sphinx installed, grab it from + echo.http://sphinx-doc.org/ + exit /b 1 + ) + %SPHINXBUILD% %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O% + + REM Copy the redirect index.html to the build directory + copy _redirect\index.html %BUILDDIR%\index.html + goto end ) -%SPHINXBUILD% -M %1 %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O% -goto end +if "%1" == "current-docs" ( + REM Check if SPHINXBUILD is set, if not default to sphinx-build + if "%SPHINXBUILD%" == "" ( + set SPHINXBUILD=sphinx-build + ) + %SPHINXBUILD% >NUL 2>NUL + if errorlevel 9009 ( + echo. + echo.The 'sphinx-build' command was not found. Make sure you have Sphinx + echo.installed, then set the SPHINXBUILD environment variable to point + echo.to the full path of the 'sphinx-build' executable. Alternatively you + echo.may add the Sphinx directory to PATH. + echo. + echo.If you don't have Sphinx installed, grab it from + echo.http://sphinx-doc.org/ + exit /b 1 + ) + %SPHINXBUILD% %SOURCEDIR% %BUILDDIR%\current %SPHINXOPTS% %O% + goto end +) -:help -%SPHINXBUILD% -M help %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O% +REM If no valid target is passed, show usage instructions +echo. +echo.Usage: +echo. make.bat multi-docs - To build the multi-version documentation. +echo. make.bat current-docs - To build the current documentation. +echo. :end popd diff --git a/docs/requirements.txt b/docs/requirements.txt index 33917bd712..13b2bfe9d6 100644 --- a/docs/requirements.txt +++ b/docs/requirements.txt @@ -7,6 +7,8 @@ sphinx-copybutton sphinx-icon sphinx_design sphinxemoji +sphinx-tabs # backwards compatibility for building docs on v1.0.0 +sphinx-multiversion==0.2.4 # basic python numpy diff --git a/isaaclab.bat b/isaaclab.bat index b415ef1a13..09c6818e37 100644 --- a/isaaclab.bat +++ b/isaaclab.bat @@ -519,9 +519,9 @@ if "%arg%"=="-i" ( call :extract_python_exe pushd %ISAACLAB_PATH%\docs call !python_exe! -m pip install -r requirements.txt >nul - call !python_exe! -m sphinx -b html -d _build\doctrees . _build\html + call !python_exe! -m sphinx -b html -d _build\doctrees . _build\current echo [INFO] To open documentation on default browser, run: - echo xdg-open "%ISAACLAB_PATH%\docs\_build\html\index.html" + echo xdg-open "%ISAACLAB_PATH%\docs\_build\current\index.html" popd >nul shift goto :end diff --git a/isaaclab.sh b/isaaclab.sh index a604706e70..22374fe0ff 100755 --- a/isaaclab.sh +++ b/isaaclab.sh @@ -396,10 +396,10 @@ while [[ $# -gt 0 ]]; do cd ${ISAACLAB_PATH}/docs ${python_exe} -m pip install -r requirements.txt > /dev/null # build the documentation - ${python_exe} -m sphinx -b html -d _build/doctrees . _build/html + ${python_exe} -m sphinx -b html -d _build/doctrees . _build/current # open the documentation echo -e "[INFO] To open documentation on default browser, run:" - echo -e "\n\t\txdg-open $(pwd)/_build/html/index.html\n" + echo -e "\n\t\txdg-open $(pwd)/_build/current/index.html\n" # exit neatly cd - > /dev/null shift # past argument From 91f760ee91027b65d8abf1400c3f36218b58e3f0 Mon Sep 17 00:00:00 2001 From: David Hoeller Date: Fri, 18 Oct 2024 18:30:45 +0200 Subject: [PATCH 027/111] Fixes the unit test success criterion in the CI pipeline (#1251) # Description - Fixes the condition for a test to report success in the `run_all_tests.py` script. Before, the test could crash and the script would still report a success. Now we have an explicit check to verify the test reports success. - Improved the tests involving environments. Before they could crash during initialization without any error message and interrupting the test. This is now caught and reported, the subtest failed, and the running the other subtests is resumed properly. ## Type of change - Bug fix (non-breaking change which fixes an issue) ## Checklist - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [ ] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [ ] I have added tests that prove my fix is effective or that my feature works - [ ] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [x] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --- .../omni/isaac/lab/envs/direct_rl_env.py | 2 +- .../omni/isaac/lab/envs/direct_rl_env_cfg.py | 2 +- .../test/envs/test_direct_marl_env.py | 26 +-- .../test/envs/test_env_rendering_logic.py | 27 ++- .../test/sim/test_simulation_context.py | 55 +++--- .../test/test_environments.py | 30 +-- .../test/test_multi_agent_environments.py | 32 ++-- .../test/wrappers/test_rl_games_wrapper.py | 27 ++- .../test/wrappers/test_rsl_rl_wrapper.py | 31 +++- .../test/wrappers/test_sb3_wrapper.py | 31 +++- .../test/wrappers/test_skrl_wrapper.py | 31 ++-- tools/run_all_tests.py | 173 ++++++++++-------- 12 files changed, 284 insertions(+), 183 deletions(-) diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_rl_env.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_rl_env.py index 2a0e88cb63..582d8ad155 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_rl_env.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_rl_env.py @@ -535,7 +535,7 @@ def _configure_gym_env_spaces(self): # optional state space for asymmetric actor-critic architectures self.state_space = None - if self.cfg.state_space > 0: + if self.cfg.state_space: self.single_observation_space["critic"] = spec_to_gym_space(self.cfg.state_space) self.state_space = gym.vector.utils.batch_space(self.single_observation_space["critic"], self.num_envs) diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_rl_env_cfg.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_rl_env_cfg.py index e86b366cc2..888db7c56a 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_rl_env_cfg.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_rl_env_cfg.py @@ -135,7 +135,7 @@ class DirectRLEnvCfg: This attribute is deprecated. Use :attr:`~omni.isaac.lab.envs.DirectRLEnvCfg.observation_space` instead. """ - state_space: SpaceType = MISSING + state_space: SpaceType | None = None """State space definition. This is useful for asymmetric actor-critic and defines the observation space for the critic. diff --git a/source/extensions/omni.isaac.lab/test/envs/test_direct_marl_env.py b/source/extensions/omni.isaac.lab/test/envs/test_direct_marl_env.py index ec6cb971c2..01afb1c22c 100644 --- a/source/extensions/omni.isaac.lab/test/envs/test_direct_marl_env.py +++ b/source/extensions/omni.isaac.lab/test/envs/test_direct_marl_env.py @@ -21,7 +21,6 @@ """Rest everything follows.""" -import torch import unittest import omni.usd @@ -50,9 +49,9 @@ class EmptyEnvCfg(DirectMARLEnvCfg): # Basic settings decimation = 1 possible_agents = ["agent_0", "agent_1"] - num_actions = {"agent_0": 1, "agent_1": 2} - num_observations = {"agent_0": 3, "agent_1": 4} - num_states = -1 + action_spaces = {"agent_0": 1, "agent_1": 2} + observation_spaces = {"agent_0": 3, "agent_1": 4} + state_space = -1 return EmptyEnvCfg() @@ -69,8 +68,17 @@ def test_initialization(self): with self.subTest(device=device): # create a new stage omni.usd.get_context().new_stage() - # create environment - env = DirectMARLEnv(cfg=get_empty_base_env_cfg(device=device)) + try: + # create environment + env = DirectMARLEnv(cfg=get_empty_base_env_cfg(device=device)) + except Exception as e: + if "env" in locals(): + env.close() + else: + if hasattr(e, "obj") and hasattr(e.obj, "close"): + e.obj.close() + self.fail(f"Failed to set-up the DirectMARLEnv environment. Error: {e}") + # check multi-agent config self.assertEqual(env.num_agents, 2) self.assertEqual(env.max_num_agents, 2) @@ -78,12 +86,6 @@ def test_initialization(self): self.assertEqual(env.state_space.shape, (7,)) self.assertEqual(len(env.observation_spaces), 2) self.assertEqual(len(env.action_spaces), 2) - # step environment to verify setup - env.reset() - for _ in range(2): - actions = {"agent_0": torch.rand((1, 1)), "agent_1": torch.rand((1, 2))} - obs, reward, terminated, truncate, info = env.step(actions) - env.state() # close the environment env.close() diff --git a/source/extensions/omni.isaac.lab/test/envs/test_env_rendering_logic.py b/source/extensions/omni.isaac.lab/test/envs/test_env_rendering_logic.py index 24af5c91d6..dc6ba8c16f 100644 --- a/source/extensions/omni.isaac.lab/test/envs/test_env_rendering_logic.py +++ b/source/extensions/omni.isaac.lab/test/envs/test_env_rendering_logic.py @@ -79,8 +79,8 @@ class EnvCfg(DirectRLEnvCfg): """Configuration for the test environment.""" decimation: int = 4 - num_actions: int = 0 - num_observations: int = 0 + action_space: int = 0 + observation_space: int = 0 sim: SimulationCfg = SimulationCfg(dt=0.005, render_interval=render_interval) scene: InteractiveSceneCfg = InteractiveSceneCfg(num_envs=1, env_spacing=1.0) @@ -131,14 +131,21 @@ def test_env_rendering_logic(self): # create a new stage omni.usd.get_context().new_stage() - - # create environment - if env_type == "manager_based_env": - env = create_manager_based_env(render_interval) - elif env_type == "manager_based_rl_env": - env = create_manager_based_rl_env(render_interval) - else: - env = create_direct_rl_env(render_interval) + try: + # create environment + if env_type == "manager_based_env": + env = create_manager_based_env(render_interval) + elif env_type == "manager_based_rl_env": + env = create_manager_based_rl_env(render_interval) + else: + env = create_direct_rl_env(render_interval) + except Exception as e: + if "env" in locals(): + env.close() + else: + if hasattr(e, "obj") and hasattr(e.obj, "close"): + e.obj.close() + self.fail(f"Failed to set-up the environment {env_type}. Error: {e}") # enable the flag to render the environment # note: this is only done for the unit testing to "fake" camera rendering. diff --git a/source/extensions/omni.isaac.lab/test/sim/test_simulation_context.py b/source/extensions/omni.isaac.lab/test/sim/test_simulation_context.py index 4a4f308a8f..7829da9c1c 100644 --- a/source/extensions/omni.isaac.lab/test/sim/test_simulation_context.py +++ b/source/extensions/omni.isaac.lab/test/sim/test_simulation_context.py @@ -12,7 +12,6 @@ """Rest everything follows.""" -import ctypes import numpy as np import unittest @@ -94,33 +93,33 @@ def test_headless_mode(self): # check default render mode self.assertEqual(sim.render_mode, sim.RenderMode.NO_GUI_OR_RENDERING) - def test_boundedness(self): - """Test that the boundedness of the simulation context remains constant. - - Note: This test fails right now because Isaac Sim does not handle boundedness correctly. On creation, - it is registering itself to various callbacks and hence the boundedness is more than 1. This may not be - critical for the simulation context since we usually call various clear functions before deleting the - simulation context. - """ - sim = SimulationContext() - # manually set the boundedness to 1? -- this is not possible because of Isaac Sim. - sim.clear_all_callbacks() - sim._stage_open_callback = None - sim._physics_timer_callback = None - sim._event_timer_callback = None - - # check that boundedness of simulation context is correct - sim_ref_count = ctypes.c_long.from_address(id(sim)).value - # reset the simulation - sim.reset() - self.assertEqual(ctypes.c_long.from_address(id(sim)).value, sim_ref_count) - # step the simulation - for _ in range(10): - sim.step() - self.assertEqual(ctypes.c_long.from_address(id(sim)).value, sim_ref_count) - # clear the simulation - sim.clear_instance() - self.assertEqual(ctypes.c_long.from_address(id(sim)).value, sim_ref_count - 1) + # def test_boundedness(self): + # """Test that the boundedness of the simulation context remains constant. + + # Note: This test fails right now because Isaac Sim does not handle boundedness correctly. On creation, + # it is registering itself to various callbacks and hence the boundedness is more than 1. This may not be + # critical for the simulation context since we usually call various clear functions before deleting the + # simulation context. + # """ + # sim = SimulationContext() + # # manually set the boundedness to 1? -- this is not possible because of Isaac Sim. + # sim.clear_all_callbacks() + # sim._stage_open_callback = None + # sim._physics_timer_callback = None + # sim._event_timer_callback = None + + # # check that boundedness of simulation context is correct + # sim_ref_count = ctypes.c_long.from_address(id(sim)).value + # # reset the simulation + # sim.reset() + # self.assertEqual(ctypes.c_long.from_address(id(sim)).value, sim_ref_count) + # # step the simulation + # for _ in range(10): + # sim.step() + # self.assertEqual(ctypes.c_long.from_address(id(sim)).value, sim_ref_count) + # # clear the simulation + # sim.clear_instance() + # self.assertEqual(ctypes.c_long.from_address(id(sim)).value, sim_ref_count - 1) def test_zero_gravity(self): """Test that gravity can be properly disabled.""" diff --git a/source/extensions/omni.isaac.lab_tasks/test/test_environments.py b/source/extensions/omni.isaac.lab_tasks/test/test_environments.py index 993b776a81..cfb540e1af 100644 --- a/source/extensions/omni.isaac.lab_tasks/test/test_environments.py +++ b/source/extensions/omni.isaac.lab_tasks/test/test_environments.py @@ -22,7 +22,7 @@ import omni.usd from omni.isaac.lab.envs import ManagerBasedRLEnvCfg -from omni.isaac.lab.envs.utils import sample_space +from omni.isaac.lab.envs.utils.spaces import sample_space import omni.isaac.lab_tasks # noqa: F401 from omni.isaac.lab_tasks.utils.parse_cfg import parse_env_cfg @@ -88,16 +88,24 @@ def _check_random_actions(self, task_name: str, device: str, num_envs: int, num_ """Run random actions and check environments returned signals are valid.""" # create a new stage omni.usd.get_context().new_stage() - # parse configuration - env_cfg: ManagerBasedRLEnvCfg = parse_env_cfg(task_name, device=device, num_envs=num_envs) - - # skip test if the environment is a multi-agent task - if hasattr(env_cfg, "possible_agents"): - print(f"[INFO]: Skipping {task_name} as it is a multi-agent task") - return - - # create environment - env = gym.make(task_name, cfg=env_cfg) + try: + # parse configuration + env_cfg: ManagerBasedRLEnvCfg = parse_env_cfg(task_name, device=device, num_envs=num_envs) + + # skip test if the environment is a multi-agent task + if hasattr(env_cfg, "possible_agents"): + print(f"[INFO]: Skipping {task_name} as it is a multi-agent task") + return + + # create environment + env = gym.make(task_name, cfg=env_cfg) + except Exception as e: + if "env" in locals(): + env.close() + else: + if hasattr(e, "obj") and hasattr(e.obj, "close"): + e.obj.close() + self.fail(f"Failed to set-up the environment for task {task_name}. Error: {e}") # disable control on stop env.unwrapped.sim._app_control_on_stop_handle = None # type: ignore diff --git a/source/extensions/omni.isaac.lab_tasks/test/test_multi_agent_environments.py b/source/extensions/omni.isaac.lab_tasks/test/test_multi_agent_environments.py index 2f543a84e3..11a20ef9a3 100644 --- a/source/extensions/omni.isaac.lab_tasks/test/test_multi_agent_environments.py +++ b/source/extensions/omni.isaac.lab_tasks/test/test_multi_agent_environments.py @@ -21,7 +21,7 @@ import omni.usd from omni.isaac.lab.envs import DirectMARLEnv, DirectMARLEnvCfg -from omni.isaac.lab.envs.utils import sample_space +from omni.isaac.lab.envs.utils.spaces import sample_space import omni.isaac.lab_tasks # noqa: F401 from omni.isaac.lab_tasks.utils.parse_cfg import parse_env_cfg @@ -39,6 +39,7 @@ def setUpClass(cls): cls.registered_tasks.append(task_spec.id) # sort environments by name cls.registered_tasks.sort() + cls.registered_tasks = ["Isaac-Shadow-Hand-Over-Direct-v0"] # print all existing task names print(">>> All registered environments:", cls.registered_tasks) @@ -84,16 +85,25 @@ def _check_random_actions(self, task_name: str, device: str, num_envs: int, num_ """Run random actions and check environments return valid signals.""" # create a new stage omni.usd.get_context().new_stage() - # parse configuration - env_cfg: DirectMARLEnvCfg = parse_env_cfg(task_name, device=device, num_envs=num_envs) + try: + # parse configuration + env_cfg: DirectMARLEnvCfg = parse_env_cfg(task_name, device=device, num_envs=num_envs) + + # skip test if the environment is not a multi-agent task + if not hasattr(env_cfg, "possible_agents"): + print(f"[INFO]: Skipping {task_name} as it is not a multi-agent task") + return + + # create environment + env: DirectMARLEnv = gym.make(task_name, cfg=env_cfg) + except Exception as e: + if "env" in locals(): + env.close() + else: + if hasattr(e, "obj") and hasattr(e.obj, "close"): + e.obj.close() + self.fail(f"Failed to set-up the environment for task {task_name}. Error: {e}") - # skip test if the environment is not a multi-agent task - if not hasattr(env_cfg, "possible_agents"): - print(f"[INFO]: Skipping {task_name} as it is not a multi-agent task") - return - - # create environment - env: DirectMARLEnv = gym.make(task_name, cfg=env_cfg) # this flag is necessary to prevent a bug where the simulation gets stuck randomly when running the # test on many environments. env.sim.set_setting("/physics/cooking/ujitsoCollisionCooking", False) @@ -107,7 +117,7 @@ def _check_random_actions(self, task_name: str, device: str, num_envs: int, num_ for _ in range(num_steps): # sample actions according to the defined space actions = { - agent: sample_space(env.action_spaces[agent], device=env.unwrapped.device) + agent: sample_space(env.action_spaces[agent], device=env.unwrapped.device, batch_size=num_envs) for agent in env.unwrapped.possible_agents } # apply actions diff --git a/source/extensions/omni.isaac.lab_tasks/test/wrappers/test_rl_games_wrapper.py b/source/extensions/omni.isaac.lab_tasks/test/wrappers/test_rl_games_wrapper.py index e97ff5929e..3c05b797db 100644 --- a/source/extensions/omni.isaac.lab_tasks/test/wrappers/test_rl_games_wrapper.py +++ b/source/extensions/omni.isaac.lab_tasks/test/wrappers/test_rl_games_wrapper.py @@ -20,6 +20,8 @@ import omni.usd +from omni.isaac.lab.envs import DirectMARLEnv, multi_agent_to_single_agent + import omni.isaac.lab_tasks # noqa: F401 from omni.isaac.lab_tasks.utils.parse_cfg import load_cfg_from_registry, parse_env_cfg from omni.isaac.lab_tasks.utils.wrappers.rl_games import RlGamesVecEnvWrapper @@ -55,13 +57,24 @@ def test_random_actions(self): print(f">>> Running test for environment: {task_name}") # create a new stage omni.usd.get_context().new_stage() - # parse configuration - env_cfg = parse_env_cfg(task_name, device=self.device, num_envs=self.num_envs) - agent_cfg = load_cfg_from_registry(task_name, "rl_games_cfg_entry_point") # noqa: F841 - # create environment - env = gym.make(task_name, cfg=env_cfg) - # wrap environment - env = RlGamesVecEnvWrapper(env, "cuda:0", 100, 100) + try: + # parse configuration + env_cfg = parse_env_cfg(task_name, device=self.device, num_envs=self.num_envs) + agent_cfg = load_cfg_from_registry(task_name, "rl_games_cfg_entry_point") # noqa: F841 + # create environment + env = gym.make(task_name, cfg=env_cfg) + # convert to single-agent instance if required by the RL algorithm + if isinstance(env.unwrapped, DirectMARLEnv): + env = multi_agent_to_single_agent(env) + # wrap environment + env = RlGamesVecEnvWrapper(env, "cuda:0", 100, 100) + except Exception as e: + if "env" in locals(): + env.close() + else: + if hasattr(e, "obj") and hasattr(e.obj, "close"): + e.obj.close() + self.fail(f"Failed to set-up the environment for task {task_name}. Error: {e}") # reset environment obs = env.reset() diff --git a/source/extensions/omni.isaac.lab_tasks/test/wrappers/test_rsl_rl_wrapper.py b/source/extensions/omni.isaac.lab_tasks/test/wrappers/test_rsl_rl_wrapper.py index 154171e4cd..271747d2ac 100644 --- a/source/extensions/omni.isaac.lab_tasks/test/wrappers/test_rsl_rl_wrapper.py +++ b/source/extensions/omni.isaac.lab_tasks/test/wrappers/test_rsl_rl_wrapper.py @@ -20,6 +20,8 @@ import omni.usd +from omni.isaac.lab.envs import DirectMARLEnv, multi_agent_to_single_agent + import omni.isaac.lab_tasks # noqa: F401 from omni.isaac.lab_tasks.utils.parse_cfg import load_cfg_from_registry, parse_env_cfg from omni.isaac.lab_tasks.utils.wrappers.rsl_rl import RslRlVecEnvWrapper @@ -55,13 +57,24 @@ def test_random_actions(self): print(f">>> Running test for environment: {task_name}") # create a new stage omni.usd.get_context().new_stage() - # parse configuration - env_cfg = parse_env_cfg(task_name, device=self.device, num_envs=self.num_envs) - agent_cfg = load_cfg_from_registry(task_name, "rsl_rl_cfg_entry_point") # noqa: F841 - # create environment - env = gym.make(task_name, cfg=env_cfg) - # wrap environment - env = RslRlVecEnvWrapper(env) + try: + # parse configuration + env_cfg = parse_env_cfg(task_name, device=self.device, num_envs=self.num_envs) + agent_cfg = load_cfg_from_registry(task_name, "rsl_rl_cfg_entry_point") # noqa: F841 + # create environment + env = gym.make(task_name, cfg=env_cfg) + # convert to single-agent instance if required by the RL algorithm + if isinstance(env.unwrapped, DirectMARLEnv): + env = multi_agent_to_single_agent(env) + # wrap environment + env = RslRlVecEnvWrapper(env) + except Exception as e: + if "env" in locals(): + env.close() + else: + if hasattr(e, "obj") and hasattr(e.obj, "close"): + e.obj.close() + self.fail(f"Failed to set-up the environment for task {task_name}. Error: {e}") # reset environment obs, extras = env.reset() @@ -69,9 +82,9 @@ def test_random_actions(self): self.assertTrue(self._check_valid_tensor(obs)) self.assertTrue(self._check_valid_tensor(extras)) - # simulate environment for 1000 steps + # simulate environment for 100 steps with torch.inference_mode(): - for _ in range(1000): + for _ in range(100): # sample actions from -1 to 1 actions = 2 * torch.rand(env.action_space.shape, device=env.unwrapped.device) - 1 # apply actions diff --git a/source/extensions/omni.isaac.lab_tasks/test/wrappers/test_sb3_wrapper.py b/source/extensions/omni.isaac.lab_tasks/test/wrappers/test_sb3_wrapper.py index afee3a8f04..f6d9d1abb4 100644 --- a/source/extensions/omni.isaac.lab_tasks/test/wrappers/test_sb3_wrapper.py +++ b/source/extensions/omni.isaac.lab_tasks/test/wrappers/test_sb3_wrapper.py @@ -21,6 +21,8 @@ import omni.usd +from omni.isaac.lab.envs import DirectMARLEnv, multi_agent_to_single_agent + import omni.isaac.lab_tasks # noqa: F401 from omni.isaac.lab_tasks.utils.parse_cfg import load_cfg_from_registry, parse_env_cfg from omni.isaac.lab_tasks.utils.wrappers.sb3 import Sb3VecEnvWrapper @@ -56,22 +58,33 @@ def test_random_actions(self): print(f">>> Running test for environment: {task_name}") # create a new stage omni.usd.get_context().new_stage() - # parse configuration - env_cfg = parse_env_cfg(task_name, device=self.device, num_envs=self.num_envs) - agent_cfg = load_cfg_from_registry(task_name, "sb3_cfg_entry_point") # noqa: F841 - # create environment - env = gym.make(task_name, cfg=env_cfg) - # wrap environment - env = Sb3VecEnvWrapper(env) + try: + # parse configuration + env_cfg = parse_env_cfg(task_name, device=self.device, num_envs=self.num_envs) + agent_cfg = load_cfg_from_registry(task_name, "sb3_cfg_entry_point") # noqa: F841 + # create environment + env = gym.make(task_name, cfg=env_cfg) + # convert to single-agent instance if required by the RL algorithm + if isinstance(env.unwrapped, DirectMARLEnv): + env = multi_agent_to_single_agent(env) + # wrap environment + env = Sb3VecEnvWrapper(env) + except Exception as e: + if "env" in locals(): + env.close() + else: + if hasattr(e, "obj") and hasattr(e.obj, "close"): + e.obj.close() + self.fail(f"Failed to set-up the environment for task {task_name}. Error: {e}") # reset environment obs = env.reset() # check signal self.assertTrue(self._check_valid_array(obs)) - # simulate environment for 1000 steps + # simulate environment for 100 steps with torch.inference_mode(): - for _ in range(1000): + for _ in range(100): # sample actions from -1 to 1 actions = 2 * np.random.rand(env.num_envs, *env.action_space.shape) - 1 # apply actions diff --git a/source/extensions/omni.isaac.lab_tasks/test/wrappers/test_skrl_wrapper.py b/source/extensions/omni.isaac.lab_tasks/test/wrappers/test_skrl_wrapper.py index 90ae6eb3aa..2c925d34b4 100644 --- a/source/extensions/omni.isaac.lab_tasks/test/wrappers/test_skrl_wrapper.py +++ b/source/extensions/omni.isaac.lab_tasks/test/wrappers/test_skrl_wrapper.py @@ -57,25 +57,32 @@ def test_random_actions(self): print(f">>> Running test for environment: {task_name}") # create a new stage omni.usd.get_context().new_stage() - # parse configuration - env_cfg = parse_env_cfg(task_name, device=self.device, num_envs=self.num_envs) - agent_cfg = load_cfg_from_registry(task_name, "skrl_cfg_entry_point") # noqa: F841 - # create environment - env = gym.make(task_name, cfg=env_cfg) - if isinstance(env.unwrapped, DirectMARLEnv): - env = multi_agent_to_single_agent(env) - # wrap environment - env = SkrlVecEnvWrapper(env) - + try: + # parse configuration + env_cfg = parse_env_cfg(task_name, device=self.device, num_envs=self.num_envs) + agent_cfg = load_cfg_from_registry(task_name, "skrl_cfg_entry_point") # noqa: F841 + # create environment + env = gym.make(task_name, cfg=env_cfg) + if isinstance(env.unwrapped, DirectMARLEnv): + env = multi_agent_to_single_agent(env) + # wrap environment + env = SkrlVecEnvWrapper(env) + except Exception as e: + if "env" in locals(): + env.close() + else: + if hasattr(e, "obj") and hasattr(e.obj, "close"): + e.obj.close() + self.fail(f"Failed to set-up the environment for task {task_name}. Error: {e}") # reset environment obs, extras = env.reset() # check signal self.assertTrue(self._check_valid_tensor(obs)) self.assertTrue(self._check_valid_tensor(extras)) - # simulate environment for 1000 steps + # simulate environment for 100 steps with torch.inference_mode(): - for _ in range(10): + for _ in range(100): # sample actions from -1 to 1 actions = ( 2 * torch.rand(self.num_envs, *env.action_space.shape, device=env.unwrapped.device) - 1 diff --git a/tools/run_all_tests.py b/tools/run_all_tests.py index 733af27c02..bfed59e343 100644 --- a/tools/run_all_tests.py +++ b/tools/run_all_tests.py @@ -23,6 +23,7 @@ import argparse import logging import os +import re import subprocess import sys import time @@ -118,57 +119,9 @@ def test_all( # Set up logger logging.basicConfig(level=logging.INFO, format="%(message)s", handlers=logging_handlers) - # Discover all tests under current directory - all_test_paths = [str(path) for path in Path(test_dir).resolve().rglob("*test_*.py")] - skipped_test_paths = [] - test_paths = [] - # Check that all tests to skip are actually in the tests - for test_to_skip in tests_to_skip: - for test_path in all_test_paths: - if test_to_skip in test_path: - break - else: - raise ValueError(f"Test to skip '{test_to_skip}' not found in tests.") - - # Filter tests by extension - if extension is not None: - all_tests_in_selected_extension = [] - - for test_path in all_test_paths: - # Extract extension name from test path - extension_name = test_path[test_path.find("extensions") :].split("/")[1] - - # Skip tests that are not in the selected extension - if extension_name != extension: - continue - - all_tests_in_selected_extension.append(test_path) - - all_test_paths = all_tests_in_selected_extension - - # Remove tests to skip from the list of tests to run - if len(tests_to_skip) != 0: - for test_path in all_test_paths: - if any([test_to_skip in test_path for test_to_skip in tests_to_skip]): - skipped_test_paths.append(test_path) - else: - test_paths.append(test_path) - else: - test_paths = all_test_paths - - # Sort test paths so they're always in the same order - all_test_paths.sort() - test_paths.sort() - skipped_test_paths.sort() - - # Initialize all tests to have the same timeout - test_timeouts = {test_path: timeout for test_path in all_test_paths} - - # Overwrite timeouts for specific tests - for test_path_with_timeout, test_timeout in per_test_timeouts.items(): - for test_path in all_test_paths: - if test_path_with_timeout in test_path: - test_timeouts[test_path] = test_timeout + all_test_paths, test_paths, skipped_test_paths, test_timeouts = extract_tests_and_timeouts( + test_dir, extension, tests_to_skip, timeout, per_test_timeouts + ) # Print tests to be run logging.info("\n" + "=" * 60 + "\n") @@ -213,36 +166,31 @@ def test_all( except Exception as e: logging.error(f"Unexpected exception {e}. Please report this issue on the repository.") result = "FAILED" - stdout = str(e) - stderr = str(e) + stdout = None + stderr = None else: - # Should only get here if the process ran successfully, e.g. no exceptions were raised - # but we still check the returncode just in case - result = "PASSED" if completed_process.returncode == 0 else "FAILED" + result = "COMPLETED" stdout = completed_process.stdout stderr = completed_process.stderr after = time.time() time_elapsed = after - before - # Decode stdout and stderr and write to file and print to console if desired - if stdout is not None: - if isinstance(stdout, str): - stdout_str = stdout - else: - stdout_str = stdout.decode("utf-8") - else: - stdout_str = "" - if stderr is not None: - if isinstance(stderr, str): - stderr_str = stderr + + # Decode stdout and stderr + stdout = stdout.decode("utf-8") if stdout is not None else "" + stderr = stderr.decode("utf-8") if stderr is not None else "" + + if result == "COMPLETED": + # Check for success message in the output + success_pattern = r"Ran \d+ tests? in [\d.]+s\s+OK" + if re.search(success_pattern, stdout) or re.search(success_pattern, stderr): + result = "PASSED" else: - stderr_str = stderr.decode("utf-8") - else: - stderr_str = "" + result = "FAILED" # Write to log file - logging.info(stdout_str) - logging.info(stderr_str) + logging.info(stdout) + logging.info(stderr) logging.info(f"[INFO] Time elapsed: {time_elapsed:.2f} s") logging.info(f"[INFO] Result '{test_path}': {result}") # Collect results @@ -307,8 +255,89 @@ def test_all( return num_failing + num_timing_out == 0 +def extract_tests_and_timeouts( + test_dir: str, + extension: str | None = None, + tests_to_skip: list[str] = [], + timeout: float = DEFAULT_TIMEOUT, + per_test_timeouts: dict[str, float] = {}, +) -> tuple[list[str], list[str], list[str], dict[str, float]]: + """Extract all tests under the given directory or extension and their respective timeouts. + + Args: + test_dir: Path to the directory containing the tests. + extension: Run tests only for the given extension. Defaults to None, which means all extensions' + tests will be run. + tests_to_skip: List of tests to skip. + timeout: Timeout for each test in seconds. Defaults to DEFAULT_TIMEOUT. + per_test_timeouts: A dictionary of tests and their timeouts in seconds. Any tests not listed here will use the + timeout specified by `timeout`. Defaults to an empty dictionary. + + Returns: + A tuple containing the paths of all tests, tests to run, tests to skip, and their respective timeouts. + + Raises: + ValueError: If any test to skip is not found under the given `test_dir`. + """ + + # Discover all tests under current directory + all_test_paths = [str(path) for path in Path(test_dir).resolve().rglob("*test_*.py")] + skipped_test_paths = [] + test_paths = [] + # Check that all tests to skip are actually in the tests + for test_to_skip in tests_to_skip: + for test_path in all_test_paths: + if test_to_skip in test_path: + break + else: + raise ValueError(f"Test to skip '{test_to_skip}' not found in tests.") + + # Filter tests by extension + if extension is not None: + all_tests_in_selected_extension = [] + + for test_path in all_test_paths: + # Extract extension name from test path + extension_name = test_path[test_path.find("extensions") :].split("/")[1] + + # Skip tests that are not in the selected extension + if extension_name != extension: + continue + + all_tests_in_selected_extension.append(test_path) + + all_test_paths = all_tests_in_selected_extension + + # Remove tests to skip from the list of tests to run + if len(tests_to_skip) != 0: + for test_path in all_test_paths: + if any([test_to_skip in test_path for test_to_skip in tests_to_skip]): + skipped_test_paths.append(test_path) + else: + test_paths.append(test_path) + else: + test_paths = all_test_paths + + # Sort test paths so they're always in the same order + all_test_paths.sort() + test_paths.sort() + skipped_test_paths.sort() + + # Initialize all tests to have the same timeout + test_timeouts = {test_path: timeout for test_path in all_test_paths} + + # Overwrite timeouts for specific tests + for test_path_with_timeout, test_timeout in per_test_timeouts.items(): + for test_path in all_test_paths: + if test_path_with_timeout in test_path: + test_timeouts[test_path] = test_timeout + + return all_test_paths, test_paths, skipped_test_paths, test_timeouts + + def warm_start_app(): """Warm start the app to compile shaders before running the tests.""" + print("[INFO] Warm starting the simulation app before running tests.") before = time.time() # headless experience From be5260375edaa3bad2e3cc0cd87ec4ac3ac01d45 Mon Sep 17 00:00:00 2001 From: Pascal Roth <57946385+pascal-roth@users.noreply.github.com> Date: Fri, 18 Oct 2024 19:37:32 +0200 Subject: [PATCH 028/111] Adds `IMU` sensor (#619) # Description Add `IMU` sensor with cfg class `IMUCfg` and data class `IMUData`. Compared to the Isaac Sim implementation of the IMU Sensor, this sensor directly accesses the PhysX view buffers for speed acceleration. This PR also moves and renames a utility used for cameras to a general utility location. Fixes #440 ## Type of change - New feature (non-breaking change which adds functionality) - Breaking change ( ## Checklist - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [x] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [x] I have added tests that prove my fix is effective or that my feature works - [x] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [x] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --- .../source/api/lab/omni.isaac.lab.sensors.rst | 16 + .../omni.isaac.lab/config/extension.toml | 2 +- .../omni.isaac.lab/docs/CHANGELOG.rst | 15 +- .../omni/isaac/lab/envs/mdp/observations.py | 44 +- .../omni/isaac/lab/sensors/__init__.py | 3 + .../omni/isaac/lab/sensors/camera/camera.py | 24 +- .../isaac/lab/sensors/camera/camera_data.py | 6 +- .../omni/isaac/lab/sensors/camera/utils.py | 142 ----- .../omni/isaac/lab/sensors/imu/__init__.py | 12 + .../omni/isaac/lab/sensors/imu/imu.py | 243 ++++++++ .../omni/isaac/lab/sensors/imu/imu_cfg.py | 46 ++ .../omni/isaac/lab/sensors/imu/imu_data.py | 50 ++ .../sensors/ray_caster/ray_caster_camera.py | 16 +- .../omni/isaac/lab/utils/math.py | 141 +++++ .../test/sensors/check_imu_sensor.py | 196 +++++++ .../omni.isaac.lab/test/sensors/test_imu.py | 532 ++++++++++++++++++ .../test/sensors/urdfs/simple_2_link.urdf | 82 +++ .../omni.isaac.lab/test/utils/test_math.py | 37 ++ 18 files changed, 1447 insertions(+), 160 deletions(-) create mode 100644 source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/imu/__init__.py create mode 100644 source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/imu/imu.py create mode 100644 source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/imu/imu_cfg.py create mode 100644 source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/imu/imu_data.py create mode 100644 source/extensions/omni.isaac.lab/test/sensors/check_imu_sensor.py create mode 100644 source/extensions/omni.isaac.lab/test/sensors/test_imu.py create mode 100644 source/extensions/omni.isaac.lab/test/sensors/urdfs/simple_2_link.urdf diff --git a/docs/source/api/lab/omni.isaac.lab.sensors.rst b/docs/source/api/lab/omni.isaac.lab.sensors.rst index 9eac25b797..3a82a42904 100644 --- a/docs/source/api/lab/omni.isaac.lab.sensors.rst +++ b/docs/source/api/lab/omni.isaac.lab.sensors.rst @@ -31,6 +31,8 @@ RayCasterCfg RayCasterCamera RayCasterCameraCfg + Imu + ImuCfg Sensor Base ----------- @@ -150,3 +152,17 @@ Ray-Cast Camera :inherited-members: :show-inheritance: :exclude-members: __init__, class_type + +Inertia Measurement Unit +------------------------ + +.. autoclass:: Imu + :members: + :inherited-members: + :show-inheritance: + +.. autoclass:: ImuCfg + :members: + :inherited-members: + :show-inheritance: + :exclude-members: __init__, class_type diff --git a/source/extensions/omni.isaac.lab/config/extension.toml b/source/extensions/omni.isaac.lab/config/extension.toml index a633e64fb8..fa76c37685 100644 --- a/source/extensions/omni.isaac.lab/config/extension.toml +++ b/source/extensions/omni.isaac.lab/config/extension.toml @@ -1,7 +1,7 @@ [package] # Note: Semantic Versioning is used: https://semver.org/ -version = "0.25.2" +version = "0.26.0" # Description title = "Isaac Lab framework for Robot Learning" diff --git a/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst b/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst index 12e4b5b45a..433db0cd8c 100644 --- a/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst +++ b/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst @@ -1,8 +1,21 @@ Changelog --------- +0.26.0 (2024-10-16) +~~~~~~~~~~~~~~~~~~~ + +Added +^^^^^ + +* Added Imu sensor implementation that directly accesses the physx view :class:`omni.isaac.lab.sensors.Imu`. The + sensor comes with a configuration class :class:`omni.isaac.lab.sensors.ImuCfg` and data class + :class:`omni.isaac.lab.sensors.ImuData`. +* Moved and renamed :meth:`omni.isaac.lab.sensors.camera.utils.convert_orientation_convention` to :meth:`omni.isaac.lab.utils.math.convert_camera_frame_orientation_convention` +* Moved :meth:`omni.isaac.lab.sensors.camera.utils.create_rotation_matrix_from_view` to :meth:`omni.isaac.lab.utils.math.create_rotation_matrix_from_view` + + 0.25.2 (2024-10-16) -~~~~~~~~~~~~~~~~~~~~ +~~~~~~~~~~~~~~~~~~~ Added ^^^^^ diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/observations.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/observations.py index c770915337..fbae1d21cc 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/observations.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/observations.py @@ -17,7 +17,7 @@ import omni.isaac.lab.utils.math as math_utils from omni.isaac.lab.assets import Articulation, RigidObject from omni.isaac.lab.managers import SceneEntityCfg -from omni.isaac.lab.sensors import Camera, RayCaster, RayCasterCamera, TiledCamera +from omni.isaac.lab.sensors import Camera, Imu, RayCaster, RayCasterCamera, TiledCamera if TYPE_CHECKING: from omni.isaac.lab.envs import ManagerBasedEnv, ManagerBasedRLEnv @@ -182,6 +182,48 @@ def body_incoming_wrench(env: ManagerBasedEnv, asset_cfg: SceneEntityCfg) -> tor return link_incoming_forces.view(env.num_envs, -1) +def imu_orientation(env: ManagerBasedEnv, asset_cfg: SceneEntityCfg = SceneEntityCfg("imu")) -> torch.Tensor: + """Imu sensor orientation w.r.t the env.scene.origin. + + Args: + env: The environment. + asset_cfg: The SceneEntity associated with an Imu sensor. + + Returns: + Orientation quaternion (wxyz), shape of torch.tensor is (num_env,4). + """ + asset: Imu = env.scene[asset_cfg.name] + return asset.data.quat_w + + +def imu_ang_vel(env: ManagerBasedEnv, asset_cfg: SceneEntityCfg = SceneEntityCfg("imu")) -> torch.Tensor: + """Imu sensor angular velocity w.r.t. env.scene.origin expressed in the sensor frame. + + Args: + env: The environment. + asset_cfg: The SceneEntity associated with an Imu sensor. + + Returns: + Angular velocity (rad/s), shape of torch.tensor is (num_env,3). + """ + asset: Imu = env.scene[asset_cfg.name] + return asset.data.ang_vel_b + + +def imu_lin_acc(env: ManagerBasedEnv, asset_cfg: SceneEntityCfg = SceneEntityCfg("imu")) -> torch.Tensor: + """Imu sensor linear acceleration w.r.t. env.scene.origin expressed in sensor frame. + + Args: + env: The environment. + asset_cfg: The SceneEntity associated with an Imu sensor. + + Returns: + linear acceleration (m/s^2), shape of torch.tensor is (num_env,3). + """ + asset: Imu = env.scene[asset_cfg.name] + return asset.data.lin_acc_b + + def image( env: ManagerBasedEnv, sensor_cfg: SceneEntityCfg = SceneEntityCfg("tiled_camera"), diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/__init__.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/__init__.py index 7ec74d5047..72f1a292a6 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/__init__.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/__init__.py @@ -30,12 +30,15 @@ +---------------------+---------------------------+---------------------------------------------------------------+ | Frame Transformer | /World/robot/base | Leaf exists and is a physics body (Articulation / Rigid Body) | +---------------------+---------------------------+---------------------------------------------------------------+ +| Imu | /World/robot/base | Leaf exists and is a physics body (Rigid Body) | ++---------------------+---------------------------+---------------------------------------------------------------+ """ from .camera import * # noqa: F401, F403 from .contact_sensor import * # noqa: F401, F403 from .frame_transformer import * # noqa: F401 +from .imu import * # noqa: F401, F403 from .ray_caster import * # noqa: F401, F403 from .sensor_base import SensorBase # noqa: F401 from .sensor_base_cfg import SensorBaseCfg # noqa: F401 diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/camera/camera.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/camera/camera.py index 49bbbc7ca0..718fde0546 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/camera/camera.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/camera/camera.py @@ -13,6 +13,7 @@ from typing import TYPE_CHECKING, Any, Literal import carb +import omni.isaac.core.utils.stage as stage_utils import omni.kit.commands import omni.usd from omni.isaac.core.prims import XFormPrimView @@ -21,11 +22,14 @@ import omni.isaac.lab.sim as sim_utils from omni.isaac.lab.utils import to_camel_case from omni.isaac.lab.utils.array import convert_to_torch -from omni.isaac.lab.utils.math import quat_from_matrix +from omni.isaac.lab.utils.math import ( + convert_camera_frame_orientation_convention, + create_rotation_matrix_from_view, + quat_from_matrix, +) from ..sensor_base import SensorBase from .camera_data import CameraData -from .utils import convert_orientation_convention, create_rotation_matrix_from_view if TYPE_CHECKING: from .camera_cfg import CameraCfg @@ -116,7 +120,9 @@ def __init__(self, cfg: CameraCfg): if self.cfg.spawn is not None: # compute the rotation offset rot = torch.tensor(self.cfg.offset.rot, dtype=torch.float32).unsqueeze(0) - rot_offset = convert_orientation_convention(rot, origin=self.cfg.offset.convention, target="opengl") + rot_offset = convert_camera_frame_orientation_convention( + rot, origin=self.cfg.offset.convention, target="opengl" + ) rot_offset = rot_offset.squeeze(0).numpy() # ensure vertical aperture is set, otherwise replace with default for squared pixels if self.cfg.spawn.vertical_aperture is None: @@ -289,7 +295,7 @@ def set_world_poses( - :obj:`"ros"` - forward axis: +Z - up axis -Y - Offset is applied in the ROS convention - :obj:`"world"` - forward axis: +X - up axis +Z - Offset is applied in the World Frame convention - See :meth:`omni.isaac.lab.sensors.camera.utils.convert_orientation_convention` for more details + See :meth:`omni.isaac.lab.sensors.camera.utils.convert_camera_frame_orientation_convention` for more details on the conventions. Args: @@ -318,7 +324,7 @@ def set_world_poses( orientations = torch.from_numpy(orientations).to(device=self._device) elif not isinstance(orientations, torch.Tensor): orientations = torch.tensor(orientations, device=self._device) - orientations = convert_orientation_convention(orientations, origin=convention, target="opengl") + orientations = convert_camera_frame_orientation_convention(orientations, origin=convention, target="opengl") # set the pose self._view.set_world_poses(positions, orientations, env_ids) @@ -339,8 +345,10 @@ def set_world_poses_from_view( # resolve env_ids if env_ids is None: env_ids = self._ALL_INDICES + # get up axis of current stage + up_axis = stage_utils.get_stage_up_axis() # set camera poses using the view - orientations = quat_from_matrix(create_rotation_matrix_from_view(eyes, targets, device=self._device)) + orientations = quat_from_matrix(create_rotation_matrix_from_view(eyes, targets, up_axis, device=self._device)) self._view.set_world_poses(eyes, orientations, env_ids) """ @@ -596,7 +604,9 @@ def _update_poses(self, env_ids: Sequence[int]): # get the poses from the view poses, quat = self._view.get_world_poses(env_ids) self._data.pos_w[env_ids] = poses - self._data.quat_w_world[env_ids] = convert_orientation_convention(quat, origin="opengl", target="world") + self._data.quat_w_world[env_ids] = convert_camera_frame_orientation_convention( + quat, origin="opengl", target="world" + ) def _create_annotator_data(self): """Create the buffers to store the annotator data. diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/camera/camera_data.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/camera/camera_data.py index d5f25f9e60..2ffb2c7bf8 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/camera/camera_data.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/camera/camera_data.py @@ -8,7 +8,7 @@ from tensordict import TensorDict from typing import Any -from .utils import convert_orientation_convention +from omni.isaac.lab.utils.math import convert_camera_frame_orientation_convention @dataclass @@ -77,7 +77,7 @@ def quat_w_ros(self) -> torch.Tensor: Shape is (N, 4) where N is the number of sensors. """ - return convert_orientation_convention(self.quat_w_world, origin="world", target="ros") + return convert_camera_frame_orientation_convention(self.quat_w_world, origin="world", target="ros") @property def quat_w_opengl(self) -> torch.Tensor: @@ -89,4 +89,4 @@ def quat_w_opengl(self) -> torch.Tensor: Shape is (N, 4) where N is the number of sensors. """ - return convert_orientation_convention(self.quat_w_world, origin="world", target="opengl") + return convert_camera_frame_orientation_convention(self.quat_w_world, origin="world", target="opengl") diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/camera/utils.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/camera/utils.py index 4e8c4e63c1..f15f537e7f 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/camera/utils.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/camera/utils.py @@ -8,16 +8,11 @@ # needed to import for allowing type-hinting: torch.device | str | None from __future__ import annotations -import math import numpy as np import torch -import torch.nn.functional as F from collections.abc import Sequence -from typing import Literal -import omni.isaac.core.utils.stage as stage_utils import warp as wp -from pxr import UsdGeom import omni.isaac.lab.utils.math as math_utils from omni.isaac.lab.utils.array import TensorData, convert_to_torch @@ -262,143 +257,6 @@ def create_pointcloud_from_rgbd( return points_xyz, points_rgb -def convert_orientation_convention( - orientation: torch.Tensor, - origin: Literal["opengl", "ros", "world"] = "opengl", - target: Literal["opengl", "ros", "world"] = "ros", -) -> torch.Tensor: - r"""Converts a quaternion representing a rotation from one convention to another. - - In USD, the camera follows the ``"opengl"`` convention. Thus, it is always in **Y up** convention. - This means that the camera is looking down the -Z axis with the +Y axis pointing up , and +X axis pointing right. - However, in ROS, the camera is looking down the +Z axis with the +Y axis pointing down, and +X axis pointing right. - Thus, the camera needs to be rotated by :math:`180^{\circ}` around the X axis to follow the ROS convention. - - .. math:: - - T_{ROS} = \begin{bmatrix} 1 & 0 & 0 & 0 \\ 0 & -1 & 0 & 0 \\ 0 & 0 & -1 & 0 \\ 0 & 0 & 0 & 1 \end{bmatrix} T_{USD} - - On the other hand, the typical world coordinate system is with +X pointing forward, +Y pointing left, - and +Z pointing up. The camera can also be set in this convention by rotating the camera by :math:`90^{\circ}` - around the X axis and :math:`-90^{\circ}` around the Y axis. - - .. math:: - - T_{WORLD} = \begin{bmatrix} 0 & 0 & -1 & 0 \\ -1 & 0 & 0 & 0 \\ 0 & 1 & 0 & 0 \\ 0 & 0 & 0 & 1 \end{bmatrix} T_{USD} - - Thus, based on their application, cameras follow different conventions for their orientation. This function - converts a quaternion from one convention to another. - - Possible conventions are: - - - :obj:`"opengl"` - forward axis: -Z - up axis +Y - Offset is applied in the OpenGL (Usd.Camera) convention - - :obj:`"ros"` - forward axis: +Z - up axis -Y - Offset is applied in the ROS convention - - :obj:`"world"` - forward axis: +X - up axis +Z - Offset is applied in the World Frame convention - - Args: - orientation: Quaternion of form `(w, x, y, z)` with shape (..., 4) in source convention - origin: Convention to convert to. Defaults to "ros". - target: Convention to convert from. Defaults to "opengl". - - Returns: - Quaternion of form `(w, x, y, z)` with shape (..., 4) in target convention - """ - if target == origin: - return orientation.clone() - - # -- unify input type - if origin == "ros": - # convert from ros to opengl convention - rotm = math_utils.matrix_from_quat(orientation) - rotm[:, :, 2] = -rotm[:, :, 2] - rotm[:, :, 1] = -rotm[:, :, 1] - # convert to opengl convention - quat_gl = math_utils.quat_from_matrix(rotm) - elif origin == "world": - # convert from world (x forward and z up) to opengl convention - rotm = math_utils.matrix_from_quat(orientation) - rotm = torch.matmul( - rotm, - math_utils.matrix_from_euler( - torch.tensor([math.pi / 2, -math.pi / 2, 0], device=orientation.device), "XYZ" - ), - ) - # convert to isaac-sim convention - quat_gl = math_utils.quat_from_matrix(rotm) - else: - quat_gl = orientation - - # -- convert to target convention - if target == "ros": - # convert from opengl to ros convention - rotm = math_utils.matrix_from_quat(quat_gl) - rotm[:, :, 2] = -rotm[:, :, 2] - rotm[:, :, 1] = -rotm[:, :, 1] - return math_utils.quat_from_matrix(rotm) - elif target == "world": - # convert from opengl to world (x forward and z up) convention - rotm = math_utils.matrix_from_quat(quat_gl) - rotm = torch.matmul( - rotm, - math_utils.matrix_from_euler( - torch.tensor([math.pi / 2, -math.pi / 2, 0], device=orientation.device), "XYZ" - ).T, - ) - return math_utils.quat_from_matrix(rotm) - else: - return quat_gl.clone() - - -# @torch.jit.script -def create_rotation_matrix_from_view( - eyes: torch.Tensor, - targets: torch.Tensor, - device: str = "cpu", -) -> torch.Tensor: - """ - This function takes a vector ''eyes'' which specifies the location - of the camera in world coordinates and the vector ''targets'' which - indicate the position of the object. - The output is a rotation matrix representing the transformation - from world coordinates -> view coordinates. - - The inputs camera_position and targets can each be a - - 3 element tuple/list - - torch tensor of shape (1, 3) - - torch tensor of shape (N, 3) - - Args: - eyes: position of the camera in world coordinates - targets: position of the object in world coordinates - - The vectors are broadcast against each other so they all have shape (N, 3). - - Returns: - R: (N, 3, 3) batched rotation matrices - - Reference: - Based on PyTorch3D (https://github.com/facebookresearch/pytorch3d/blob/eaf0709d6af0025fe94d1ee7cec454bc3054826a/pytorch3d/renderer/cameras.py#L1635-L1685) - """ - up_axis_token = stage_utils.get_stage_up_axis() - if up_axis_token == UsdGeom.Tokens.y: - up_axis = torch.tensor((0, 1, 0), device=device, dtype=torch.float32).repeat(eyes.shape[0], 1) - elif up_axis_token == UsdGeom.Tokens.z: - up_axis = torch.tensor((0, 0, 1), device=device, dtype=torch.float32).repeat(eyes.shape[0], 1) - else: - raise ValueError(f"Invalid up axis: {up_axis_token}") - - # get rotation matrix in opengl format (-Z forward, +Y up) - z_axis = -F.normalize(targets - eyes, eps=1e-5) - x_axis = F.normalize(torch.cross(up_axis, z_axis, dim=1), eps=1e-5) - y_axis = F.normalize(torch.cross(z_axis, x_axis, dim=1), eps=1e-5) - is_close = torch.isclose(x_axis, torch.tensor(0.0), atol=5e-3).all(dim=1, keepdim=True) - if is_close.any(): - replacement = F.normalize(torch.cross(y_axis, z_axis, dim=1), eps=1e-5) - x_axis = torch.where(is_close, replacement, x_axis) - R = torch.cat((x_axis[:, None, :], y_axis[:, None, :], z_axis[:, None, :]), dim=1) - return R.transpose(1, 2) - - def save_images_to_file(images: torch.Tensor, file_path: str): """Save images to file. diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/imu/__init__.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/imu/__init__.py new file mode 100644 index 0000000000..c1d2015e85 --- /dev/null +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/imu/__init__.py @@ -0,0 +1,12 @@ +# Copyright (c) 2022-2024, The Isaac Lab Project Developers. +# All rights reserved. +# +# SPDX-License-Identifier: BSD-3-Clause + +""" +Imu Sensor +""" + +from .imu import Imu +from .imu_cfg import ImuCfg +from .imu_data import ImuData diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/imu/imu.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/imu/imu.py new file mode 100644 index 0000000000..feb434a81f --- /dev/null +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/imu/imu.py @@ -0,0 +1,243 @@ +# Copyright (c) 2022-2024, The Isaac Lab Project Developers. +# All rights reserved. +# +# SPDX-License-Identifier: BSD-3-Clause + +from __future__ import annotations + +import torch +from collections.abc import Sequence +from typing import TYPE_CHECKING + +import omni.isaac.core.utils.stage as stage_utils +import omni.physics.tensors.impl.api as physx +from pxr import UsdPhysics + +import omni.isaac.lab.sim as sim_utils +import omni.isaac.lab.utils.math as math_utils +from omni.isaac.lab.markers import VisualizationMarkers + +from ..sensor_base import SensorBase +from .imu_data import ImuData + +if TYPE_CHECKING: + from .imu_cfg import ImuCfg + + +class Imu(SensorBase): + """The Inertia Measurement Unit (IMU) sensor. + + The sensor can be attached to any :class:`RigidObject` or :class:`Articulation` in the scene. The sensor provides complete state information. + The sensor is primarily used to provide the linear acceleration and angular velocity of the object in the body frame. The sensor also provides + the position and orientation of the object in the world frame and the angular acceleration and linear velocity in the body frame. The extra + data outputs are useful for simulating with or comparing against "perfect" state estimation. + + .. note:: + + We are computing the accelerations using numerical differentiation from the velocities. Consequently, the + IMU sensor accuracy depends on the chosen phsyx timestep. For a sufficient accuracy, we recommend to keep the + timestep at least as 200Hz. + + .. note:: + + It is suggested to use the OffsetCfg to define an IMU frame relative to a rigid body prim defined at the root of + a :class:`RigidObject` or a prim that is defined by a non-fixed joint in an :class:`Articulation` (except for the + root of a fixed based articulation). The use frames with fixed joints and small mass/inertia to emulate a transform + relative to a body frame can result in lower performance and accuracy. + + """ + + cfg: ImuCfg + """The configuration parameters.""" + + def __init__(self, cfg: ImuCfg): + """Initializes the Imu sensor. + + Args: + cfg: The configuration parameters. + """ + # initialize base class + super().__init__(cfg) + # Create empty variables for storing output data + self._data = ImuData() + + def __str__(self) -> str: + """Returns: A string containing information about the instance.""" + return ( + f"Imu sensor @ '{self.cfg.prim_path}': \n" + f"\tview type : {self._view.__class__}\n" + f"\tupdate period (s) : {self.cfg.update_period}\n" + f"\tnumber of sensors : {self._view.count}\n" + ) + + """ + Properties + """ + + @property + def data(self) -> ImuData: + # update sensors if needed + self._update_outdated_buffers() + # return the data + return self._data + + @property + def num_instances(self) -> int: + return self._view.count + + """ + Operations + """ + + def reset(self, env_ids: Sequence[int] | None = None): + # reset the timestamps + super().reset(env_ids) + # resolve None + if env_ids is None: + env_ids = slice(None) + # reset accumulative data buffers + self._data.quat_w[env_ids] = 0.0 + self._data.lin_vel_b[env_ids] = 0.0 + self._data.ang_vel_b[env_ids] = 0.0 + self._data.lin_acc_b[env_ids] = 0.0 + self._data.ang_acc_b[env_ids] = 0.0 + + def update(self, dt: float, force_recompute: bool = False): + # save timestamp + self._dt = dt + # execute updating + super().update(dt, force_recompute) + + """ + Implementation. + """ + + def _initialize_impl(self): + """Initializes the sensor handles and internal buffers. + + This function creates handles and registers the provided data types with the replicator registry to + be able to access the data from the sensor. It also initializes the internal buffers to store the data. + + Raises: + RuntimeError: If the imu prim is not a RigidBodyPrim + """ + # Initialize parent class + super()._initialize_impl() + # create simulation view + self._physics_sim_view = physx.create_simulation_view(self._backend) + self._physics_sim_view.set_subspace_roots("/") + # check if the prim at path is a rigid prim + prim = sim_utils.find_first_matching_prim(self.cfg.prim_path) + if prim is None: + raise RuntimeError(f"Failed to find a prim at path expression: {self.cfg.prim_path}") + # check if it is a RigidBody Prim + if prim.HasAPI(UsdPhysics.RigidBodyAPI): + self._view = self._physics_sim_view.create_rigid_body_view(self.cfg.prim_path.replace(".*", "*")) + else: + raise RuntimeError(f"Failed to find a RigidBodyAPI for the prim paths: {self.cfg.prim_path}") + + # Create internal buffers + self._initialize_buffers_impl() + + def _update_buffers_impl(self, env_ids: Sequence[int]): + """Fills the buffers of the sensor data.""" + # check if self._dt is set (this is set in the update function) + if not hasattr(self, "_dt"): + raise RuntimeError( + "The update function must be called before the data buffers are accessed the first time." + ) + # default to all sensors + if len(env_ids) == self._num_envs: + env_ids = slice(None) + # obtain the poses of the sensors + pos_w, quat_w = self._view.get_transforms()[env_ids].split([3, 4], dim=-1) + quat_w = math_utils.convert_quat(quat_w, to="wxyz") + + # store the poses + self._data.pos_w[env_ids] = pos_w + math_utils.quat_rotate(quat_w, self._offset_pos_b[env_ids]) + self._data.quat_w[env_ids] = math_utils.quat_mul(quat_w, self._offset_quat_b[env_ids]) + + # get the offset from COM to link origin + com_pos_b = self._view.get_coms().to(self.device).split([3, 4], dim=-1)[0] + + # obtain the velocities of the link COM + lin_vel_w, ang_vel_w = self._view.get_velocities()[env_ids].split([3, 3], dim=-1) + # if an offset is present or the COM does not agree with the link origin, the linear velocity has to be + # transformed taking the angular velocity into account + lin_vel_w += torch.linalg.cross( + ang_vel_w, math_utils.quat_rotate(quat_w, self._offset_pos_b[env_ids] - com_pos_b[env_ids]), dim=-1 + ) + + # numerical derivative + lin_acc_w = (lin_vel_w - self._prev_lin_vel_w[env_ids]) / self._dt + self._gravity_bias_w[env_ids] + ang_acc_w = (ang_vel_w - self._prev_ang_vel_w[env_ids]) / self._dt + # store the velocities + self._data.lin_vel_b[env_ids] = math_utils.quat_rotate_inverse(self._data.quat_w[env_ids], lin_vel_w) + self._data.ang_vel_b[env_ids] = math_utils.quat_rotate_inverse(self._data.quat_w[env_ids], ang_vel_w) + # store the accelerations + self._data.lin_acc_b[env_ids] = math_utils.quat_rotate_inverse(self._data.quat_w[env_ids], lin_acc_w) + self._data.ang_acc_b[env_ids] = math_utils.quat_rotate_inverse(self._data.quat_w[env_ids], ang_acc_w) + + self._prev_lin_vel_w[env_ids] = lin_vel_w + self._prev_ang_vel_w[env_ids] = ang_vel_w + + def _initialize_buffers_impl(self): + """Create buffers for storing data.""" + # data buffers + self._data.pos_w = torch.zeros(self._view.count, 3, device=self._device) + self._data.quat_w = torch.zeros(self._view.count, 4, device=self._device) + self._data.quat_w[:, 0] = 1.0 + self._data.lin_vel_b = torch.zeros_like(self._data.pos_w) + self._data.ang_vel_b = torch.zeros_like(self._data.pos_w) + self._data.lin_acc_b = torch.zeros_like(self._data.pos_w) + self._data.ang_acc_b = torch.zeros_like(self._data.pos_w) + self._prev_lin_vel_w = torch.zeros_like(self._data.pos_w) + self._prev_ang_vel_w = torch.zeros_like(self._data.pos_w) + + # store sensor offset transformation + self._offset_pos_b = torch.tensor(list(self.cfg.offset.pos), device=self._device).repeat(self._view.count, 1) + self._offset_quat_b = torch.tensor(list(self.cfg.offset.rot), device=self._device).repeat(self._view.count, 1) + # set gravity bias + self._gravity_bias_w = torch.tensor(list(self.cfg.gravity_bias), device=self._device).repeat( + self._view.count, 1 + ) + + def _set_debug_vis_impl(self, debug_vis: bool): + # set visibility of markers + # note: parent only deals with callbacks. not their visibility + if debug_vis: + # create markers if necessary for the first tome + if not hasattr(self, "acceleration_visualizer"): + self.acceleration_visualizer = VisualizationMarkers(self.cfg.visualizer_cfg) + # set their visibility to true + self.acceleration_visualizer.set_visibility(True) + else: + if hasattr(self, "acceleration_visualizer"): + self.acceleration_visualizer.set_visibility(False) + + def _debug_vis_callback(self, event): + # safely return if view becomes invalid + # note: this invalidity happens because of isaac sim view callbacks + if self._view is None: + return + # get marker location + # -- base state + base_pos_w = self._data.pos_w.clone() + base_pos_w[:, 2] += 0.5 + # -- resolve the scales + default_scale = self.acceleration_visualizer.cfg.markers["arrow"].scale + arrow_scale = torch.tensor(default_scale, device=self.device).repeat(self._data.lin_acc_b.shape[0], 1) + # get up axis of current stage + up_axis = stage_utils.get_stage_up_axis() + # arrow-direction + quat_opengl = math_utils.quat_from_matrix( + math_utils.create_rotation_matrix_from_view( + self._data.pos_w, + self._data.pos_w + math_utils.quat_rotate(self._data.quat_w, self._data.lin_acc_b), + up_axis=up_axis, + device=self._device, + ) + ) + quat_w = math_utils.convert_camera_frame_orientation_convention(quat_opengl, "opengl", "world") + # display markers + self.acceleration_visualizer.visualize(base_pos_w, quat_w, arrow_scale) diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/imu/imu_cfg.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/imu/imu_cfg.py new file mode 100644 index 0000000000..74e38f9e6e --- /dev/null +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/imu/imu_cfg.py @@ -0,0 +1,46 @@ +# Copyright (c) 2022-2024, The Isaac Lab Project Developers. +# All rights reserved. +# +# SPDX-License-Identifier: BSD-3-Clause + +from __future__ import annotations + +from omni.isaac.lab.markers import VisualizationMarkersCfg +from omni.isaac.lab.markers.config import RED_ARROW_X_MARKER_CFG +from omni.isaac.lab.utils import configclass + +from ..sensor_base_cfg import SensorBaseCfg +from .imu import Imu + + +@configclass +class ImuCfg(SensorBaseCfg): + """Configuration for an Inertial Measurement Unit (IMU) sensor.""" + + class_type: type = Imu + + @configclass + class OffsetCfg: + """The offset pose of the sensor's frame from the sensor's parent frame.""" + + pos: tuple[float, float, float] = (0.0, 0.0, 0.0) + """Translation w.r.t. the parent frame. Defaults to (0.0, 0.0, 0.0).""" + + rot: tuple[float, float, float, float] = (1.0, 0.0, 0.0, 0.0) + """Quaternion rotation (w, x, y, z) w.r.t. the parent frame. Defaults to (1.0, 0.0, 0.0, 0.0).""" + + offset: OffsetCfg = OffsetCfg() + """The offset pose of the sensor's frame from the sensor's parent frame. Defaults to identity.""" + + visualizer_cfg: VisualizationMarkersCfg = RED_ARROW_X_MARKER_CFG.replace(prim_path="/Visuals/Command/velocity_goal") + """The configuration object for the visualization markers. Defaults to RED_ARROW_X_MARKER_CFG. + + This attribute is only used when debug visualization is enabled. + """ + gravity_bias: tuple[float, float, float] = (0.0, 0.0, 9.81) + """The linear acceleration bias applied to the linear acceleration in the world frame (x,y,z). + + Imu sensors typically output a positive gravity acceleration in opposition to the direction of gravity. This + config parameter allows users to subtract that bias if set to (0.,0.,0.). By default this is set to (0.0,0.0,9.81) + which results in a positive acceleration reading in the world Z. + """ diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/imu/imu_data.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/imu/imu_data.py new file mode 100644 index 0000000000..37920cd841 --- /dev/null +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/imu/imu_data.py @@ -0,0 +1,50 @@ +# Copyright (c) 2022-2024, The Isaac Lab Project Developers. +# All rights reserved. +# +# SPDX-License-Identifier: BSD-3-Clause + +from __future__ import annotations + +import torch +from dataclasses import dataclass + + +@dataclass +class ImuData: + """Data container for the Imu sensor.""" + + pos_w: torch.Tensor = None + """Position of the sensor origin in world frame. + + Shape is (N, 3), where ``N`` is the number of environments. + """ + + quat_w: torch.Tensor = None + """Orientation of the sensor origin in quaternion ``(w, x, y, z)`` in world frame. + + Shape is (N, 4), where ``N`` is the number of environments. + """ + + lin_vel_b: torch.Tensor = None + """IMU frame angular velocity relative to the world expressed in IMU frame. + + Shape is (N, 3), where ``N`` is the number of environments. + """ + + ang_vel_b: torch.Tensor = None + """IMU frame angular velocity relative to the world expressed in IMU frame. + + Shape is (N, 3), where ``N`` is the number of environments. + """ + + lin_acc_b: torch.Tensor = None + """IMU frame linear acceleration relative to the world expressed in IMU frame. + + Shape is (N, 3), where ``N`` is the number of environments. + """ + + ang_acc_b: torch.Tensor = None + """IMU frame angular acceleration relative to the world expressed in IMU frame. + + Shape is (N, 3), where ``N`` is the number of environments. + """ diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/ray_caster/ray_caster_camera.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/ray_caster/ray_caster_camera.py index 745033003c..9a7e483bc1 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/ray_caster/ray_caster_camera.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/ray_caster/ray_caster_camera.py @@ -10,12 +10,12 @@ from tensordict import TensorDict from typing import TYPE_CHECKING, ClassVar, Literal +import omni.isaac.core.utils.stage as stage_utils import omni.physics.tensors.impl.api as physx from omni.isaac.core.prims import XFormPrimView import omni.isaac.lab.utils.math as math_utils from omni.isaac.lab.sensors.camera import CameraData -from omni.isaac.lab.sensors.camera.utils import convert_orientation_convention, create_rotation_matrix_from_view from omni.isaac.lab.utils.warp import raycast_mesh from .ray_caster import RayCaster @@ -170,7 +170,7 @@ def set_world_poses( - :obj:`"ros"` - forward axis: +Z - up axis -Y - Offset is applied in the ROS convention - :obj:`"world"` - forward axis: +X - up axis +Z - Offset is applied in the World Frame convention - See :meth:`omni.isaac.lab.sensors.camera.utils.convert_orientation_convention` for more details + See :meth:`omni.isaac.lab.utils.maths.convert_camera_frame_orientation_convention` for more details on the conventions. Args: @@ -196,7 +196,9 @@ def set_world_poses( self._offset_pos[env_ids] = math_utils.quat_apply(math_utils.quat_inv(quat_w), pos_offset_world_frame) if orientations is not None: # convert rotation matrix from input convention to world - quat_w_set = convert_orientation_convention(orientations, origin=convention, target="world") + quat_w_set = math_utils.convert_camera_frame_orientation_convention( + orientations, origin=convention, target="world" + ) self._offset_quat[env_ids] = math_utils.quat_mul(math_utils.quat_inv(quat_w), quat_w_set) # update the data @@ -218,8 +220,12 @@ def set_world_poses_from_view( RuntimeError: If the camera prim is not set. Need to call :meth:`initialize` method first. NotImplementedError: If the stage up-axis is not "Y" or "Z". """ + # get up axis of current stage + up_axis = stage_utils.get_stage_up_axis() # camera position and rotation in opengl convention - orientations = math_utils.quat_from_matrix(create_rotation_matrix_from_view(eyes, targets, device=self._device)) + orientations = math_utils.quat_from_matrix( + math_utils.create_rotation_matrix_from_view(eyes, targets, up_axis=up_axis, device=self._device) + ) self.set_world_poses(eyes, orientations, env_ids, convention="opengl") """ @@ -243,7 +249,7 @@ def _initialize_rays_impl(self): # create buffer to store ray hits self.ray_hits_w = torch.zeros(self._view.count, self.num_rays, 3, device=self._device) # set offsets - quat_w = convert_orientation_convention( + quat_w = math_utils.convert_camera_frame_orientation_convention( torch.tensor([self.cfg.offset.rot], device=self._device), origin=self.cfg.offset.convention, target="world" ) self._offset_quat = quat_w.repeat(self._view.count, 1) diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/utils/math.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/utils/math.py index 1d3c0db81f..42c6a2bc0d 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/utils/math.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/utils/math.py @@ -8,6 +8,7 @@ # needed to import for allowing type-hinting: torch.Tensor | np.ndarray from __future__ import annotations +import math import numpy as np import torch import torch.nn.functional @@ -1418,3 +1419,143 @@ def sample_cylinder( xyz[..., 2].uniform_(h_min, h_max) # return positions return xyz + + +""" +Orientation Conversions +""" + + +def convert_camera_frame_orientation_convention( + orientation: torch.Tensor, + origin: Literal["opengl", "ros", "world"] = "opengl", + target: Literal["opengl", "ros", "world"] = "ros", +) -> torch.Tensor: + r"""Converts a quaternion representing a rotation from one convention to another. + + In USD, the camera follows the ``"opengl"`` convention. Thus, it is always in **Y up** convention. + This means that the camera is looking down the -Z axis with the +Y axis pointing up , and +X axis pointing right. + However, in ROS, the camera is looking down the +Z axis with the +Y axis pointing down, and +X axis pointing right. + Thus, the camera needs to be rotated by :math:`180^{\circ}` around the X axis to follow the ROS convention. + + .. math:: + + T_{ROS} = \begin{bmatrix} 1 & 0 & 0 & 0 \\ 0 & -1 & 0 & 0 \\ 0 & 0 & -1 & 0 \\ 0 & 0 & 0 & 1 \end{bmatrix} T_{USD} + + On the other hand, the typical world coordinate system is with +X pointing forward, +Y pointing left, + and +Z pointing up. The camera can also be set in this convention by rotating the camera by :math:`90^{\circ}` + around the X axis and :math:`-90^{\circ}` around the Y axis. + + .. math:: + + T_{WORLD} = \begin{bmatrix} 0 & 0 & -1 & 0 \\ -1 & 0 & 0 & 0 \\ 0 & 1 & 0 & 0 \\ 0 & 0 & 0 & 1 \end{bmatrix} T_{USD} + + Thus, based on their application, cameras follow different conventions for their orientation. This function + converts a quaternion from one convention to another. + + Possible conventions are: + + - :obj:`"opengl"` - forward axis: -Z - up axis +Y - Offset is applied in the OpenGL (Usd.Camera) convention + - :obj:`"ros"` - forward axis: +Z - up axis -Y - Offset is applied in the ROS convention + - :obj:`"world"` - forward axis: +X - up axis +Z - Offset is applied in the World Frame convention + + Args: + orientation: Quaternion of form `(w, x, y, z)` with shape (..., 4) in source convention. + origin: Convention to convert from. Defaults to "opengl". + target: Convention to convert to. Defaults to "ros". + + Returns: + Quaternion of form `(w, x, y, z)` with shape (..., 4) in target convention + """ + if target == origin: + return orientation.clone() + + # -- unify input type + if origin == "ros": + # convert from ros to opengl convention + rotm = matrix_from_quat(orientation) + rotm[:, :, 2] = -rotm[:, :, 2] + rotm[:, :, 1] = -rotm[:, :, 1] + # convert to opengl convention + quat_gl = quat_from_matrix(rotm) + elif origin == "world": + # convert from world (x forward and z up) to opengl convention + rotm = matrix_from_quat(orientation) + rotm = torch.matmul( + rotm, + matrix_from_euler(torch.tensor([math.pi / 2, -math.pi / 2, 0], device=orientation.device), "XYZ"), + ) + # convert to isaac-sim convention + quat_gl = quat_from_matrix(rotm) + else: + quat_gl = orientation + + # -- convert to target convention + if target == "ros": + # convert from opengl to ros convention + rotm = matrix_from_quat(quat_gl) + rotm[:, :, 2] = -rotm[:, :, 2] + rotm[:, :, 1] = -rotm[:, :, 1] + return quat_from_matrix(rotm) + elif target == "world": + # convert from opengl to world (x forward and z up) convention + rotm = matrix_from_quat(quat_gl) + rotm = torch.matmul( + rotm, + matrix_from_euler(torch.tensor([math.pi / 2, -math.pi / 2, 0], device=orientation.device), "XYZ").T, + ) + return quat_from_matrix(rotm) + else: + return quat_gl.clone() + + +def create_rotation_matrix_from_view( + eyes: torch.Tensor, + targets: torch.Tensor, + up_axis: Literal["Y", "Z"] = "Z", + device: str = "cpu", +) -> torch.Tensor: + """Compute the rotation matrix from world to view coordinates. + + This function takes a vector ''eyes'' which specifies the location + of the camera in world coordinates and the vector ''targets'' which + indicate the position of the object. + The output is a rotation matrix representing the transformation + from world coordinates -> view coordinates. + + The inputs eyes and targets can each be a + - 3 element tuple/list + - torch tensor of shape (1, 3) + - torch tensor of shape (N, 3) + + Args: + eyes: Position of the camera in world coordinates. + targets: Position of the object in world coordinates. + up_axis: The up axis of the camera. Defaults to "Z". + device: The device to create torch tensors on. Defaults to "cpu". + + The vectors are broadcast against each other so they all have shape (N, 3). + + Returns: + R: (N, 3, 3) batched rotation matrices + + Reference: + Based on PyTorch3D (https://github.com/facebookresearch/pytorch3d/blob/eaf0709d6af0025fe94d1ee7cec454bc3054826a/pytorch3d/renderer/cameras.py#L1635-L1685) + """ + if up_axis == "Y": + up_axis_vec = torch.tensor((0, 1, 0), device=device, dtype=torch.float32).repeat(eyes.shape[0], 1) + elif up_axis == "Z": + up_axis_vec = torch.tensor((0, 0, 1), device=device, dtype=torch.float32).repeat(eyes.shape[0], 1) + else: + raise ValueError(f"Invalid up axis: {up_axis}. Valid options are 'Y' and 'Z'.") + + # get rotation matrix in opengl format (-Z forward, +Y up) + z_axis = -torch.nn.functional.normalize(targets - eyes, eps=1e-5) + x_axis = torch.nn.functional.normalize(torch.cross(up_axis_vec, z_axis, dim=1), eps=1e-5) + y_axis = torch.nn.functional.normalize(torch.cross(z_axis, x_axis, dim=1), eps=1e-5) + is_close = torch.isclose(x_axis, torch.tensor(0.0), atol=5e-3).all(dim=1, keepdim=True) + if is_close.any(): + replacement = torch.nn.functional.normalize(torch.cross(y_axis, z_axis, dim=1), eps=1e-5) + x_axis = torch.where(is_close, replacement, x_axis) + R = torch.cat((x_axis[:, None, :], y_axis[:, None, :], z_axis[:, None, :]), dim=1) + return R.transpose(1, 2) diff --git a/source/extensions/omni.isaac.lab/test/sensors/check_imu_sensor.py b/source/extensions/omni.isaac.lab/test/sensors/check_imu_sensor.py new file mode 100644 index 0000000000..6516c0eefb --- /dev/null +++ b/source/extensions/omni.isaac.lab/test/sensors/check_imu_sensor.py @@ -0,0 +1,196 @@ +# Copyright (c) 2022-2024, The Isaac Lab Project Developers. +# All rights reserved. +# +# SPDX-License-Identifier: BSD-3-Clause + +""" +Visual test script for the imu sensor from the Orbit framework. +""" + +from __future__ import annotations + +"""Launch Isaac Sim Simulator first.""" + +import argparse + +from omni.isaac.kit import SimulationApp + +# add argparse arguments +parser = argparse.ArgumentParser(description="Imu Test Script") +parser.add_argument("--headless", action="store_true", default=False, help="Force display off at all times.") +parser.add_argument("--num_envs", type=int, default=128, help="Number of environments to clone.") +parser.add_argument( + "--terrain_type", + type=str, + default="generator", + choices=["generator", "usd", "plane"], + help="Type of terrain to import. Can be 'generator' or 'usd' or 'plane'.", +) +args_cli = parser.parse_args() + +# launch omniverse app +config = {"headless": args_cli.headless} +simulation_app = SimulationApp(config) + + +"""Rest everything follows.""" + +import torch +import traceback + +import carb +import omni +from omni.isaac.cloner import GridCloner +from omni.isaac.core.simulation_context import SimulationContext +from omni.isaac.core.utils.viewports import set_camera_view +from pxr import PhysxSchema + +import omni.isaac.lab.sim as sim_utils +import omni.isaac.lab.terrains as terrain_gen +from omni.isaac.lab.assets import RigidObject, RigidObjectCfg +from omni.isaac.lab.sensors.imu import Imu, ImuCfg +from omni.isaac.lab.terrains.config.rough import ROUGH_TERRAINS_CFG +from omni.isaac.lab.terrains.terrain_importer import TerrainImporter +from omni.isaac.lab.utils.assets import ISAAC_NUCLEUS_DIR +from omni.isaac.lab.utils.timer import Timer + + +def design_scene(sim: SimulationContext, num_envs: int = 2048) -> RigidObject: + """Design the scene.""" + # Handler for terrains importing + terrain_importer_cfg = terrain_gen.TerrainImporterCfg( + prim_path="/World/ground", + terrain_type="generator", + terrain_generator=ROUGH_TERRAINS_CFG, + usd_path=f"{ISAAC_NUCLEUS_DIR}/Environments/Terrains/rough_plane.usd", + max_init_terrain_level=None, + num_envs=1, + ) + _ = TerrainImporter(terrain_importer_cfg) + # obtain the current stage + stage = omni.usd.get_context().get_stage() + # Create interface to clone the scene + cloner = GridCloner(spacing=2.0) + cloner.define_base_env("/World/envs") + envs_prim_paths = cloner.generate_paths("/World/envs/env", num_paths=num_envs) + # create source prim + stage.DefinePrim(envs_prim_paths[0], "Xform") + # clone the env xform + cloner.clone(source_prim_path="/World/envs/env_0", prim_paths=envs_prim_paths, replicate_physics=True) + # Define the scene + # -- Light + cfg = sim_utils.DistantLightCfg(intensity=2000) + cfg.func("/World/light", cfg) + # -- Balls + cfg = RigidObjectCfg( + spawn=sim_utils.SphereCfg( + radius=0.25, + rigid_props=sim_utils.RigidBodyPropertiesCfg(), + mass_props=sim_utils.MassPropertiesCfg(mass=0.5), + collision_props=sim_utils.CollisionPropertiesCfg(), + visual_material=sim_utils.PreviewSurfaceCfg(diffuse_color=(0.0, 0.0, 1.0)), + ), + prim_path="/World/envs/env_.*/ball", + init_state=RigidObjectCfg.InitialStateCfg(pos=(0.0, 0.0, 5.0)), + ) + balls = RigidObject(cfg) + # Clone the scene + # obtain the current physics scene + physics_scene_prim_path = None + for prim in stage.Traverse(): + if prim.HasAPI(PhysxSchema.PhysxSceneAPI): + physics_scene_prim_path = prim.GetPrimPath() + carb.log_info(f"Physics scene prim path: {physics_scene_prim_path}") + break + # filter collisions within each environment instance + cloner.filter_collisions( + physics_scene_prim_path, + "/World/collisions", + envs_prim_paths, + ) + return balls + + +def main(): + """Main function.""" + + # Load kit helper + sim_params = { + "use_gpu": True, + "use_gpu_pipeline": True, + "use_flatcache": True, # deprecated from Isaac Sim 2023.1 onwards + "use_fabric": True, # used from Isaac Sim 2023.1 onwards + "enable_scene_query_support": True, + } + sim = SimulationContext( + physics_dt=1.0 / 60.0, rendering_dt=1.0 / 60.0, sim_params=sim_params, backend="torch", device="cuda:0" + ) + # Set main camera + set_camera_view([0.0, 30.0, 25.0], [0.0, 0.0, -2.5]) + + # Parameters + num_envs = args_cli.num_envs + # Design the scene + balls = design_scene(sim=sim, num_envs=num_envs) + + # Create a ray-caster sensor + imu_cfg = ImuCfg( + prim_path="/World/envs/env_.*/ball", + debug_vis=not args_cli.headless, + ) + # increase scale of the arrows for better visualization + imu_cfg.visualizer_cfg.markers["arrow"].scale = (1.0, 0.2, 0.2) + imu = Imu(cfg=imu_cfg) + + # Play simulator and init the Imu + sim.reset() + + # Print the sensor information + print(imu) + + # Get the ball initial positions + sim.step(render=not args_cli.headless) + balls.update(sim.get_physics_dt()) + ball_initial_positions = balls.data.root_pos_w.clone() + ball_initial_orientations = balls.data.root_quat_w.clone() + + # Create a counter for resetting the scene + step_count = 0 + # Simulate physics + while simulation_app.is_running(): + # If simulation is stopped, then exit. + if sim.is_stopped(): + break + # If simulation is paused, then skip. + if not sim.is_playing(): + sim.step(render=not args_cli.headless) + continue + # Reset the scene + if step_count % 500 == 0: + # reset ball positions + balls.write_root_pose_to_sim(torch.cat([ball_initial_positions, ball_initial_orientations], dim=-1)) + balls.reset() + # reset the sensor + imu.reset() + # reset the counter + step_count = 0 + # Step simulation + sim.step() + # Update the imu sensor + with Timer(f"Imu sensor update with {num_envs}"): + imu.update(dt=sim.get_physics_dt(), force_recompute=True) + # Update counter + step_count += 1 + + +if __name__ == "__main__": + try: + # Run the main function + main() + except Exception as err: + carb.log_error(err) + carb.log_error(traceback.format_exc()) + raise + finally: + # close sim app + simulation_app.close() diff --git a/source/extensions/omni.isaac.lab/test/sensors/test_imu.py b/source/extensions/omni.isaac.lab/test/sensors/test_imu.py new file mode 100644 index 0000000000..ee0db71bf7 --- /dev/null +++ b/source/extensions/omni.isaac.lab/test/sensors/test_imu.py @@ -0,0 +1,532 @@ +# Copyright (c) 2022-2024, The Isaac Lab Project Developers. +# All rights reserved. +# +# SPDX-License-Identifier: BSD-3-Clause + +"""Launch Isaac Sim Simulator first.""" + +from omni.isaac.lab.app import AppLauncher, run_tests + +# launch omniverse app +app_launcher = AppLauncher(headless=True, enable_cameras=True) +simulation_app = app_launcher.app + +"""Rest everything follows.""" + +import pathlib +import torch +import unittest + +import omni.isaac.core.utils.stage as stage_utils + +import omni.isaac.lab.sim as sim_utils +import omni.isaac.lab.utils.math as math_utils +from omni.isaac.lab.actuators import ImplicitActuatorCfg +from omni.isaac.lab.assets import ArticulationCfg, RigidObjectCfg +from omni.isaac.lab.markers.config import GREEN_ARROW_X_MARKER_CFG, RED_ARROW_X_MARKER_CFG +from omni.isaac.lab.scene import InteractiveScene, InteractiveSceneCfg +from omni.isaac.lab.sensors.imu import ImuCfg +from omni.isaac.lab.terrains import TerrainImporterCfg +from omni.isaac.lab.utils import configclass + +## +# Pre-defined configs +## +from omni.isaac.lab_assets.anymal import ANYMAL_C_CFG # isort: skip +from omni.isaac.lab.utils.assets import NUCLEUS_ASSET_ROOT_DIR # isort: skip + +# offset of imu_link from base_link on anymal_c +POS_OFFSET = (0.2488, 0.00835, 0.04628) +ROT_OFFSET = (0.7071068, 0, 0, 0.7071068) + +# offset of imu_link from link_1 on simple_2_link +PEND_POS_OFFSET = (0.4, 0.0, 0.1) +PEND_ROT_OFFSET = (0.5, 0.5, 0.5, 0.5) + + +@configclass +class MySceneCfg(InteractiveSceneCfg): + """Example scene configuration.""" + + # terrain - flat terrain plane + terrain = TerrainImporterCfg( + prim_path="/World/ground", + terrain_type="plane", + max_init_terrain_level=None, + ) + + # rigid objects - balls + balls = RigidObjectCfg( + prim_path="{ENV_REGEX_NS}/ball", + init_state=RigidObjectCfg.InitialStateCfg(pos=(0.0, 0.0, 0.5)), + spawn=sim_utils.SphereCfg( + radius=0.25, + rigid_props=sim_utils.RigidBodyPropertiesCfg(), + mass_props=sim_utils.MassPropertiesCfg(mass=0.5), + collision_props=sim_utils.CollisionPropertiesCfg(), + visual_material=sim_utils.PreviewSurfaceCfg(diffuse_color=(0.0, 0.0, 1.0)), + ), + ) + + cube = RigidObjectCfg( + prim_path="{ENV_REGEX_NS}/cube", + init_state=RigidObjectCfg.InitialStateCfg(pos=(0.0, -2.0, 0.5)), + spawn=sim_utils.CuboidCfg( + size=(0.25, 0.25, 0.25), + rigid_props=sim_utils.RigidBodyPropertiesCfg(), + mass_props=sim_utils.MassPropertiesCfg(mass=0.5), + collision_props=sim_utils.CollisionPropertiesCfg(), + visual_material=sim_utils.PreviewSurfaceCfg(diffuse_color=(0.0, 0.0, 1.0)), + ), + ) + + # articulations - robot + robot = ANYMAL_C_CFG.replace(prim_path="{ENV_REGEX_NS}/robot") + pendulum = ArticulationCfg( + prim_path="{ENV_REGEX_NS}/pendulum", + spawn=sim_utils.UrdfFileCfg( + fix_base=True, + merge_fixed_joints=False, + make_instanceable=False, + asset_path=f"{pathlib.Path(__file__).parent.resolve()}/urdfs/simple_2_link.urdf", + articulation_props=sim_utils.ArticulationRootPropertiesCfg( + enabled_self_collisions=True, solver_position_iteration_count=4, solver_velocity_iteration_count=0 + ), + ), + init_state=ArticulationCfg.InitialStateCfg(), + actuators={ + "joint_1_act": ImplicitActuatorCfg(joint_names_expr=["joint_.*"], stiffness=0.0, damping=0.3), + }, + ) + # sensors - imu (filled inside unit test) + imu_ball: ImuCfg = ImuCfg( + prim_path="{ENV_REGEX_NS}/ball", + gravity_bias=(0.0, 0.0, 0.0), + ) + imu_cube: ImuCfg = ImuCfg( + prim_path="{ENV_REGEX_NS}/cube", + gravity_bias=(0.0, 0.0, 0.0), + ) + imu_robot_imu_link: ImuCfg = ImuCfg( + prim_path="{ENV_REGEX_NS}/robot/imu_link", + gravity_bias=(0.0, 0.0, 0.0), + ) + imu_robot_base: ImuCfg = ImuCfg( + prim_path="{ENV_REGEX_NS}/robot/base", + offset=ImuCfg.OffsetCfg( + pos=POS_OFFSET, + rot=ROT_OFFSET, + ), + gravity_bias=(0.0, 0.0, 0.0), + ) + + imu_pendulum_imu_link: ImuCfg = ImuCfg( + prim_path="{ENV_REGEX_NS}/pendulum/imu_link", + debug_vis=not app_launcher._headless, + visualizer_cfg=RED_ARROW_X_MARKER_CFG.replace(prim_path="/Visuals/Acceleration/imu_link"), + gravity_bias=(0.0, 0.0, 9.81), + ) + imu_pendulum_base: ImuCfg = ImuCfg( + prim_path="{ENV_REGEX_NS}/pendulum/link_1", + offset=ImuCfg.OffsetCfg( + pos=PEND_POS_OFFSET, + rot=PEND_ROT_OFFSET, + ), + debug_vis=not app_launcher._headless, + visualizer_cfg=GREEN_ARROW_X_MARKER_CFG.replace(prim_path="/Visuals/Acceleration/base"), + gravity_bias=(0.0, 0.0, 9.81), + ) + + def __post_init__(self): + """Post initialization.""" + # change position of the robot + self.robot.init_state.pos = (0.0, 2.0, 1.0) + self.pendulum.init_state.pos = (-1.0, 1.0, 0.5) + + # change asset + self.robot.spawn.usd_path = f"{NUCLEUS_ASSET_ROOT_DIR}/Isaac/Robots/ANYbotics/anymal_c.usd" + # change iterations + self.robot.spawn.articulation_props.solver_position_iteration_count = 32 + self.robot.spawn.articulation_props.solver_velocity_iteration_count = 32 + + +class TestImu(unittest.TestCase): + """Test for Imu sensor.""" + + def setUp(self): + """Create a blank new stage for each test.""" + # Create a new stage + stage_utils.create_new_stage() + # Load simulation context + sim_cfg = sim_utils.SimulationCfg(dt=0.001) + sim_cfg.physx.solver_type = 0 # 0: PGS, 1: TGS --> use PGS for more accurate results + self.sim = sim_utils.SimulationContext(sim_cfg) + # construct scene + scene_cfg = MySceneCfg(num_envs=2, env_spacing=5.0, lazy_sensor_update=False) + self.scene = InteractiveScene(scene_cfg) + # Play the simulator + self.sim.reset() + + def tearDown(self): + """Stops simulator after each test.""" + # clear the stage + self.sim.clear_all_callbacks() + self.sim.clear_instance() + + """ + Tests + """ + + def test_constant_velocity(self): + """Test the Imu sensor with a constant velocity. + + Expected behavior is that the linear and angular are approx the same at every time step as in each step we set + the same velocity and therefore reset the physx buffers.""" + prev_lin_acc_ball = torch.zeros((self.scene.num_envs, 3), dtype=torch.float32, device=self.scene.device) + prev_ang_acc_ball = torch.zeros((self.scene.num_envs, 3), dtype=torch.float32, device=self.scene.device) + prev_lin_acc_cube = torch.zeros((self.scene.num_envs, 3), dtype=torch.float32, device=self.scene.device) + prev_ang_acc_cube = torch.zeros((self.scene.num_envs, 3), dtype=torch.float32, device=self.scene.device) + + for idx in range(200): + # set velocity + self.scene.rigid_objects["balls"].write_root_velocity_to_sim( + torch.tensor([[1.0, 0.0, 0.0, 0.0, 0.0, 0.0]], dtype=torch.float32, device=self.scene.device).repeat( + self.scene.num_envs, 1 + ) + ) + self.scene.rigid_objects["cube"].write_root_velocity_to_sim( + torch.tensor([[1.0, 0.0, 0.0, 0.0, 0.0, 0.0]], dtype=torch.float32, device=self.scene.device).repeat( + self.scene.num_envs, 1 + ) + ) + # write data to sim + self.scene.write_data_to_sim() + + # perform step + self.sim.step() + # read data from sim + self.scene.update(self.sim.get_physics_dt()) + + if idx > 1: + # check the imu accelerations + torch.testing.assert_close( + self.scene.sensors["imu_ball"].data.lin_acc_b, + prev_lin_acc_ball, + rtol=1e-3, + atol=1e-3, + ) + torch.testing.assert_close( + self.scene.sensors["imu_ball"].data.ang_acc_b, + prev_ang_acc_ball, + rtol=1e-3, + atol=1e-3, + ) + + torch.testing.assert_close( + self.scene.sensors["imu_cube"].data.lin_acc_b, + prev_lin_acc_cube, + rtol=1e-3, + atol=1e-3, + ) + torch.testing.assert_close( + self.scene.sensors["imu_cube"].data.ang_acc_b, + prev_ang_acc_cube, + rtol=1e-3, + atol=1e-3, + ) + + # check the imu velocities + # NOTE: the expected lin_vel_b is the same as the set velocity, as write_root_velocity_to_sim is + # setting v_0 (initial velocity) and then a calculation step of v_i = v_0 + a*dt. Consequently, + # the data.lin_vel_b is returning approx. v_i. + torch.testing.assert_close( + self.scene.sensors["imu_ball"].data.lin_vel_b, + torch.tensor( + [[1.0, 0.0, -self.scene.physics_dt * 9.81]], dtype=torch.float32, device=self.scene.device + ).repeat(self.scene.num_envs, 1), + rtol=1e-4, + atol=1e-4, + ) + torch.testing.assert_close( + self.scene.sensors["imu_cube"].data.lin_vel_b, + torch.tensor( + [[1.0, 0.0, -self.scene.physics_dt * 9.81]], dtype=torch.float32, device=self.scene.device + ).repeat(self.scene.num_envs, 1), + rtol=1e-4, + atol=1e-4, + ) + + # update previous values + prev_lin_acc_ball = self.scene.sensors["imu_ball"].data.lin_acc_b.clone() + prev_ang_acc_ball = self.scene.sensors["imu_ball"].data.ang_acc_b.clone() + prev_lin_acc_cube = self.scene.sensors["imu_cube"].data.lin_acc_b.clone() + prev_ang_acc_cube = self.scene.sensors["imu_cube"].data.ang_acc_b.clone() + + def test_constant_acceleration(self): + """Test the Imu sensor with a constant acceleration.""" + for idx in range(100): + # set acceleration + self.scene.rigid_objects["balls"].write_root_velocity_to_sim( + torch.tensor([[0.1, 0.0, 0.0, 0.0, 0.0, 0.0]], dtype=torch.float32, device=self.scene.device).repeat( + self.scene.num_envs, 1 + ) + * (idx + 1) + ) + # write data to sim + self.scene.write_data_to_sim() + # perform step + self.sim.step() + # read data from sim + self.scene.update(self.sim.get_physics_dt()) + + # skip first step where initial velocity is zero + if idx < 1: + continue + + # check the imu data + torch.testing.assert_close( + self.scene.sensors["imu_ball"].data.lin_acc_b, + math_utils.quat_rotate_inverse( + self.scene.rigid_objects["balls"].data.root_quat_w, + torch.tensor([[0.1, 0.0, 0.0]], dtype=torch.float32, device=self.scene.device).repeat( + self.scene.num_envs, 1 + ) + / self.sim.get_physics_dt(), + ), + rtol=1e-4, + atol=1e-4, + ) + + # check the angular velocity + torch.testing.assert_close( + self.scene.sensors["imu_ball"].data.ang_vel_b, + self.scene.rigid_objects["balls"].data.root_ang_vel_b, + rtol=1e-4, + atol=1e-4, + ) + + def test_single_dof_pendulum(self): + """Test imu against analytical pendulum problem.""" + + # pendulum length + pend_length = PEND_POS_OFFSET[0] + + # should achieve same results between the two imu sensors on the robot + for idx in range(500): + + # write data to sim + self.scene.write_data_to_sim() + # perform step + self.sim.step() + # read data from sim + self.scene.update(self.sim.get_physics_dt()) + + # get pendulum joint state + joint_pos = self.scene.articulations["pendulum"].data.joint_pos + joint_vel = self.scene.articulations["pendulum"].data.joint_vel + joint_acc = self.scene.articulations["pendulum"].data.joint_acc + + # IMU and base data + imu_data = self.scene.sensors["imu_pendulum_imu_link"].data + base_data = self.scene.sensors["imu_pendulum_base"].data + + # extract imu_link imu_sensor dynamics + lin_vel_w_imu_link = math_utils.quat_rotate(imu_data.quat_w, imu_data.lin_vel_b) + lin_acc_w_imu_link = math_utils.quat_rotate(imu_data.quat_w, imu_data.lin_acc_b) + + # calculate the joint dynamics from the imu_sensor (y axis of imu_link is parallel to joint axis of pendulum) + joint_vel_imu = math_utils.quat_rotate(imu_data.quat_w, imu_data.ang_vel_b)[..., 1].unsqueeze(-1) + joint_acc_imu = math_utils.quat_rotate(imu_data.quat_w, imu_data.ang_acc_b)[..., 1].unsqueeze(-1) + + # calculate analytical solution + vx = -joint_vel * pend_length * torch.sin(joint_pos) + vy = torch.zeros(2, 1, device=self.scene.device) + vz = -joint_vel * pend_length * torch.cos(joint_pos) + gt_linear_vel_w = torch.cat([vx, vy, vz], dim=-1) + + ax = -joint_acc * pend_length * torch.sin(joint_pos) - joint_vel**2 * pend_length * torch.cos(joint_pos) + ay = torch.zeros(2, 1, device=self.scene.device) + az = ( + -joint_acc * pend_length * torch.cos(joint_pos) + + joint_vel**2 * pend_length * torch.sin(joint_pos) + + 9.81 + ) + gt_linear_acc_w = torch.cat([ax, ay, az], dim=-1) + + # skip first step where initial velocity is zero + if idx < 2: + continue + + # compare imu angular velocity with joint velocity + torch.testing.assert_close( + joint_vel, + joint_vel_imu, + rtol=1e-1, + atol=1e-3, + ) + # compare imu angular acceleration with joint acceleration + torch.testing.assert_close( + joint_acc, + joint_acc_imu, + rtol=1e-1, + atol=1e-3, + ) + # compare imu linear velocituy with simple pendulum calculation + torch.testing.assert_close( + gt_linear_vel_w, + lin_vel_w_imu_link, + rtol=1e-1, + atol=1e-3, + ) + # compare imu linear acceleration with simple pendulum calculation + torch.testing.assert_close( + gt_linear_acc_w, + lin_acc_w_imu_link, + rtol=1e-1, + atol=1e0, + ) + + # check the position between offset and imu definition + torch.testing.assert_close( + base_data.pos_w, + imu_data.pos_w, + rtol=1e-5, + atol=1e-5, + ) + + # check the orientation between offset and imu definition + torch.testing.assert_close( + base_data.quat_w, + imu_data.quat_w, + rtol=1e-4, + atol=1e-4, + ) + + # check the angular velocities of the imus between offset and imu definition + torch.testing.assert_close( + base_data.ang_vel_b, + imu_data.ang_vel_b, + rtol=1e-4, + atol=1e-4, + ) + # check the angular acceleration of the imus between offset and imu definition + torch.testing.assert_close( + base_data.ang_acc_b, + imu_data.ang_acc_b, + rtol=1e-4, + atol=1e-4, + ) + + # check the linear velocity of the imus between offset and imu definition + torch.testing.assert_close( + base_data.lin_vel_b, + imu_data.lin_vel_b, + rtol=1e-2, + atol=5e-3, + ) + + # check the linear acceleration of the imus between offset and imu definition + torch.testing.assert_close( + base_data.lin_acc_b, + imu_data.lin_acc_b, + rtol=1e-1, + atol=1e-1, + ) + + def test_offset_calculation(self): + """Test offset configuration argument.""" + # should achieve same results between the two imu sensors on the robot + for idx in range(500): + # set acceleration + self.scene.articulations["robot"].write_root_velocity_to_sim( + torch.tensor([[0.05, 0.0, 0.0, 0.0, 0.0, 0.0]], dtype=torch.float32, device=self.scene.device).repeat( + self.scene.num_envs, 1 + ) + * (idx + 1) + ) + # write data to sim + self.scene.write_data_to_sim() + # perform step + self.sim.step() + # read data from sim + self.scene.update(self.sim.get_physics_dt()) + + # skip first step where initial velocity is zero + if idx < 1: + continue + + # check the accelerations + torch.testing.assert_close( + self.scene.sensors["imu_robot_base"].data.lin_acc_b, + self.scene.sensors["imu_robot_imu_link"].data.lin_acc_b, + rtol=1e-4, + atol=1e-4, + ) + torch.testing.assert_close( + self.scene.sensors["imu_robot_base"].data.ang_acc_b, + self.scene.sensors["imu_robot_imu_link"].data.ang_acc_b, + rtol=1e-4, + atol=1e-4, + ) + + # check the velocities + torch.testing.assert_close( + self.scene.sensors["imu_robot_base"].data.ang_vel_b, + self.scene.sensors["imu_robot_imu_link"].data.ang_vel_b, + rtol=1e-4, + atol=1e-4, + ) + torch.testing.assert_close( + self.scene.sensors["imu_robot_base"].data.lin_vel_b, + self.scene.sensors["imu_robot_imu_link"].data.lin_vel_b, + rtol=1e-4, + atol=1e-4, + ) + + # check the orientation + torch.testing.assert_close( + self.scene.sensors["imu_robot_base"].data.quat_w, + self.scene.sensors["imu_robot_imu_link"].data.quat_w, + rtol=1e-4, + atol=1e-4, + ) + # check the position + torch.testing.assert_close( + self.scene.sensors["imu_robot_base"].data.pos_w, + self.scene.sensors["imu_robot_imu_link"].data.pos_w, + rtol=1e-4, + atol=1e-4, + ) + + +def test_env_ids_propogation(self): + """Test that env_ids argument propagates through update and reset methods""" + self.scene.reset() + + for idx in range(10): + # set acceleration + self.scene.articulations["robot"].write_root_velocity_to_sim( + torch.tensor([[0.5, 0.0, 0.0, 0.0, 0.0, 0.0]], dtype=torch.float32, device=self.scene.device).repeat( + self.scene.num_envs, 1 + ) + * (idx + 1) + ) + # write data to sim + self.scene.write_data_to_sim() + # perform step + self.sim.step() + # read data from sim + self.scene.update(self.sim.get_physics_dt()) + + # reset scene for env 1 + self.scene.reset(env_ids=[1]) + # read data from sim + self.scene.update(self.sim.get_physics_dt()) + # perform step + self.sim.step() + # read data from sim + self.scene.update(self.sim.get_physics_dt()) + + +if __name__ == "__main__": + run_tests() diff --git a/source/extensions/omni.isaac.lab/test/sensors/urdfs/simple_2_link.urdf b/source/extensions/omni.isaac.lab/test/sensors/urdfs/simple_2_link.urdf new file mode 100644 index 0000000000..7c09e1b82c --- /dev/null +++ b/source/extensions/omni.isaac.lab/test/sensors/urdfs/simple_2_link.urdf @@ -0,0 +1,82 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/source/extensions/omni.isaac.lab/test/utils/test_math.py b/source/extensions/omni.isaac.lab/test/utils/test_math.py index d6d6086290..33a1cb1497 100644 --- a/source/extensions/omni.isaac.lab/test/utils/test_math.py +++ b/source/extensions/omni.isaac.lab/test/utils/test_math.py @@ -195,6 +195,43 @@ def test_quat_error_mag_with_quat_unique(self): torch.testing.assert_close(error_3, error_4) torch.testing.assert_close(error_4, error_1) + def test_convention_converter(self): + """Test convert_camera_frame_orientation_convention to and from ros, opengl, and world conventions.""" + quat_ros = torch.tensor([[-0.17591989, 0.33985114, 0.82047325, -0.42470819]]) + quat_opengl = torch.tensor([[0.33985113, 0.17591988, 0.42470818, 0.82047324]]) + quat_world = torch.tensor([[-0.3647052, -0.27984815, -0.1159169, 0.88047623]]) + + # from ROS + torch.testing.assert_close( + math_utils.convert_camera_frame_orientation_convention(quat_ros, "ros", "opengl"), quat_opengl + ) + torch.testing.assert_close( + math_utils.convert_camera_frame_orientation_convention(quat_ros, "ros", "world"), quat_world + ) + torch.testing.assert_close( + math_utils.convert_camera_frame_orientation_convention(quat_ros, "ros", "ros"), quat_ros + ) + # from OpenGL + torch.testing.assert_close( + math_utils.convert_camera_frame_orientation_convention(quat_opengl, "opengl", "ros"), quat_ros + ) + torch.testing.assert_close( + math_utils.convert_camera_frame_orientation_convention(quat_opengl, "opengl", "world"), quat_world + ) + torch.testing.assert_close( + math_utils.convert_camera_frame_orientation_convention(quat_opengl, "opengl", "opengl"), quat_opengl + ) + # from World + torch.testing.assert_close( + math_utils.convert_camera_frame_orientation_convention(quat_world, "world", "ros"), quat_ros + ) + torch.testing.assert_close( + math_utils.convert_camera_frame_orientation_convention(quat_world, "world", "opengl"), quat_opengl + ) + torch.testing.assert_close( + math_utils.convert_camera_frame_orientation_convention(quat_world, "world", "world"), quat_world + ) + def test_wrap_to_pi(self): """Test wrap_to_pi method.""" # Define test cases From 7e4d69b8531a6401672cd2e5c63221d22bff9d4a Mon Sep 17 00:00:00 2001 From: Wei Yang Date: Tue, 22 Oct 2024 01:47:32 -0700 Subject: [PATCH 029/111] Fixes pytorch broadcasting issue in `EMAJointPositionToLimitsAction` (#1207) # Fix the pytorch broadcasting error when joint_ids are not None This PR fixes the broadcasting error in `EMAJointPositionToLimitsAction` when `joint_ids` are not None. Fixes #1082 ## Type of change - Bug fix (non-breaking change which fixes an issue) ## Checklist - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [ ] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [ ] I have added tests that prove my fix is effective or that my feature works - [ ] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [x] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --- CONTRIBUTORS.md | 1 + .../omni/isaac/lab/envs/mdp/actions/joint_actions_to_limits.py | 2 +- 2 files changed, 2 insertions(+), 1 deletion(-) diff --git a/CONTRIBUTORS.md b/CONTRIBUTORS.md index 3c345a9d31..a606378b16 100644 --- a/CONTRIBUTORS.md +++ b/CONTRIBUTORS.md @@ -70,6 +70,7 @@ Guidelines for modifications: * Zhengyu Zhang * Ziqi Fan * Qian Wan +* Wei Yang ## Acknowledgements diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/actions/joint_actions_to_limits.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/actions/joint_actions_to_limits.py index 4345b4dec6..6478f9c82c 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/actions/joint_actions_to_limits.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/actions/joint_actions_to_limits.py @@ -185,7 +185,7 @@ def reset(self, env_ids: Sequence[int] | None = None) -> None: env_ids = slice(None) super().reset(env_ids) # reset history to current joint positions - self._prev_applied_actions[env_ids, :] = self._asset.data.joint_pos[env_ids, self._joint_ids] + self._prev_applied_actions[env_ids, :] = self._asset.data.joint_pos[env_ids[:, None], self._joint_ids] def process_actions(self, actions: torch.Tensor): # apply affine transformations From 54c4b47f71fd8c841117c69573dea789a3798dc8 Mon Sep 17 00:00:00 2001 From: robotsfan Date: Tue, 22 Oct 2024 22:53:31 +0800 Subject: [PATCH 030/111] Removes `ml_archive` as a dependency of `omni.isaac.lab` extension (#1266) # Description Extension ui can't load because of `omni.isaac.ml_archive` Fixes https://github.com/isaac-sim/IsaacLabExtensionTemplate/issues/39 ## Type of change - Bug fix (non-breaking change which fixes an issue) ## Screenshots | Before | After | | ------ | ----- | | ![before](https://github.com/user-attachments/assets/93a2973c-8934-4ba4-be77-2f7af657126f) | ![after](https://github.com/user-attachments/assets/605449ff-9280-4ee8-88d3-fc14cc2d4d5d) | ## Checklist - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [ ] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [ ] I have added tests that prove my fix is effective or that my feature works - [ ] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [x] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --- source/extensions/omni.isaac.lab/config/extension.toml | 1 - 1 file changed, 1 deletion(-) diff --git a/source/extensions/omni.isaac.lab/config/extension.toml b/source/extensions/omni.isaac.lab/config/extension.toml index fa76c37685..8252683087 100644 --- a/source/extensions/omni.isaac.lab/config/extension.toml +++ b/source/extensions/omni.isaac.lab/config/extension.toml @@ -13,7 +13,6 @@ keywords = ["kit", "robotics", "learning", "ai"] [dependencies] "omni.isaac.core" = {} -"omni.isaac.ml_archive" = {} "omni.replicator.core" = {} [python.pipapi] From 6bc4d0a01a800c015d33a1b0dc78220216664332 Mon Sep 17 00:00:00 2001 From: dtc103 <44235856+dtc103@users.noreply.github.com> Date: Tue, 22 Oct 2024 16:57:59 +0200 Subject: [PATCH 031/111] Fixes body IDs selection when computing `feet_slide` reward for locomotion-velocity task (#1277) # Description Since I wanted to use Isaac Lab for training a Unitree Go2, I played around with the examples to get used to the framework. While playing around, I got the following error message: ``` reward = torch.sum(body_vel.norm(dim=-1) * contacts, dim=1) RuntimeError: The size of tensor a (19) must match the size of tensor b (4) at non-singleton dimension 1 ``` The reward term was added as follows: ``` sliding_feet = RewTerm( func=mdp.feet_slide, params={"sensor_cfg": SceneEntityCfg("contact_forces", body_names=".*foot")}, weight=0.1 ) ``` After some code investigation, I found out, that inside the feet_slide function, the body velocities are queried as "asset.data.body_lin_vel_w[:, asset_cfg.body_ids, :2]". This would return the velocity of all body parts, since asset_cfg.body_ids contains the ids of all body parts. Therefore we need to change the line to "body_vel = asset.data.body_lin_vel_w[:, sensor_cfg.body_ids, :2]" since we only want the velocity of the body parts that contain the force sensors. This means we have to change `asset_cfg.body_ids` to `sensor_cfg.body_ids` inside the tensor call Doing this leads to the successful running of the simulation without failure. No additional dependencies are necessary for this fix. ## Type of change - Bug fix (non-breaking change which fixes an issue) ## Checklist - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [x] My changes generate no new warnings - [ ] I have added tests that prove my fix is effective or that my feature works - [x] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [x] I have added my name to the CONTRIBUTORS.md or my name already exists there --- CONTRIBUTORS.md | 1 + .../omni.isaac.lab_tasks/config/extension.toml | 2 +- .../extensions/omni.isaac.lab_tasks/docs/CHANGELOG.rst | 10 ++++++++++ .../manager_based/locomotion/velocity/mdp/rewards.py | 2 +- 4 files changed, 13 insertions(+), 2 deletions(-) diff --git a/CONTRIBUTORS.md b/CONTRIBUTORS.md index a606378b16..a47a1ab8a8 100644 --- a/CONTRIBUTORS.md +++ b/CONTRIBUTORS.md @@ -45,6 +45,7 @@ Guidelines for modifications: * Gary Lvov * Giulio Romualdi * HoJin Jeon +* Jan Kerner * Jean Tampon * Jia Lin Yuan * Jingzhou Liu diff --git a/source/extensions/omni.isaac.lab_tasks/config/extension.toml b/source/extensions/omni.isaac.lab_tasks/config/extension.toml index a6ecb7a56c..002927c1b2 100644 --- a/source/extensions/omni.isaac.lab_tasks/config/extension.toml +++ b/source/extensions/omni.isaac.lab_tasks/config/extension.toml @@ -1,7 +1,7 @@ [package] # Note: Semantic Versioning is used: https://semver.org/ -version = "0.10.7" +version = "0.10.8" # Description title = "Isaac Lab Environments" diff --git a/source/extensions/omni.isaac.lab_tasks/docs/CHANGELOG.rst b/source/extensions/omni.isaac.lab_tasks/docs/CHANGELOG.rst index b3ba0a77fd..0f55936604 100644 --- a/source/extensions/omni.isaac.lab_tasks/docs/CHANGELOG.rst +++ b/source/extensions/omni.isaac.lab_tasks/docs/CHANGELOG.rst @@ -1,6 +1,16 @@ Changelog --------- +0.10.8 (2024-10-22) +~~~~~~~~~~~~~~~~~~~ + +Fixed +^^^^^ + +* Fixed the wrong selection of body id's in the :meth:`omni.isaac.lab_tasks.manager_based.locomotion.velocity.mdp.rewards.feet_slide` + reward function. This makes sure the right IDs are selected for the bodies. + + 0.10.7 (2024-10-02) ~~~~~~~~~~~~~~~~~~~ diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/mdp/rewards.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/mdp/rewards.py index db8ad9a0cc..08c1df0097 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/mdp/rewards.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/mdp/rewards.py @@ -77,7 +77,7 @@ def feet_slide(env, sensor_cfg: SceneEntityCfg, asset_cfg: SceneEntityCfg = Scen contact_sensor: ContactSensor = env.scene.sensors[sensor_cfg.name] contacts = contact_sensor.data.net_forces_w_history[:, :, sensor_cfg.body_ids, :].norm(dim=-1).max(dim=1)[0] > 1.0 asset = env.scene[asset_cfg.name] - body_vel = asset.data.body_lin_vel_w[:, asset_cfg.body_ids, :2] + body_vel = asset.data.body_lin_vel_w[:, sensor_cfg.body_ids, :2] reward = torch.sum(body_vel.norm(dim=-1) * contacts, dim=1) return reward From bd4cd3b4d84003ab16c7dad594f4bf2ad62077c7 Mon Sep 17 00:00:00 2001 From: David Hoeller Date: Wed, 23 Oct 2024 09:43:52 +0200 Subject: [PATCH 032/111] Adds a validity check for configclasses (#1214) # Description Added a mechanism to check for the validity of a configclass object. A configclass object is valid if it contains no MISSING attributes. ## Type of change - New feature (non-breaking change which adds functionality) ## Checklist - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [ ] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [x] I have added tests that prove my fix is effective or that my feature works - [x] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [x] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --- .github/workflows/docs.yaml | 34 +++++---- docs/conf.py | 2 +- .../03_envs/create_manager_rl_env.rst | 16 +--- .../omni.isaac.lab/config/extension.toml | 2 +- .../omni.isaac.lab/docs/CHANGELOG.rst | 17 +++++ .../omni/isaac/lab/assets/asset_base.py | 2 + .../omni/isaac/lab/assets/asset_base_cfg.py | 5 +- .../omni/isaac/lab/envs/direct_marl_env.py | 2 + .../omni/isaac/lab/envs/direct_rl_env.py | 2 + .../omni/isaac/lab/envs/direct_rl_env_cfg.py | 2 +- .../omni/isaac/lab/envs/manager_based_env.py | 2 + .../lab/envs/manager_based_rl_env_cfg.py | 8 +- .../mdp/actions/joint_actions_to_limits.py | 4 +- .../lab/envs/mdp/commands/commands_cfg.py | 75 +++++++++++++------ .../lab/envs/mdp/commands/velocity_command.py | 17 +++++ .../omni/isaac/lab/managers/action_manager.py | 13 +++- .../isaac/lab/managers/command_manager.py | 15 ++-- .../isaac/lab/managers/curriculum_manager.py | 12 +-- .../omni/isaac/lab/managers/event_manager.py | 11 +-- .../omni/isaac/lab/managers/manager_base.py | 5 +- .../isaac/lab/managers/observation_manager.py | 6 ++ .../omni/isaac/lab/managers/reward_manager.py | 12 +-- .../isaac/lab/managers/termination_manager.py | 12 +-- .../omni/isaac/lab/scene/interactive_scene.py | 2 + .../lab/sensors/ray_caster/ray_caster.py | 24 ++---- .../sensors/ray_caster/ray_caster_camera.py | 2 +- .../omni/isaac/lab/sensors/sensor_base.py | 2 + .../omni/isaac/lab/sim/simulation_context.py | 2 + .../lab/terrains/terrain_generator_cfg.py | 8 +- .../isaac/lab/terrains/terrain_importer.py | 2 + .../lab/terrains/terrain_importer_cfg.py | 8 +- .../omni/isaac/lab/utils/configclass.py | 53 ++++++++++++- .../test/envs/test_direct_marl_env.py | 5 +- .../test/envs/test_env_rendering_logic.py | 9 ++- .../test/managers/test_event_manager.py | 9 +++ .../test/managers/test_reward_manager.py | 16 ++++ .../test/scene/test_interactive_scene.py | 2 +- .../test/utils/test_configclass.py | 71 ++++++++++++++++++ .../config/extension.toml | 2 +- .../omni.isaac.lab_tasks/docs/CHANGELOG.rst | 10 +++ .../manager_based/classic/ant/ant_env_cfg.py | 18 ----- .../classic/cartpole/cartpole_env_cfg.py | 18 ----- .../classic/humanoid/humanoid_env_cfg.py | 18 ----- .../velocity/config/spot/flat_env_cfg.py | 8 -- .../manipulation/cabinet/cabinet_env_cfg.py | 8 -- .../config/anymal_c/navigation_env_cfg.py | 17 ++--- .../test/test_environment_determinism.py | 21 ++++-- .../test/test_environments.py | 4 +- .../test/test_multi_agent_environments.py | 5 +- .../test/wrappers/test_rl_games_wrapper.py | 4 +- .../test/wrappers/test_rsl_rl_wrapper.py | 4 +- .../test/wrappers/test_sb3_wrapper.py | 4 +- .../test/wrappers/test_skrl_wrapper.py | 4 +- 53 files changed, 414 insertions(+), 222 deletions(-) diff --git a/.github/workflows/docs.yaml b/.github/workflows/docs.yaml index 92f854ac96..b7873872c8 100644 --- a/.github/workflows/docs.yaml +++ b/.github/workflows/docs.yaml @@ -2,12 +2,29 @@ name: Build & deploy docs on: push: - pull_request: + +concurrency: + group: ${{ github.workflow }}-${{ github.ref }} + cancel-in-progress: true jobs: + check-secrets: + name: Check secrets + runs-on: ubuntu-latest + outputs: + trigger-deploy: ${{ steps.trigger-deploy.outputs.defined }} + steps: + - id: trigger-deploy + env: + REPO_NAME: ${{ secrets.REPO_NAME }} + BRANCH_REF: ${{ secrets.BRANCH_REF }} + if: "${{ github.repository == env.REPO_NAME && github.ref == env.BRANCH_REF }}" + run: echo "defined=true" >> "$GITHUB_OUTPUT" + build-docs: name: Build Docs runs-on: ubuntu-latest + needs: [check-secrets] steps: - name: Checkout code @@ -24,8 +41,8 @@ jobs: run: pip install -r requirements.txt - name: Check branch docs building - if: ${{ github.event_name == 'pull_request' }} working-directory: ./docs + if: needs.check-secrets.outputs.trigger-deploy != 'true' run: make current-docs - name: Generate multi-version docs @@ -40,19 +57,6 @@ jobs: name: docs-html path: ./docs/_build - check-secrets: - name: Check secrets - runs-on: ubuntu-latest - outputs: - trigger-deploy: ${{ steps.trigger-deploy.outputs.defined }} - steps: - - id: trigger-deploy - env: - REPO_NAME: ${{ secrets.REPO_NAME }} - BRANCH_REF: ${{ secrets.BRANCH_REF }} - if: "${{ github.repository == env.REPO_NAME && github.ref == env.BRANCH_REF }}" - run: echo "defined=true" >> "$GITHUB_OUTPUT" - deploy-docs: name: Deploy Docs runs-on: ubuntu-latest diff --git a/docs/conf.py b/docs/conf.py index 4c7a777559..0fccd611de 100644 --- a/docs/conf.py +++ b/docs/conf.py @@ -262,7 +262,7 @@ def skip_member(app, what, name, obj, skip, options): # List the names of the functions you want to skip here - exclusions = ["from_dict", "to_dict", "replace", "copy", "__post_init__"] + exclusions = ["from_dict", "to_dict", "replace", "copy", "validate", "__post_init__"] if name in exclusions: return True return None diff --git a/docs/source/tutorials/03_envs/create_manager_rl_env.rst b/docs/source/tutorials/03_envs/create_manager_rl_env.rst index 1ff7c71990..63f710965b 100644 --- a/docs/source/tutorials/03_envs/create_manager_rl_env.rst +++ b/docs/source/tutorials/03_envs/create_manager_rl_env.rst @@ -36,7 +36,7 @@ For this tutorial, we use the cartpole environment defined in ``omni.isaac.lab_t .. literalinclude:: ../../../../source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/cartpole/cartpole_env_cfg.py :language: python - :emphasize-lines: 63-68, 124-149, 152-162, 165-169, 187-192 + :emphasize-lines: 117-141, 144-154, 172-174 :linenos: The script for running the environment ``run_cartpole_rl_env.py`` is present in the @@ -117,13 +117,8 @@ For various goal-conditioned tasks, it is useful to specify the goals or command handled through the :class:`managers.CommandManager`. The command manager handles resampling and updating the commands at each step. It can also be used to provide the commands as an observation to the agent. -For this simple task, we do not use any commands. This is specified by using a command term with the -:class:`envs.mdp.NullCommandCfg` configuration. However, you can see an example of command definitions in the -locomotion or manipulation tasks. - -.. literalinclude:: ../../../../source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/cartpole/cartpole_env_cfg.py - :language: python - :pyobject: CommandsCfg +For this simple task, we do not use any commands. Hence, we leave this attribute as its default value, which is None. +You can see an example of how to define a command manager in the other locomotion or manipulation tasks. Defining curriculum ------------------- @@ -134,11 +129,6 @@ we provide a :class:`managers.CurriculumManager` class that can be used to defin In this tutorial we don't implement a curriculum for simplicity, but you can see an example of a curriculum definition in the other locomotion or manipulation tasks. -We use a simple pass-through curriculum to define a curriculum manager that does not modify the environment. - -.. literalinclude:: ../../../../source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/cartpole/cartpole_env_cfg.py - :language: python - :pyobject: CurriculumCfg Tying it all together --------------------- diff --git a/source/extensions/omni.isaac.lab/config/extension.toml b/source/extensions/omni.isaac.lab/config/extension.toml index 8252683087..db8ec4d6b1 100644 --- a/source/extensions/omni.isaac.lab/config/extension.toml +++ b/source/extensions/omni.isaac.lab/config/extension.toml @@ -1,7 +1,7 @@ [package] # Note: Semantic Versioning is used: https://semver.org/ -version = "0.26.0" +version = "0.27.0" # Description title = "Isaac Lab framework for Robot Learning" diff --git a/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst b/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst index 433db0cd8c..ab1a562b1e 100644 --- a/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst +++ b/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst @@ -1,6 +1,23 @@ Changelog --------- +0.27.0 (2024-10-14) +~~~~~~~~~~~~~~~~~~~ + +Added +^^^^^ + +* Added a method to :class:`~omni.isaac.lab.utils.configclass` to check for attributes with values of + type ``MISSING``. This is useful when the user wants to check if a certain attribute has been set or not. +* Added the configuration validation check inside the constructor of all the core classes + (such as sensor base, asset base, scene and environment base classes). +* Added support for environments without commands by leaving the attribute + :attr:`omni.isaac.lab.envs.ManagerBasedRLEnvCfg.commands` as None. Before, this had to be done using + the class :class:`omni.isaac.lab.command_generators.NullCommandGenerator`. +* Moved the ``meshes`` attribute in the :class:`omni.isaac.lab.sensors.RayCaster` class from class variable to instance variable. + This prevents the meshes to overwrite each other. + + 0.26.0 (2024-10-16) ~~~~~~~~~~~~~~~~~~~ diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/asset_base.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/asset_base.py index 9a55a87ef0..8c66bb626a 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/asset_base.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/asset_base.py @@ -59,6 +59,8 @@ def __init__(self, cfg: AssetBaseCfg): Raises: RuntimeError: If no prims found at input prim path or prim path expression. """ + # check that the config is valid + cfg.validate() # store inputs self.cfg = cfg # flag for whether the asset is initialized diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/asset_base_cfg.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/asset_base_cfg.py index 6bea572dcb..62d047fb5c 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/asset_base_cfg.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/asset_base_cfg.py @@ -39,8 +39,9 @@ class InitialStateCfg: Defaults to (1.0, 0.0, 0.0, 0.0). """ - class_type: type[AssetBase] = MISSING - """The associated asset class. + class_type: type[AssetBase] = None + """The associated asset class. Defaults to None, which means that the asset will be spawned + but cannot be interacted with via the asset class. The class should inherit from :class:`omni.isaac.lab.assets.asset_base.AssetBase`. """ diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_marl_env.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_marl_env.py index 5bcedb0591..70c0b3f662 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_marl_env.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_marl_env.py @@ -74,6 +74,8 @@ def __init__(self, cfg: DirectMARLEnvCfg, render_mode: str | None = None, **kwar RuntimeError: If a simulation context already exists. The environment must always create one since it configures the simulation context and controls the simulation. """ + # check that the config is valid + cfg.validate() # store inputs to class self.cfg = cfg # store the render mode diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_rl_env.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_rl_env.py index 582d8ad155..32dafdef33 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_rl_env.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_rl_env.py @@ -79,6 +79,8 @@ def __init__(self, cfg: DirectRLEnvCfg, render_mode: str | None = None, **kwargs RuntimeError: If a simulation context already exists. The environment must always create one since it configures the simulation context and controls the simulation. """ + # check that the config is valid + cfg.validate() # store inputs to class self.cfg = cfg # store the render mode diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_rl_env_cfg.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_rl_env_cfg.py index 888db7c56a..4e4f1725c8 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_rl_env_cfg.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/direct_rl_env_cfg.py @@ -98,7 +98,7 @@ class DirectRLEnvCfg: Please refer to the :class:`omni.isaac.lab.scene.InteractiveSceneCfg` class for more details. """ - events: object = None + events: object | None = None """Event settings. Defaults to None, in which case no events are applied through the event manager. Please refer to the :class:`omni.isaac.lab.managers.EventManager` class for more details. diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/manager_based_env.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/manager_based_env.py index 9b2991a521..ccf8a5ae14 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/manager_based_env.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/manager_based_env.py @@ -69,6 +69,8 @@ def __init__(self, cfg: ManagerBasedEnvCfg): RuntimeError: If a simulation context already exists. The environment must always create one since it configures the simulation context and controls the simulation. """ + # check that the config is valid + cfg.validate() # store inputs to class self.cfg = cfg # initialize internal variables diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/manager_based_rl_env_cfg.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/manager_based_rl_env_cfg.py index b0def63606..93195d4d55 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/manager_based_rl_env_cfg.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/manager_based_rl_env_cfg.py @@ -67,14 +67,14 @@ class ManagerBasedRLEnvCfg(ManagerBasedEnvCfg): Please refer to the :class:`omni.isaac.lab.managers.TerminationManager` class for more details. """ - curriculum: object = MISSING - """Curriculum settings. + curriculum: object | None = None + """Curriculum settings. Defaults to None, in which case no curriculum is applied. Please refer to the :class:`omni.isaac.lab.managers.CurriculumManager` class for more details. """ - commands: object = MISSING - """Command settings. + commands: object | None = None + """Command settings. Defaults to None, in which case no commands are generated. Please refer to the :class:`omni.isaac.lab.managers.CommandManager` class for more details. """ diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/actions/joint_actions_to_limits.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/actions/joint_actions_to_limits.py index 6478f9c82c..3b31c9502a 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/actions/joint_actions_to_limits.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/actions/joint_actions_to_limits.py @@ -183,9 +183,11 @@ def reset(self, env_ids: Sequence[int] | None = None) -> None: # check if specific environment ids are provided if env_ids is None: env_ids = slice(None) + else: + env_ids = env_ids[:, None] super().reset(env_ids) # reset history to current joint positions - self._prev_applied_actions[env_ids, :] = self._asset.data.joint_pos[env_ids[:, None], self._joint_ids] + self._prev_applied_actions[env_ids, :] = self._asset.data.joint_pos[env_ids, self._joint_ids] def process_actions(self, actions: torch.Tensor): # apply affine transformations diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/commands/commands_cfg.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/commands/commands_cfg.py index d548f554db..d19bea60e2 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/commands/commands_cfg.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/commands/commands_cfg.py @@ -37,29 +37,46 @@ class UniformVelocityCommandCfg(CommandTermCfg): asset_name: str = MISSING """Name of the asset in the environment for which the commands are generated.""" - heading_command: bool = MISSING - """Whether to use heading command or angular velocity command. + + heading_command: bool = False + """Whether to use heading command or angular velocity command. Defaults to False. If True, the angular velocity command is computed from the heading error, where the target heading is sampled uniformly from provided range. Otherwise, the angular velocity command is sampled uniformly from provided range. """ - heading_control_stiffness: float = MISSING - """Scale factor to convert the heading error to angular velocity command.""" - rel_standing_envs: float = MISSING - """Probability threshold for environments where the robots that are standing still.""" - rel_heading_envs: float = MISSING - """Probability threshold for environments where the robots follow the heading-based angular velocity command - (the others follow the sampled angular velocity command).""" + + heading_control_stiffness: float = 1.0 + """Scale factor to convert the heading error to angular velocity command. Defaults to 1.0.""" + + rel_standing_envs: float = 0.0 + """The sampled probability of environments that should be standing still. Defaults to 0.0.""" + + rel_heading_envs: float = 1.0 + """The sampled probability of environments where the robots follow the heading-based angular velocity command + (the others follow the sampled angular velocity command). Defaults to 1.0. + + This parameter is only used if :attr:`heading_command` is True. + """ @configclass class Ranges: """Uniform distribution ranges for the velocity commands.""" - lin_vel_x: tuple[float, float] = MISSING # min max [m/s] - lin_vel_y: tuple[float, float] = MISSING # min max [m/s] - ang_vel_z: tuple[float, float] = MISSING # min max [rad/s] - heading: tuple[float, float] = MISSING # min max [rad] + lin_vel_x: tuple[float, float] = MISSING + """Range for the linear-x velocity command (in m/s).""" + + lin_vel_y: tuple[float, float] = MISSING + """Range for the linear-y velocity command (in m/s).""" + + ang_vel_z: tuple[float, float] = MISSING + """Range for the angular-z velocity command (in rad/s).""" + + heading: tuple[float, float] | None = None + """Range for the heading command (in rad). Defaults to None. + + This parameter is only used if :attr:`~UniformVelocityCommandCfg.heading_command` is True. + """ ranges: Ranges = MISSING """Distribution ranges for the velocity commands.""" @@ -91,15 +108,17 @@ class Ranges: """Normal distribution ranges for the velocity commands.""" mean_vel: tuple[float, float, float] = MISSING - """Mean velocity for the normal distribution. + """Mean velocity for the normal distribution (in m/s). The tuple contains the mean linear-x, linear-y, and angular-z velocity. """ + std_vel: tuple[float, float, float] = MISSING - """Standard deviation for the normal distribution. + """Standard deviation for the normal distribution (in m/s). The tuple contains the standard deviation linear-x, linear-y, and angular-z velocity. """ + zero_prob: tuple[float, float, float] = MISSING """Probability of zero velocity for the normal distribution. @@ -118,6 +137,7 @@ class UniformPoseCommandCfg(CommandTermCfg): asset_name: str = MISSING """Name of the asset in the environment for which the commands are generated.""" + body_name: str = MISSING """Name of the body in the asset for which the commands are generated.""" @@ -131,12 +151,23 @@ class UniformPoseCommandCfg(CommandTermCfg): class Ranges: """Uniform distribution ranges for the pose commands.""" - pos_x: tuple[float, float] = MISSING # min max [m] - pos_y: tuple[float, float] = MISSING # min max [m] - pos_z: tuple[float, float] = MISSING # min max [m] - roll: tuple[float, float] = MISSING # min max [rad] - pitch: tuple[float, float] = MISSING # min max [rad] - yaw: tuple[float, float] = MISSING # min max [rad] + pos_x: tuple[float, float] = MISSING + """Range for the x position (in m).""" + + pos_y: tuple[float, float] = MISSING + """Range for the y position (in m).""" + + pos_z: tuple[float, float] = MISSING + """Range for the z position (in m).""" + + roll: tuple[float, float] = MISSING + """Range for the roll angle (in rad).""" + + pitch: tuple[float, float] = MISSING + """Range for the pitch angle (in rad).""" + + yaw: tuple[float, float] = MISSING + """Range for the yaw angle (in rad).""" ranges: Ranges = MISSING """Ranges for the commands.""" @@ -175,8 +206,10 @@ class Ranges: pos_x: tuple[float, float] = MISSING """Range for the x position (in m).""" + pos_y: tuple[float, float] = MISSING """Range for the y position (in m).""" + heading: tuple[float, float] = MISSING """Heading range for the position commands (in rad). diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/commands/velocity_command.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/commands/velocity_command.py index 4a35adc5fd..2cabd86dba 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/commands/velocity_command.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/commands/velocity_command.py @@ -11,6 +11,8 @@ from collections.abc import Sequence from typing import TYPE_CHECKING +import omni.log + import omni.isaac.lab.utils.math as math_utils from omni.isaac.lab.assets import Articulation from omni.isaac.lab.managers import CommandTerm @@ -49,10 +51,25 @@ def __init__(self, cfg: UniformVelocityCommandCfg, env: ManagerBasedEnv): Args: cfg: The configuration of the command generator. env: The environment. + + Raises: + ValueError: If the heading command is active but the heading range is not provided. """ # initialize the base class super().__init__(cfg, env) + # check configuration + if self.cfg.heading_command and self.cfg.ranges.heading is None: + raise ValueError( + "The velocity command has heading commands active (heading_command=True) but the `ranges.heading`" + " parameter is set to None." + ) + if self.cfg.ranges.heading and not self.cfg.heading_command: + omni.log.warn( + f"The velocity command has the 'ranges.heading' attribute set to '{self.cfg.ranges.heading}'" + " but the heading command is not active. Consider setting the flag for the heading command to True." + ) + # obtain the robot asset # -- robot self.robot: Articulation = env.scene[cfg.asset_name] diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/action_manager.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/action_manager.py index 56a7ff92dc..2f729cde23 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/action_manager.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/action_manager.py @@ -181,12 +181,21 @@ def __init__(self, cfg: object, env: ManagerBasedEnv): Args: cfg: The configuration object or dictionary (``dict[str, ActionTermCfg]``). env: The environment instance. + + Raises: + ValueError: If the configuration is None. """ + # check if config is None + if cfg is None: + raise ValueError("Action manager configuration is None. Please provide a valid configuration.") + + # call the base class constructor (this prepares the terms) super().__init__(cfg, env) # create buffers to store actions self._action = torch.zeros((self.num_envs, self.total_action_dim), device=self.device) self._prev_action = torch.zeros_like(self._action) + # check if any term has debug visualization implemented self.cfg.debug_vis = False for term in self._terms.values(): self.cfg.debug_vis |= term.cfg.debug_vis @@ -334,8 +343,7 @@ def get_term(self, name: str) -> ActionTerm: """ def _prepare_terms(self): - """Prepares a list of action terms.""" - # parse action terms from the config + # create buffers to parse and store terms self._term_names: list[str] = list() self._terms: dict[str, ActionTerm] = dict() @@ -344,6 +352,7 @@ def _prepare_terms(self): cfg_items = self.cfg.items() else: cfg_items = self.cfg.__dict__.items() + # parse action terms from the config for term_name, term_cfg in cfg_items: # check if term config is None if term_cfg is None: diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/command_manager.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/command_manager.py index 5cf7e929ac..2b4451f7e4 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/command_manager.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/command_manager.py @@ -243,12 +243,17 @@ def __init__(self, cfg: object, env: ManagerBasedRLEnv): cfg: The configuration object or dictionary (``dict[str, CommandTermCfg]``). env: The environment instance. """ + # create buffers to parse and store terms + self._terms: dict[str, CommandTerm] = dict() + + # call the base class constructor (this prepares the terms) super().__init__(cfg, env) # store the commands self._commands = dict() - self.cfg.debug_vis = False - for term in self._terms.values(): - self.cfg.debug_vis |= term.cfg.debug_vis + if self.cfg: + self.cfg.debug_vis = False + for term in self._terms.values(): + self.cfg.debug_vis |= term.cfg.debug_vis def __str__(self) -> str: """Returns: A string representation for the command manager.""" @@ -371,10 +376,6 @@ def get_term(self, name: str) -> CommandTerm: """ def _prepare_terms(self): - """Prepares a list of command terms.""" - # parse command terms from the config - self._terms: dict[str, CommandTerm] = dict() - # check if config is dict already if isinstance(self.cfg, dict): cfg_items = self.cfg.items() diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/curriculum_manager.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/curriculum_manager.py index b9bef068bf..92fe7e7ef7 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/curriculum_manager.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/curriculum_manager.py @@ -44,7 +44,14 @@ def __init__(self, cfg: object, env: ManagerBasedRLEnv): TypeError: If curriculum term is not of type :class:`CurriculumTermCfg`. ValueError: If curriculum term configuration does not satisfy its function signature. """ + # create buffers to parse and store terms + self._term_names: list[str] = list() + self._term_cfgs: list[CurriculumTermCfg] = list() + self._class_term_cfgs: list[CurriculumTermCfg] = list() + + # call the base class constructor (this will parse the terms config) super().__init__(cfg, env) + # prepare logging self._curriculum_state = dict() for term_name in self._term_names: @@ -136,11 +143,6 @@ def compute(self, env_ids: Sequence[int] | None = None): """ def _prepare_terms(self): - # parse remaining curriculum terms and decimate their information - self._term_names: list[str] = list() - self._term_cfgs: list[CurriculumTermCfg] = list() - self._class_term_cfgs: list[CurriculumTermCfg] = list() - # check if config is dict already if isinstance(self.cfg, dict): cfg_items = self.cfg.items() diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/event_manager.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/event_manager.py index 9843164ba0..9209fe1d4a 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/event_manager.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/event_manager.py @@ -62,6 +62,12 @@ def __init__(self, cfg: object, env: ManagerBasedEnv): cfg: A configuration object or dictionary (``dict[str, EventTermCfg]``). env: An environment object. """ + # create buffers to parse and store terms + self._mode_term_names: dict[str, list[str]] = dict() + self._mode_term_cfgs: dict[str, list[EventTermCfg]] = dict() + self._mode_class_term_cfgs: dict[str, list[EventTermCfg]] = dict() + + # call the base class (this will parse the terms config) super().__init__(cfg, env) def __str__(self) -> str: @@ -294,11 +300,6 @@ def get_term_cfg(self, term_name: str) -> EventTermCfg: """ def _prepare_terms(self): - """Prepares a list of event functions.""" - # parse remaining event terms and decimate their information - self._mode_term_names: dict[str, list[str]] = dict() - self._mode_term_cfgs: dict[str, list[EventTermCfg]] = dict() - self._mode_class_term_cfgs: dict[str, list[EventTermCfg]] = dict() # buffer to store the time left for "interval" mode # if interval is global, then it is a single value, otherwise it is per environment self._interval_term_time_left: list[torch.Tensor] = list() diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/manager_base.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/manager_base.py index 2bc9236cab..4da002934f 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/manager_base.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/manager_base.py @@ -120,14 +120,15 @@ def __init__(self, cfg: object, env: ManagerBasedEnv): """Initialize the manager. Args: - cfg: The configuration object. + cfg: The configuration object. If None, the manager is initialized without any terms. env: The environment instance. """ # store the inputs self.cfg = copy.deepcopy(cfg) self._env = env # parse config to create terms information - self._prepare_terms() + if self.cfg: + self._prepare_terms() """ Properties. diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/observation_manager.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/observation_manager.py index 58ae0f55f3..1e0391b3a0 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/observation_manager.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/observation_manager.py @@ -63,9 +63,15 @@ def __init__(self, cfg: object, env: ManagerBasedEnv): env: The environment instance. Raises: + ValueError: If the configuration is None. RuntimeError: If the shapes of the observation terms in a group are not compatible for concatenation and the :attr:`~ObservationGroupCfg.concatenate_terms` attribute is set to True. """ + # check that cfg is not None + if cfg is None: + raise ValueError("Observation manager configuration is None. Please provide a valid configuration.") + + # call the base class constructor (this will parse the terms config) super().__init__(cfg, env) # compute combined vector for obs group diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/reward_manager.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/reward_manager.py index c10bc12ec5..5e17e0516e 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/reward_manager.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/reward_manager.py @@ -47,6 +47,12 @@ def __init__(self, cfg: object, env: ManagerBasedRLEnv): cfg: The configuration object or dictionary (``dict[str, RewardTermCfg]``). env: The environment instance. """ + # create buffers to parse and store terms + self._term_names: list[str] = list() + self._term_cfgs: list[RewardTermCfg] = list() + self._class_term_cfgs: list[RewardTermCfg] = list() + + # call the base class constructor (this will parse the terms config) super().__init__(cfg, env) # prepare extra info to store individual reward term information self._episode_sums = dict() @@ -185,12 +191,6 @@ def get_term_cfg(self, term_name: str) -> RewardTermCfg: """ def _prepare_terms(self): - """Prepares a list of reward functions.""" - # parse remaining reward terms and decimate their information - self._term_names: list[str] = list() - self._term_cfgs: list[RewardTermCfg] = list() - self._class_term_cfgs: list[RewardTermCfg] = list() - # check if config is dict already if isinstance(self.cfg, dict): cfg_items = self.cfg.items() diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/termination_manager.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/termination_manager.py index bbd1924048..77b32f2a53 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/termination_manager.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/termination_manager.py @@ -53,6 +53,12 @@ def __init__(self, cfg: object, env: ManagerBasedRLEnv): cfg: The configuration object or dictionary (``dict[str, TerminationTermCfg]``). env: An environment object. """ + # create buffers to parse and store terms + self._term_names: list[str] = list() + self._term_cfgs: list[TerminationTermCfg] = list() + self._class_term_cfgs: list[TerminationTermCfg] = list() + + # call the base class constructor (this will parse the terms config) super().__init__(cfg, env) # prepare extra info to store individual termination term information self._term_dones = dict() @@ -219,12 +225,6 @@ def get_term_cfg(self, term_name: str) -> TerminationTermCfg: """ def _prepare_terms(self): - """Prepares a list of termination functions.""" - # parse remaining termination terms and decimate their information - self._term_names: list[str] = list() - self._term_cfgs: list[TerminationTermCfg] = list() - self._class_term_cfgs: list[TerminationTermCfg] = list() - # check if config is dict already if isinstance(self.cfg, dict): cfg_items = self.cfg.items() diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/scene/interactive_scene.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/scene/interactive_scene.py index 85775ba425..0e74a9f878 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/scene/interactive_scene.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/scene/interactive_scene.py @@ -104,6 +104,8 @@ def __init__(self, cfg: InteractiveSceneCfg): Args: cfg: The configuration class for the scene. """ + # check that the config is valid + cfg.validate() # store inputs self.cfg = cfg # initialize scene elements diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/ray_caster/ray_caster.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/ray_caster/ray_caster.py index 8be96c358d..ec25f88f24 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/ray_caster/ray_caster.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/ray_caster/ray_caster.py @@ -9,7 +9,7 @@ import re import torch from collections.abc import Sequence -from typing import TYPE_CHECKING, ClassVar +from typing import TYPE_CHECKING import omni.log import omni.physics.tensors.impl.api as physx @@ -48,14 +48,6 @@ class RayCaster(SensorBase): cfg: RayCasterCfg """The configuration parameters.""" - meshes: ClassVar[dict[str, wp.Mesh]] = {} - """The warp meshes available for raycasting. - - The keys correspond to the prim path for the meshes, and values are the corresponding warp Mesh objects. - - Note: - We store a global dictionary of all warp meshes to prevent re-loading the mesh for different ray-cast sensor instances. - """ def __init__(self, cfg: RayCasterCfg): """Initializes the ray-caster object. @@ -77,6 +69,8 @@ def __init__(self, cfg: RayCasterCfg): super().__init__(cfg) # Create empty variables for storing output data self._data = RayCasterData() + # the warp meshes used for raycasting. + self.meshes: dict[str, wp.Mesh] = {} def __str__(self) -> str: """Returns: A string containing information about the instance.""" @@ -84,7 +78,7 @@ def __str__(self) -> str: f"Ray-caster @ '{self.cfg.prim_path}': \n" f"\tview type : {self._view.__class__}\n" f"\tupdate period (s) : {self.cfg.update_period}\n" - f"\tnumber of meshes : {len(RayCaster.meshes)}\n" + f"\tnumber of meshes : {len(self.meshes)}\n" f"\tnumber of sensors : {self._view.count}\n" f"\tnumber of rays/sensor: {self.num_rays}\n" f"\ttotal number of rays : {self.num_rays * self._view.count}" @@ -163,10 +157,6 @@ def _initialize_warp_meshes(self): # read prims to ray-cast for mesh_prim_path in self.cfg.mesh_prim_paths: - # check if mesh already casted into warp mesh - if mesh_prim_path in RayCaster.meshes: - continue - # check if the prim is a plane - handle PhysX plane as a special case # if a plane exists then we need to create an infinite mesh that is a plane mesh_prim = sim_utils.get_first_matching_child_prim( @@ -197,10 +187,10 @@ def _initialize_warp_meshes(self): # print info omni.log.info(f"Created infinite plane mesh prim: {mesh_prim.GetPath()}.") # add the warp mesh to the list - RayCaster.meshes[mesh_prim_path] = wp_mesh + self.meshes[mesh_prim_path] = wp_mesh # throw an error if no meshes are found - if all([mesh_prim_path not in RayCaster.meshes for mesh_prim_path in self.cfg.mesh_prim_paths]): + if all([mesh_prim_path not in self.meshes for mesh_prim_path in self.cfg.mesh_prim_paths]): raise RuntimeError( f"No meshes found for ray-casting! Please check the mesh prim paths: {self.cfg.mesh_prim_paths}" ) @@ -263,7 +253,7 @@ def _update_buffers_impl(self, env_ids: Sequence[int]): ray_starts_w, ray_directions_w, max_dist=self.cfg.max_distance, - mesh=RayCaster.meshes[self.cfg.mesh_prim_paths[0]], + mesh=self.meshes[self.cfg.mesh_prim_paths[0]], )[0] def _set_debug_vis_impl(self, debug_vis: bool): diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/ray_caster/ray_caster_camera.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/ray_caster/ray_caster_camera.py index 9a7e483bc1..03da4ca9b8 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/ray_caster/ray_caster_camera.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/ray_caster/ray_caster_camera.py @@ -281,7 +281,7 @@ def _update_buffers_impl(self, env_ids: Sequence[int]): self.ray_hits_w, ray_depth, ray_normal, _ = raycast_mesh( ray_starts_w, ray_directions_w, - mesh=RayCasterCamera.meshes[self.cfg.mesh_prim_paths[0]], + mesh=self.meshes[self.cfg.mesh_prim_paths[0]], max_dist=1e6, return_distance=any( [name in self.cfg.data_types for name in ["distance_to_image_plane", "distance_to_camera"]] diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/sensor_base.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/sensor_base.py index 8f0d2d5092..b87e209d0a 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/sensor_base.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/sensor_base.py @@ -48,6 +48,8 @@ def __init__(self, cfg: SensorBaseCfg): # check that config is valid if cfg.history_length < 0: raise ValueError(f"History length must be greater than 0! Received: {cfg.history_length}") + # check that the config is valid + cfg.validate() # store inputs self.cfg = cfg # flag for whether the sensor is initialized diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/simulation_context.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/simulation_context.py index 315ad18d47..ce1278f5fc 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/simulation_context.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/simulation_context.py @@ -114,6 +114,8 @@ def __init__(self, cfg: SimulationCfg | None = None): # store input if cfg is None: cfg = SimulationCfg() + # check that the config is valid + cfg.validate() self.cfg = cfg # check that simulation is running if stage_utils.get_current_stage() is None: diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/terrains/terrain_generator_cfg.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/terrains/terrain_generator_cfg.py index 5b692bfd81..4b1e9a077a 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/terrains/terrain_generator_cfg.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/terrains/terrain_generator_cfg.py @@ -88,8 +88,12 @@ class SubTerrainBaseCfg: is 0.7. """ - size: tuple[float, float] = MISSING - """The width (along x) and length (along y) of the terrain (in m).""" + size: tuple[float, float] = (10.0, 10.0) + """The width (along x) and length (along y) of the terrain (in m). Defaults to (10.0, 10.0). + + In case the :class:`~omni.isaac.lab.terrains.TerrainImporterCfg` is used, this parameter gets overridden by + :attr:`omni.isaac.lab.scene.TerrainImporterCfg.size` attribute. + """ flat_patch_sampling: dict[str, FlatPatchSamplingCfg] | None = None """Dictionary of configurations for sampling flat patches on the sub-terrain. Defaults to None, diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/terrains/terrain_importer.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/terrains/terrain_importer.py index 2dbdcbf9e9..e8834ceb52 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/terrains/terrain_importer.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/terrains/terrain_importer.py @@ -67,6 +67,8 @@ def __init__(self, cfg: TerrainImporterCfg): ValueError: If terrain type is 'usd' and no configuration provided for ``usd_path``. ValueError: If terrain type is 'usd' or 'plane' and no configuration provided for ``env_spacing``. """ + # check that the config is valid + cfg.validate() # store inputs self.cfg = cfg self.device = sim_utils.SimulationContext.instance().device # type: ignore diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/terrains/terrain_importer_cfg.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/terrains/terrain_importer_cfg.py index d6aca9419e..c420ed2844 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/terrains/terrain_importer_cfg.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/terrains/terrain_importer_cfg.py @@ -36,8 +36,12 @@ class TerrainImporterCfg: All sub-terrains are imported relative to this prim path. """ - num_envs: int = MISSING - """The number of environment origins to consider.""" + num_envs: int = 1 + """The number of environment origins to consider. Defaults to 1. + + In case, the :class:`~omni.isaac.lab.scene.InteractiveSceneCfg` is used, this parameter gets overridden by + :attr:`omni.isaac.lab.scene.InteractiveSceneCfg.num_envs` attribute. + """ terrain_type: Literal["generator", "plane", "usd"] = "generator" """The type of terrain to generate. Defaults to "generator". diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/utils/configclass.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/utils/configclass.py index 7c1e1a9291..5bb9c30183 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/utils/configclass.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/utils/configclass.py @@ -14,7 +14,7 @@ from .dict import class_to_dict, update_class_from_dict -_CONFIGCLASS_METHODS = ["to_dict", "from_dict", "replace", "copy"] +_CONFIGCLASS_METHODS = ["to_dict", "from_dict", "replace", "copy", "validate"] """List of class methods added at runtime to dataclass.""" """ @@ -98,6 +98,7 @@ class EnvCfg: setattr(cls, "from_dict", _update_class_from_dict) setattr(cls, "replace", _replace_class_with_kwargs) setattr(cls, "copy", _copy_class) + setattr(cls, "validate", _validate) # wrap around dataclass cls = dataclass(cls, **kwargs) # return wrapped class @@ -240,6 +241,56 @@ class State: cls.__annotations__ = hints +def _validate(obj: object, prefix: str = "") -> list[str]: + """Check the validity of configclass object. + + This function checks if the object is a valid configclass object. A valid configclass object contains no MISSING + entries. + + Args: + obj: The object to check. + prefix: The prefix to add to the missing fields. Defaults to ''. + + Returns: + A list of missing fields. + + Raises: + TypeError: When the object is not a valid configuration object. + """ + missing_fields = [] + + if type(obj) is type(MISSING): + missing_fields.append(prefix) + return missing_fields + elif isinstance(obj, (list, tuple)): + for index, item in enumerate(obj): + current_path = f"{prefix}[{index}]" + missing_fields.extend(_validate(item, prefix=current_path)) + return missing_fields + elif isinstance(obj, dict): + obj_dict = obj + elif hasattr(obj, "__dict__"): + obj_dict = obj.__dict__ + else: + return missing_fields + + for key, value in obj_dict.items(): + # disregard builtin attributes + if key.startswith("__"): + continue + current_path = f"{prefix}.{key}" if prefix else key + missing_fields.extend(_validate(value, prefix=current_path)) + + # raise an error only once at the top-level call + if prefix == "" and missing_fields: + formatted_message = "\n".join(f" - {field}" for field in missing_fields) + raise TypeError( + f"Missing values detected in object {obj.__class__.__name__} for the following" + f" fields:\n{formatted_message}\n" + ) + return missing_fields + + def _process_mutable_types(cls): """Initialize all mutable elements through :obj:`dataclasses.Field` to avoid unnecessary complaints. diff --git a/source/extensions/omni.isaac.lab/test/envs/test_direct_marl_env.py b/source/extensions/omni.isaac.lab/test/envs/test_direct_marl_env.py index 01afb1c22c..eba2895e30 100644 --- a/source/extensions/omni.isaac.lab/test/envs/test_direct_marl_env.py +++ b/source/extensions/omni.isaac.lab/test/envs/test_direct_marl_env.py @@ -52,6 +52,7 @@ class EmptyEnvCfg(DirectMARLEnvCfg): action_spaces = {"agent_0": 1, "agent_1": 2} observation_spaces = {"agent_0": 3, "agent_1": 4} state_space = -1 + episode_length_s = 100.0 return EmptyEnvCfg() @@ -72,10 +73,10 @@ def test_initialization(self): # create environment env = DirectMARLEnv(cfg=get_empty_base_env_cfg(device=device)) except Exception as e: - if "env" in locals(): + if "env" in locals() and hasattr(env, "_is_closed"): env.close() else: - if hasattr(e, "obj") and hasattr(e.obj, "close"): + if hasattr(e, "obj") and hasattr(e.obj, "_is_closed"): e.obj.close() self.fail(f"Failed to set-up the DirectMARLEnv environment. Error: {e}") diff --git a/source/extensions/omni.isaac.lab/test/envs/test_env_rendering_logic.py b/source/extensions/omni.isaac.lab/test/envs/test_env_rendering_logic.py index dc6ba8c16f..378a089750 100644 --- a/source/extensions/omni.isaac.lab/test/envs/test_env_rendering_logic.py +++ b/source/extensions/omni.isaac.lab/test/envs/test_env_rendering_logic.py @@ -47,6 +47,7 @@ class EnvCfg(ManagerBasedEnvCfg): """Configuration for the test environment.""" decimation: int = 4 + episode_length_s: float = 100.0 sim: SimulationCfg = SimulationCfg(dt=0.005, render_interval=render_interval) scene: InteractiveSceneCfg = InteractiveSceneCfg(num_envs=1, env_spacing=1.0) actions: EmptyManagerCfg = EmptyManagerCfg() @@ -63,10 +64,13 @@ class EnvCfg(ManagerBasedRLEnvCfg): """Configuration for the test environment.""" decimation: int = 4 + episode_length_s: float = 100.0 sim: SimulationCfg = SimulationCfg(dt=0.005, render_interval=render_interval) scene: InteractiveSceneCfg = InteractiveSceneCfg(num_envs=1, env_spacing=1.0) actions: EmptyManagerCfg = EmptyManagerCfg() observations: EmptyManagerCfg = EmptyManagerCfg() + rewards: EmptyManagerCfg = EmptyManagerCfg() + terminations: EmptyManagerCfg = EmptyManagerCfg() return ManagerBasedRLEnv(cfg=EnvCfg()) @@ -81,6 +85,7 @@ class EnvCfg(DirectRLEnvCfg): decimation: int = 4 action_space: int = 0 observation_space: int = 0 + episode_length_s: float = 100.0 sim: SimulationCfg = SimulationCfg(dt=0.005, render_interval=render_interval) scene: InteractiveSceneCfg = InteractiveSceneCfg(num_envs=1, env_spacing=1.0) @@ -140,10 +145,10 @@ def test_env_rendering_logic(self): else: env = create_direct_rl_env(render_interval) except Exception as e: - if "env" in locals(): + if "env" in locals() and hasattr(env, "_is_closed"): env.close() else: - if hasattr(e, "obj") and hasattr(e.obj, "close"): + if hasattr(e, "obj") and hasattr(e.obj, "_is_closed"): e.obj.close() self.fail(f"Failed to set-up the environment {env_type}. Error: {e}") diff --git a/source/extensions/omni.isaac.lab/test/managers/test_event_manager.py b/source/extensions/omni.isaac.lab/test/managers/test_event_manager.py index 89f43e7060..5a92b7c28d 100644 --- a/source/extensions/omni.isaac.lab/test/managers/test_event_manager.py +++ b/source/extensions/omni.isaac.lab/test/managers/test_event_manager.py @@ -134,6 +134,15 @@ def test_active_terms(self): self.assertEqual(len(self.event_man.active_terms["reset"]), 1) self.assertEqual(len(self.event_man.active_terms["custom"]), 2) + def test_config_empty(self): + """Test the creation of reward manager with empty config.""" + self.event_man = EventManager(None, self.env) + self.assertEqual(len(self.event_man.active_terms), 0) + + # print the expected string + print() + print(self.event_man) + def test_invalid_event_func_module(self): """Test the handling of invalid event function's module in string representation.""" cfg = { diff --git a/source/extensions/omni.isaac.lab/test/managers/test_reward_manager.py b/source/extensions/omni.isaac.lab/test/managers/test_reward_manager.py index 381886776f..af5d35d858 100644 --- a/source/extensions/omni.isaac.lab/test/managers/test_reward_manager.py +++ b/source/extensions/omni.isaac.lab/test/managers/test_reward_manager.py @@ -12,6 +12,7 @@ """Rest everything follows.""" +import torch import unittest from collections import namedtuple @@ -123,6 +124,21 @@ def test_compute(self): self.assertEqual(float(rewards[0]), expected_reward) self.assertEqual(tuple(rewards.shape), (self.env.num_envs,)) + def test_config_empty(self): + """Test the creation of reward manager with empty config.""" + self.rew_man = RewardManager(None, self.env) + self.assertEqual(len(self.rew_man.active_terms), 0) + + # print the expected string + print() + print(self.rew_man) + + # compute reward + rewards = self.rew_man.compute(dt=self.env.dt) + + # check all rewards are zero + torch.testing.assert_close(rewards, torch.zeros_like(rewards)) + def test_active_terms(self): """Test the correct reading of active terms.""" cfg = { diff --git a/source/extensions/omni.isaac.lab/test/scene/test_interactive_scene.py b/source/extensions/omni.isaac.lab/test/scene/test_interactive_scene.py index 4e9d08e54b..70d149fd1e 100644 --- a/source/extensions/omni.isaac.lab/test/scene/test_interactive_scene.py +++ b/source/extensions/omni.isaac.lab/test/scene/test_interactive_scene.py @@ -40,7 +40,7 @@ class MySceneCfg(InteractiveSceneCfg): prim_path="/World/Robot", spawn=sim_utils.UsdFileCfg(usd_path=f"{ISAAC_NUCLEUS_DIR}/Robots/Simple/revolute_articulation.usd"), actuators={ - "joint": ImplicitActuatorCfg(), + "joint": ImplicitActuatorCfg(joint_names_expr=[".*"], stiffness=100.0, damping=1.0), }, ) # rigid object diff --git a/source/extensions/omni.isaac.lab/test/utils/test_configclass.py b/source/extensions/omni.isaac.lab/test/utils/test_configclass.py index 1ee984ce52..f899534033 100644 --- a/source/extensions/omni.isaac.lab/test/utils/test_configclass.py +++ b/source/extensions/omni.isaac.lab/test/utils/test_configclass.py @@ -329,6 +329,45 @@ class NestedDictAndListCfg: list_1: list[EnvCfg] = [EnvCfg(), EnvCfg()] +""" +Dummy configuration: Missing attributes +""" + + +@configclass +class MissingParentDemoCfg: + """Dummy parent configuration with missing fields.""" + + a: int = MISSING + + @configclass + class InsideClassCfg: + """Inner dummy configuration.""" + + @configclass + class InsideInsideClassCfg: + """Inner inner dummy configuration.""" + + a: str = MISSING + + inside: str = MISSING + inside_dict = {"a": MISSING} + inside_nested_dict = {"a": {"b": "hello", "c": MISSING, "d": InsideInsideClassCfg()}} + inside_tuple = (10, MISSING, 20) + inside_list = [MISSING, MISSING, 2] + + b: InsideClassCfg = InsideClassCfg() + + +@configclass +class MissingChildDemoCfg(MissingParentDemoCfg): + """Dummy child configuration with missing fields.""" + + c: Callable = MISSING + d: int | None = None + e: dict = {} + + """ Test solutions: Basic """ @@ -404,6 +443,22 @@ class NestedDictAndListCfg: "func_in_dict": {"func": "__main__:dummy_function2"}, } +""" +Test solutions: Missing attributes +""" + +validity_expected_fields = [ + "a", + "b.inside", + "b.inside_dict.a", + "b.inside_nested_dict.a.c", + "b.inside_nested_dict.a.d.a", + "b.inside_tuple[1]", + "b.inside_list[0]", + "b.inside_list[1]", + "c", +] + """ Test fixtures. """ @@ -888,6 +943,22 @@ def test_config_md5_hash(self): self.assertEqual(md5_hash_1, md5_hash_2) + def test_validity(self): + """Check that invalid configurations raise errors.""" + + cfg = MissingChildDemoCfg() + + with self.assertRaises(TypeError) as context: + cfg.validate() + + # check that the expected missing fields are in the error message + error_message = str(context.exception) + for elem in validity_expected_fields: + self.assertIn(elem, error_message) + + # check that no more than the expected missing fields are in the error message + self.assertEqual(len(error_message.split("\n")) - 2, len(validity_expected_fields)) + if __name__ == "__main__": run_tests() diff --git a/source/extensions/omni.isaac.lab_tasks/config/extension.toml b/source/extensions/omni.isaac.lab_tasks/config/extension.toml index 002927c1b2..a739dc74a0 100644 --- a/source/extensions/omni.isaac.lab_tasks/config/extension.toml +++ b/source/extensions/omni.isaac.lab_tasks/config/extension.toml @@ -1,7 +1,7 @@ [package] # Note: Semantic Versioning is used: https://semver.org/ -version = "0.10.8" +version = "0.10.9" # Description title = "Isaac Lab Environments" diff --git a/source/extensions/omni.isaac.lab_tasks/docs/CHANGELOG.rst b/source/extensions/omni.isaac.lab_tasks/docs/CHANGELOG.rst index 0f55936604..5bf5d9eeea 100644 --- a/source/extensions/omni.isaac.lab_tasks/docs/CHANGELOG.rst +++ b/source/extensions/omni.isaac.lab_tasks/docs/CHANGELOG.rst @@ -1,6 +1,16 @@ Changelog --------- +0.10.9 (2024-10-22) +~~~~~~~~~~~~~~~~~~~ + +Changed +^^^^^^^ + +* Sets curriculum and commands to None in manager-based environment configurations when not needed. + Earlier, this was done by making an empty configuration object, which is now unnecessary. + + 0.10.8 (2024-10-22) ~~~~~~~~~~~~~~~~~~~ diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/ant/ant_env_cfg.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/ant/ant_env_cfg.py index f12a046305..68f091c515 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/ant/ant_env_cfg.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/ant/ant_env_cfg.py @@ -58,14 +58,6 @@ class MySceneCfg(InteractiveSceneCfg): ## -@configclass -class CommandsCfg: - """Command terms for the MDP.""" - - # no commands for this MDP - null = mdp.NullCommandCfg() - - @configclass class ActionsCfg: """Action specifications for the MDP.""" @@ -163,13 +155,6 @@ class TerminationsCfg: torso_height = DoneTerm(func=mdp.root_height_below_minimum, params={"minimum_height": 0.31}) -@configclass -class CurriculumCfg: - """Curriculum terms for the MDP.""" - - pass - - @configclass class AntEnvCfg(ManagerBasedRLEnvCfg): """Configuration for the MuJoCo-style Ant walking environment.""" @@ -179,13 +164,10 @@ class AntEnvCfg(ManagerBasedRLEnvCfg): # Basic settings observations: ObservationsCfg = ObservationsCfg() actions: ActionsCfg = ActionsCfg() - commands: CommandsCfg = CommandsCfg() - # MDP settings rewards: RewardsCfg = RewardsCfg() terminations: TerminationsCfg = TerminationsCfg() events: EventCfg = EventCfg() - curriculum: CurriculumCfg = CurriculumCfg() def __post_init__(self): """Post initialization.""" diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/cartpole/cartpole_env_cfg.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/cartpole/cartpole_env_cfg.py index 8c92d3d5ae..84d88cba10 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/cartpole/cartpole_env_cfg.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/cartpole/cartpole_env_cfg.py @@ -60,14 +60,6 @@ class CartpoleSceneCfg(InteractiveSceneCfg): ## -@configclass -class CommandsCfg: - """Command terms for the MDP.""" - - # no commands for this MDP - null = mdp.NullCommandCfg() - - @configclass class ActionsCfg: """Action specifications for the MDP.""" @@ -162,13 +154,6 @@ class TerminationsCfg: ) -@configclass -class CurriculumCfg: - """Configuration for the curriculum.""" - - pass - - ## # Environment configuration ## @@ -185,11 +170,8 @@ class CartpoleEnvCfg(ManagerBasedRLEnvCfg): actions: ActionsCfg = ActionsCfg() events: EventCfg = EventCfg() # MDP settings - curriculum: CurriculumCfg = CurriculumCfg() rewards: RewardsCfg = RewardsCfg() terminations: TerminationsCfg = TerminationsCfg() - # No command generator - commands: CommandsCfg = CommandsCfg() # Post initialization def __post_init__(self) -> None: diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/humanoid/humanoid_env_cfg.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/humanoid/humanoid_env_cfg.py index f376811a43..e02dd94edb 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/humanoid/humanoid_env_cfg.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/humanoid/humanoid_env_cfg.py @@ -102,14 +102,6 @@ class MySceneCfg(InteractiveSceneCfg): ## -@configclass -class CommandsCfg: - """Command terms for the MDP.""" - - # no commands for this MDP - null = mdp.NullCommandCfg() - - @configclass class ActionsCfg: """Action specifications for the MDP.""" @@ -248,13 +240,6 @@ class TerminationsCfg: torso_height = DoneTerm(func=mdp.root_height_below_minimum, params={"minimum_height": 0.8}) -@configclass -class CurriculumCfg: - """Curriculum terms for the MDP.""" - - pass - - @configclass class HumanoidEnvCfg(ManagerBasedRLEnvCfg): """Configuration for the MuJoCo-style Humanoid walking environment.""" @@ -264,13 +249,10 @@ class HumanoidEnvCfg(ManagerBasedRLEnvCfg): # Basic settings observations: ObservationsCfg = ObservationsCfg() actions: ActionsCfg = ActionsCfg() - commands: CommandsCfg = CommandsCfg() - # MDP settings rewards: RewardsCfg = RewardsCfg() terminations: TerminationsCfg = TerminationsCfg() events: EventCfg = EventCfg() - curriculum: CurriculumCfg = CurriculumCfg() def __post_init__(self): """Post initialization.""" diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/spot/flat_env_cfg.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/spot/flat_env_cfg.py index 986b10da33..fba2e69ee1 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/spot/flat_env_cfg.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/spot/flat_env_cfg.py @@ -293,13 +293,6 @@ class SpotTerminationsCfg: ) -@configclass -class SpotCurriculumCfg: - """Curriculum terms for the MDP.""" - - pass - - @configclass class SpotFlatEnvCfg(LocomotionVelocityRoughEnvCfg): @@ -312,7 +305,6 @@ class SpotFlatEnvCfg(LocomotionVelocityRoughEnvCfg): rewards: SpotRewardsCfg = SpotRewardsCfg() terminations: SpotTerminationsCfg = SpotTerminationsCfg() events: SpotEventCfg = SpotEventCfg() - curriculum: SpotCurriculumCfg = SpotCurriculumCfg() # Viewer viewer = ViewerCfg(eye=(10.5, 10.5, 0.3), origin_type="world", env_index=0, asset_name="robot") diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/cabinet/cabinet_env_cfg.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/cabinet/cabinet_env_cfg.py index 7faa94601a..56c7e5d2b8 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/cabinet/cabinet_env_cfg.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/cabinet/cabinet_env_cfg.py @@ -123,13 +123,6 @@ class CabinetSceneCfg(InteractiveSceneCfg): ## -@configclass -class CommandsCfg: - """Command terms for the MDP.""" - - null_command = mdp.NullCommandCfg() - - @configclass class ActionsCfg: """Action specifications for the MDP.""" @@ -267,7 +260,6 @@ class CabinetEnvCfg(ManagerBasedRLEnvCfg): # Basic settings observations: ObservationsCfg = ObservationsCfg() actions: ActionsCfg = ActionsCfg() - commands: CommandsCfg = CommandsCfg() # MDP settings rewards: RewardsCfg = RewardsCfg() terminations: TerminationsCfg = TerminationsCfg() diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/navigation/config/anymal_c/navigation_env_cfg.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/navigation/config/anymal_c/navigation_env_cfg.py index 6f5f00a025..c13875c545 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/navigation/config/anymal_c/navigation_env_cfg.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/navigation/config/anymal_c/navigation_env_cfg.py @@ -107,13 +107,6 @@ class CommandsCfg: ) -@configclass -class CurriculumCfg: - """Curriculum terms for the MDP.""" - - pass - - @configclass class TerminationsCfg: """Termination terms for the MDP.""" @@ -127,14 +120,16 @@ class TerminationsCfg: @configclass class NavigationEnvCfg(ManagerBasedRLEnvCfg): + """Configuration for the navigation environment.""" + + # environment settings scene: SceneEntityCfg = LOW_LEVEL_ENV_CFG.scene - commands: CommandsCfg = CommandsCfg() actions: ActionsCfg = ActionsCfg() observations: ObservationsCfg = ObservationsCfg() - rewards: RewardsCfg = RewardsCfg() events: EventCfg = EventCfg() - - curriculum: CurriculumCfg = CurriculumCfg() + # mdp settings + commands: CommandsCfg = CommandsCfg() + rewards: RewardsCfg = RewardsCfg() terminations: TerminationsCfg = TerminationsCfg() def __post_init__(self): diff --git a/source/extensions/omni.isaac.lab_tasks/test/test_environment_determinism.py b/source/extensions/omni.isaac.lab_tasks/test/test_environment_determinism.py index 3346e8284d..3aa2977935 100644 --- a/source/extensions/omni.isaac.lab_tasks/test/test_environment_determinism.py +++ b/source/extensions/omni.isaac.lab_tasks/test/test_environment_determinism.py @@ -101,13 +101,20 @@ def _obtain_transition_tuples( """Run random actions and obtain transition tuples after fixed number of steps.""" # create a new stage omni.usd.get_context().new_stage() - # parse configuration - env_cfg = parse_env_cfg(task_name, device=device, num_envs=num_envs) - # set seed - env_cfg.seed = 42 - - # create environment - env = gym.make(task_name, cfg=env_cfg) + try: + # parse configuration + env_cfg = parse_env_cfg(task_name, device=device, num_envs=num_envs) + # set seed + env_cfg.seed = 42 + # create environment + env = gym.make(task_name, cfg=env_cfg) + except Exception as e: + if "env" in locals() and hasattr(env, "_is_closed"): + env.close() + else: + if hasattr(e, "obj") and hasattr(e.obj, "_is_closed"): + e.obj.close() + self.fail(f"Failed to set-up the environment for task {task_name}. Error: {e}") # disable control on stop env.unwrapped.sim._app_control_on_stop_handle = None # type: ignore diff --git a/source/extensions/omni.isaac.lab_tasks/test/test_environments.py b/source/extensions/omni.isaac.lab_tasks/test/test_environments.py index cfb540e1af..440b35d7c8 100644 --- a/source/extensions/omni.isaac.lab_tasks/test/test_environments.py +++ b/source/extensions/omni.isaac.lab_tasks/test/test_environments.py @@ -100,10 +100,10 @@ def _check_random_actions(self, task_name: str, device: str, num_envs: int, num_ # create environment env = gym.make(task_name, cfg=env_cfg) except Exception as e: - if "env" in locals(): + if "env" in locals() and hasattr(env, "_is_closed"): env.close() else: - if hasattr(e, "obj") and hasattr(e.obj, "close"): + if hasattr(e, "obj") and hasattr(e.obj, "_is_closed"): e.obj.close() self.fail(f"Failed to set-up the environment for task {task_name}. Error: {e}") diff --git a/source/extensions/omni.isaac.lab_tasks/test/test_multi_agent_environments.py b/source/extensions/omni.isaac.lab_tasks/test/test_multi_agent_environments.py index 11a20ef9a3..d65a39bc45 100644 --- a/source/extensions/omni.isaac.lab_tasks/test/test_multi_agent_environments.py +++ b/source/extensions/omni.isaac.lab_tasks/test/test_multi_agent_environments.py @@ -39,7 +39,6 @@ def setUpClass(cls): cls.registered_tasks.append(task_spec.id) # sort environments by name cls.registered_tasks.sort() - cls.registered_tasks = ["Isaac-Shadow-Hand-Over-Direct-v0"] # print all existing task names print(">>> All registered environments:", cls.registered_tasks) @@ -97,10 +96,10 @@ def _check_random_actions(self, task_name: str, device: str, num_envs: int, num_ # create environment env: DirectMARLEnv = gym.make(task_name, cfg=env_cfg) except Exception as e: - if "env" in locals(): + if "env" in locals() and hasattr(env, "_is_closed"): env.close() else: - if hasattr(e, "obj") and hasattr(e.obj, "close"): + if hasattr(e, "obj") and hasattr(e.obj, "_is_closed"): e.obj.close() self.fail(f"Failed to set-up the environment for task {task_name}. Error: {e}") diff --git a/source/extensions/omni.isaac.lab_tasks/test/wrappers/test_rl_games_wrapper.py b/source/extensions/omni.isaac.lab_tasks/test/wrappers/test_rl_games_wrapper.py index 3c05b797db..0cbf01ea75 100644 --- a/source/extensions/omni.isaac.lab_tasks/test/wrappers/test_rl_games_wrapper.py +++ b/source/extensions/omni.isaac.lab_tasks/test/wrappers/test_rl_games_wrapper.py @@ -69,10 +69,10 @@ def test_random_actions(self): # wrap environment env = RlGamesVecEnvWrapper(env, "cuda:0", 100, 100) except Exception as e: - if "env" in locals(): + if "env" in locals() and hasattr(env, "_is_closed"): env.close() else: - if hasattr(e, "obj") and hasattr(e.obj, "close"): + if hasattr(e, "obj") and hasattr(e.obj, "_is_closed"): e.obj.close() self.fail(f"Failed to set-up the environment for task {task_name}. Error: {e}") diff --git a/source/extensions/omni.isaac.lab_tasks/test/wrappers/test_rsl_rl_wrapper.py b/source/extensions/omni.isaac.lab_tasks/test/wrappers/test_rsl_rl_wrapper.py index 271747d2ac..c4e7c797f2 100644 --- a/source/extensions/omni.isaac.lab_tasks/test/wrappers/test_rsl_rl_wrapper.py +++ b/source/extensions/omni.isaac.lab_tasks/test/wrappers/test_rsl_rl_wrapper.py @@ -69,10 +69,10 @@ def test_random_actions(self): # wrap environment env = RslRlVecEnvWrapper(env) except Exception as e: - if "env" in locals(): + if "env" in locals() and hasattr(env, "_is_closed"): env.close() else: - if hasattr(e, "obj") and hasattr(e.obj, "close"): + if hasattr(e, "obj") and hasattr(e.obj, "_is_closed"): e.obj.close() self.fail(f"Failed to set-up the environment for task {task_name}. Error: {e}") diff --git a/source/extensions/omni.isaac.lab_tasks/test/wrappers/test_sb3_wrapper.py b/source/extensions/omni.isaac.lab_tasks/test/wrappers/test_sb3_wrapper.py index f6d9d1abb4..d0a9aa507c 100644 --- a/source/extensions/omni.isaac.lab_tasks/test/wrappers/test_sb3_wrapper.py +++ b/source/extensions/omni.isaac.lab_tasks/test/wrappers/test_sb3_wrapper.py @@ -70,10 +70,10 @@ def test_random_actions(self): # wrap environment env = Sb3VecEnvWrapper(env) except Exception as e: - if "env" in locals(): + if "env" in locals() and hasattr(env, "_is_closed"): env.close() else: - if hasattr(e, "obj") and hasattr(e.obj, "close"): + if hasattr(e, "obj") and hasattr(e.obj, "_is_closed"): e.obj.close() self.fail(f"Failed to set-up the environment for task {task_name}. Error: {e}") diff --git a/source/extensions/omni.isaac.lab_tasks/test/wrappers/test_skrl_wrapper.py b/source/extensions/omni.isaac.lab_tasks/test/wrappers/test_skrl_wrapper.py index 2c925d34b4..58085c1671 100644 --- a/source/extensions/omni.isaac.lab_tasks/test/wrappers/test_skrl_wrapper.py +++ b/source/extensions/omni.isaac.lab_tasks/test/wrappers/test_skrl_wrapper.py @@ -68,10 +68,10 @@ def test_random_actions(self): # wrap environment env = SkrlVecEnvWrapper(env) except Exception as e: - if "env" in locals(): + if "env" in locals() and hasattr(env, "_is_closed"): env.close() else: - if hasattr(e, "obj") and hasattr(e.obj, "close"): + if hasattr(e, "obj") and hasattr(e.obj, "_is_closed"): e.obj.close() self.fail(f"Failed to set-up the environment for task {task_name}. Error: {e}") # reset environment From a56291d07a28548784f46aed16a4b219c9b57e39 Mon Sep 17 00:00:00 2001 From: Dorsa Rohani Date: Wed, 23 Oct 2024 07:51:48 -0400 Subject: [PATCH 033/111] Fixes broken URLs in markdown files (#1272) # Description Fixes the broken URLs in README.md and CONTRIBUTING.md ## Type of change - [x] Bug fix (non-breaking change which fixes an issue) ## Screenshots Not applicable for this change ## Checklist - [x] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [x] I have added tests that prove my fix is effective or that my feature works - [x] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --------- Co-authored-by: Kelly Guo --- CONTRIBUTING.md | 2 +- CONTRIBUTORS.md | 1 + README.md | 4 ++-- 3 files changed, 4 insertions(+), 3 deletions(-) diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md index b75e4e5bc1..b837c0df92 100644 --- a/CONTRIBUTING.md +++ b/CONTRIBUTING.md @@ -5,4 +5,4 @@ the framework more mature and useful for everyone. These may happen in forms of design proposals and more. For general information on how to contribute see -. +. diff --git a/CONTRIBUTORS.md b/CONTRIBUTORS.md index a47a1ab8a8..a0e671618c 100644 --- a/CONTRIBUTORS.md +++ b/CONTRIBUTORS.md @@ -42,6 +42,7 @@ Guidelines for modifications: * Calvin Yu * Chenyu Yang * David Yang +* Dorsa Rohani * Gary Lvov * Giulio Romualdi * HoJin Jeon diff --git a/README.md b/README.md index 590fd5aeb7..04f5106105 100644 --- a/README.md +++ b/README.md @@ -25,11 +25,11 @@ installation steps, features, tutorials, and how to set up your project with Isa We wholeheartedly welcome contributions from the community to make this framework mature and useful for everyone. These may happen as bug reports, feature requests, or code contributions. For details, please check our -[contribution guidelines](https://isaac-sim.github.io/IsaacLab/source/refs/contributing.html). +[contribution guidelines](https://isaac-sim.github.io/IsaacLab/main/source/refs/contributing.html). ## Troubleshooting -Please see the [troubleshooting](https://isaac-sim.github.io/IsaacLab/source/refs/troubleshooting.html) section for +Please see the [troubleshooting](https://isaac-sim.github.io/IsaacLab/main/source/refs/troubleshooting.html) section for common fixes or [submit an issue](https://github.com/isaac-sim/IsaacLab/issues). For issues related to Isaac Sim, we recommend checking its [documentation](https://docs.omniverse.nvidia.com/app_isaacsim/app_isaacsim/overview.html) From 77133d54d46fb58888120bff67488a21f09b231b Mon Sep 17 00:00:00 2001 From: Kelly Guo Date: Thu, 24 Oct 2024 07:09:52 -0400 Subject: [PATCH 034/111] Adds a render config to the simulation and tiledCamera limitations to the docs (#1246) # Description This change adds a render config to the simulation context and highlights current limitations and workarounds for issues with the TiledCamera class. ## Type of change - This change requires a documentation update ## Checklist - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [x] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [x] I have added tests that prove my fix is effective or that my feature works - [x] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [x] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --- .github/workflows/docs.yaml | 4 + docs/index.rst | 1 - docs/source/api/lab/omni.isaac.lab.sim.rst | 6 + docs/source/features/hydra.rst | 6 +- docs/source/features/tiled_rendering.rst | 38 ++++- docs/source/overview/core-concepts/index.rst | 2 + .../omni.isaac.lab/config/extension.toml | 2 +- .../omni.isaac.lab/docs/CHANGELOG.rst | 10 ++ .../omni/isaac/lab/sim/__init__.py | 2 +- .../omni/isaac/lab/sim/simulation_cfg.py | 51 ++++++ .../omni/isaac/lab/sim/simulation_context.py | 20 +++ .../test/sim/test_simulation_render_config.py | 154 ++++++++++++++++++ 12 files changed, 289 insertions(+), 7 deletions(-) create mode 100644 source/extensions/omni.isaac.lab/test/sim/test_simulation_render_config.py diff --git a/.github/workflows/docs.yaml b/.github/workflows/docs.yaml index b7873872c8..51a9fbfd98 100644 --- a/.github/workflows/docs.yaml +++ b/.github/workflows/docs.yaml @@ -2,6 +2,10 @@ name: Build & deploy docs on: push: + branches: + - main + pull_request: + types: [opened, synchronize, reopened] concurrency: group: ${{ github.workflow }}-${{ github.ref }} diff --git a/docs/index.rst b/docs/index.rst index 873ca677cd..1d88042df2 100644 --- a/docs/index.rst +++ b/docs/index.rst @@ -98,7 +98,6 @@ Table of Contents source/features/multi_gpu source/features/tiled_rendering source/features/reproducibility - .. source/features/motion_generators .. toctree:: :maxdepth: 1 diff --git a/docs/source/api/lab/omni.isaac.lab.sim.rst b/docs/source/api/lab/omni.isaac.lab.sim.rst index 4e37e33b4a..b2b582c68b 100644 --- a/docs/source/api/lab/omni.isaac.lab.sim.rst +++ b/docs/source/api/lab/omni.isaac.lab.sim.rst @@ -19,6 +19,7 @@ SimulationContext SimulationCfg PhysxCfg + RenderCfg .. rubric:: Functions @@ -46,6 +47,11 @@ Simulation Configuration :show-inheritance: :exclude-members: __init__ +.. autoclass:: RenderCfg + :members: + :show-inheritance: + :exclude-members: __init__ + Simulation Context Builder -------------------------- diff --git a/docs/source/features/hydra.rst b/docs/source/features/hydra.rst index 89673dbe35..577eb7a6ec 100644 --- a/docs/source/features/hydra.rst +++ b/docs/source/features/hydra.rst @@ -89,8 +89,8 @@ Elements in dictionaries are handled as a parameters in the hierarchy. For examp .. literalinclude:: ../../../source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/cartpole/cartpole_env_cfg.py :language: python - :lines: 99-111 - :emphasize-lines: 10 + :lines: 90-114 + :emphasize-lines: 11 the ``position_range`` parameter can be modified with ``env.events.reset_cart_position.params.position_range="[-2.0, 2.0]"``. This example shows two noteworthy points: @@ -112,7 +112,7 @@ For example, for the configuration of the Cartpole camera depth environment: :language: python :start-at: class CartpoleDepthCameraEnvCfg :end-at: tiled_camera.width - :emphasize-lines: 16 + :emphasize-lines: 10, 15 If the user were to modify the width of the camera, i.e. ``env.tiled_camera.width=128``, then the parameter ``env.observation_space=[80,128,1]`` must be updated and given as input as well. diff --git a/docs/source/features/tiled_rendering.rst b/docs/source/features/tiled_rendering.rst index 55d22561a4..d8ee1d1118 100644 --- a/docs/source/features/tiled_rendering.rst +++ b/docs/source/features/tiled_rendering.rst @@ -8,7 +8,7 @@ Tiled-Camera Rendering This feature is only available from Isaac Sim version 4.2.0 onwards. Tiled rendering in combination with image processing networks require heavy memory resources, especially - at larger resolutions. We recommend running at 512 cameras in the scene on RTX 4090 GPUs or similar. + at larger resolutions. We recommend running 512 cameras in the scene on RTX 4090 GPUs or similar. Tiled rendering APIs provide a vectorized interface for collecting data from camera sensors. @@ -129,3 +129,39 @@ Instance Segmentation - If ``colorize_instance_segmentation=True`` in the camera config, a 4-channel RGBA image will be returned with dimension (B, H, W, 4) and type ``torch.uint8``. The info ``idToLabels`` dictionary will be the mapping from color to USD prim path of that semantic entity. The info ``idToSemantics`` dictionary will be the mapping from color to semantic labels of that semantic entity. - If ``colorize_instance_segmentation=False``, a buffer of dimension (B, H, W, 1) of type ``torch.int32`` will be returned, containing the instance ID of each pixel. The info ``idToLabels`` dictionary will be the mapping from instance ID to USD prim path of that semantic entity. The info ``idToSemantics`` dictionary will be the mapping from instance ID to semantic labels of that semantic entity. + + +Current Limitations +------------------- + +Due to current limitations in the renderer, we can have only **one** :class:`~sensors.TiledCamera` instance in the scene. +For use cases that require a setup with more than one camera, we can imitate the multi-camera behavior by moving the location +of the camera in between render calls in a step. + +For example, in a stereo vision setup, the below snippet can be implemented: + +.. code-block:: python + + # render image from "first" camera + camera_data_1 = self._tiled_camera.data.output["rgb"].clone() / 255.0 + # update camera transform to the "second" camera location + self._tiled_camera.set_world_poses( + positions=pos, + orientations=rot, + convention="world" + ) + # step the renderer + self.sim.render() + self._tiled_camera.update(0, force_recompute=True) + # render image from "second" camera + camera_data_2 = self._tiled_camera.data.output["rgb"].clone() / 255.0 + +Note that this approach still limits the rendering resolution to be identical for all cameras. Currently, there is no workaround +to achieve different resolution images using :class:`~sensors.TiledCamera`. The best approach is to use the largest resolution out of all of the +desired resolutions and add additional scaling or cropping operations to the rendered output as a post-processing step. + +In addition, there may be visible quality differences when comparing render outputs of different numbers of environments. +Currently, any combined resolution that has a width less than 265 pixels or height less than 265 will automatically switch +to the DLAA anti-aliasing mode, which does not perform up-sampling during anti-aliasing. For resolutions larger than 265 in both +width and height dimensions, we default to using the "performance" DLSS mode for anti-aliasing for performance benefits. +Anti-aliasing modes and other rendering parameters can be specified in the :class:`~sim.RenderCfg`. diff --git a/docs/source/overview/core-concepts/index.rst b/docs/source/overview/core-concepts/index.rst index 488b5ee221..179860080d 100644 --- a/docs/source/overview/core-concepts/index.rst +++ b/docs/source/overview/core-concepts/index.rst @@ -9,3 +9,5 @@ This section we introduce core concepts in Isaac Lab. task_workflows actuators + +# motion_generators diff --git a/source/extensions/omni.isaac.lab/config/extension.toml b/source/extensions/omni.isaac.lab/config/extension.toml index db8ec4d6b1..a1856cd636 100644 --- a/source/extensions/omni.isaac.lab/config/extension.toml +++ b/source/extensions/omni.isaac.lab/config/extension.toml @@ -1,7 +1,7 @@ [package] # Note: Semantic Versioning is used: https://semver.org/ -version = "0.27.0" +version = "0.27.1" # Description title = "Isaac Lab framework for Robot Learning" diff --git a/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst b/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst index ab1a562b1e..c61f2ac870 100644 --- a/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst +++ b/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst @@ -1,6 +1,16 @@ Changelog --------- +0.27.1 (2024-10-20) +~~~~~~~~~~~~~~~~~~~ + +Added +^^^^^ + +* Added :class:`~omni.isaac.lab.sim.RenderCfg` and the attribute :attr:`~omni.isaac.lab.sim.SimulationCfg.render` for + specifying render related settings. + + 0.27.0 (2024-10-14) ~~~~~~~~~~~~~~~~~~~ diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/__init__.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/__init__.py index b722e083ea..2228a2322d 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/__init__.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/__init__.py @@ -28,7 +28,7 @@ from .converters import * # noqa: F401, F403 from .schemas import * # noqa: F401, F403 -from .simulation_cfg import PhysxCfg, SimulationCfg # noqa: F401, F403 +from .simulation_cfg import PhysxCfg, RenderCfg, SimulationCfg # noqa: F401, F403 from .simulation_context import SimulationContext, build_simulation_context # noqa: F401, F403 from .spawners import * # noqa: F401, F403 from .utils import * # noqa: F401, F403 diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/simulation_cfg.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/simulation_cfg.py index 0705f5264d..a75d1f028b 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/simulation_cfg.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/simulation_cfg.py @@ -152,6 +152,54 @@ class PhysxCfg: """Size of particle contacts stream buffer allocated in pinned host memory. Default is 2 ** 20.""" +@configclass +class RenderCfg: + """Configuration for Omniverse RTX Renderer. + + These parameters are used to configure the Omniverse RTX Renderer. + For more information, see the `Omniverse RTX Renderer documentation`_. + + .. _Omniverse RTX Renderer documentation: https://docs.omniverse.nvidia.com/materials-and-rendering/latest/rtx-renderer.html + """ + + enable_translucency: bool = False + """Enables translucency for specular transmissive surfaces such as glass at the cost of some performance. Default is False.""" + + enable_reflections: bool = False + """Enables reflections at the cost of some performance. Default is False.""" + + enable_global_illumination: bool = False + """Enables Diffused Global Illumination at the cost of some performance. Default is False.""" + + antialiasing_mode: Literal["Off", "FXAA", "DLSS", "TAA", "DLAA"] = "DLSS" + """Selects the anti-aliasing mode to use. Defaults to DLSS.""" + + enable_dlssg: bool = False + """"Enables the use of DLSS-G. + DLSS Frame Generation boosts performance by using AI to generate more frames. + DLSS analyzes sequential frames and motion data to create additional high quality frames. + This feature requires an Ada Lovelace architecture GPU. + Enabling this feature also enables additional thread-related activities, which can hurt performance. + Default is False.""" + + dlss_mode: Literal[0, 1, 2, 3] = 0 + """For DLSS anti-aliasing, selects the performance/quality tradeoff mode. + Valid values are 0 (Performance), 1 (Balanced), 2 (Quality), or 3 (Auto). Default is 0.""" + + enable_direct_lighting: bool = True + """Enable direct light contributions from lights.""" + + samples_per_pixel: int = 1 + """Defines the Direct Lighting samples per pixel. + Higher values increase the direct lighting quality at the cost of performance. Default is 1.""" + + enable_shadows: bool = True + """Enables shadows at the cost of performance. When disabled, lights will not cast shadows. Defaults to True.""" + + enable_ambient_occlusion: bool = False + """Enables ambient occlusion at the cost of some performance. Default is False.""" + + @configclass class SimulationCfg: """Configuration for simulation physics.""" @@ -234,3 +282,6 @@ class SimulationCfg: The material is created at the path: ``{physics_prim_path}/defaultMaterial``. """ + + render: RenderCfg = RenderCfg() + """Render settings. Default is RenderCfg().""" diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/simulation_context.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/simulation_context.py index ce1278f5fc..104afc538d 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/simulation_context.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/simulation_context.py @@ -154,6 +154,26 @@ def __init__(self, cfg: SimulationCfg | None = None): # flag for whether any GUI will be rendered (local, livestreamed or viewport) self._has_gui = self._local_gui or self._livestream_gui + # apply render settings from render config + carb_settings_iface.set_bool("/rtx/translucency/enabled", self.cfg.render.enable_translucency) + carb_settings_iface.set_bool("/rtx/reflections/enabled", self.cfg.render.enable_reflections) + carb_settings_iface.set_bool("/rtx/indirectDiffuse/enabled", self.cfg.render.enable_global_illumination) + carb_settings_iface.set_bool("/rtx/transient/dlssg/enabled", self.cfg.render.enable_dlssg) + carb_settings_iface.set_int("/rtx/post/dlss/execMode", self.cfg.render.dlss_mode) + carb_settings_iface.set_bool("/rtx/directLighting/enabled", self.cfg.render.enable_direct_lighting) + carb_settings_iface.set_int( + "/rtx/directLighting/sampledLighting/samplesPerPixel", self.cfg.render.samples_per_pixel + ) + carb_settings_iface.set_bool("/rtx/shadows/enabled", self.cfg.render.enable_shadows) + carb_settings_iface.set_bool("/rtx/ambientOcclusion/enabled", self.cfg.render.enable_ambient_occlusion) + # set denoiser mode + try: + import omni.replicator.core as rep + + rep.settings.set_render_rtx_realtime(antialiasing=self.cfg.render.antialiasing_mode) + except Exception: + pass + # store the default render mode if not self._has_gui and not self._offscreen_render: # set default render mode diff --git a/source/extensions/omni.isaac.lab/test/sim/test_simulation_render_config.py b/source/extensions/omni.isaac.lab/test/sim/test_simulation_render_config.py new file mode 100644 index 0000000000..cd885a75a0 --- /dev/null +++ b/source/extensions/omni.isaac.lab/test/sim/test_simulation_render_config.py @@ -0,0 +1,154 @@ +# Copyright (c) 2022-2024, The Isaac Lab Project Developers. +# All rights reserved. +# +# SPDX-License-Identifier: BSD-3-Clause + + +"""Launch Isaac Sim Simulator first.""" + +from omni.isaac.lab.app import AppLauncher, run_tests + +# launch omniverse app +app_launcher = AppLauncher(headless=True, enable_cameras=True) +simulation_app = app_launcher.app + +"""Rest everything follows.""" + +import unittest + +import carb + +from omni.isaac.lab.sim.simulation_cfg import RenderCfg, SimulationCfg +from omni.isaac.lab.sim.simulation_context import SimulationContext + + +class TestSimulationRenderConfig(unittest.TestCase): + """Tests for simulation context render config.""" + + """ + Tests + """ + + def test_render_cfg(self): + """Test that the simulation context is created with the correct render cfg.""" + enable_translucency = True + enable_reflections = True + enable_global_illumination = True + antialiasing_mode = "DLAA" + enable_dlssg = True + dlss_mode = 3 + enable_direct_lighting = True + samples_per_pixel = 4 + enable_shadows = True + enable_ambient_occlusion = True + + render_cfg = RenderCfg( + enable_translucency=enable_translucency, + enable_reflections=enable_reflections, + enable_global_illumination=enable_global_illumination, + antialiasing_mode=antialiasing_mode, + enable_dlssg=enable_dlssg, + dlss_mode=dlss_mode, + enable_direct_lighting=enable_direct_lighting, + samples_per_pixel=samples_per_pixel, + enable_shadows=enable_shadows, + enable_ambient_occlusion=enable_ambient_occlusion, + ) + + cfg = SimulationCfg(render=render_cfg) + + sim = SimulationContext(cfg) + + self.assertEqual(sim.cfg.render.enable_translucency, enable_translucency) + self.assertEqual(sim.cfg.render.enable_reflections, enable_reflections) + self.assertEqual(sim.cfg.render.enable_global_illumination, enable_global_illumination) + self.assertEqual(sim.cfg.render.antialiasing_mode, antialiasing_mode) + self.assertEqual(sim.cfg.render.enable_dlssg, enable_dlssg) + self.assertEqual(sim.cfg.render.dlss_mode, dlss_mode) + self.assertEqual(sim.cfg.render.enable_direct_lighting, enable_direct_lighting) + self.assertEqual(sim.cfg.render.samples_per_pixel, samples_per_pixel) + self.assertEqual(sim.cfg.render.enable_shadows, enable_shadows) + self.assertEqual(sim.cfg.render.enable_ambient_occlusion, enable_ambient_occlusion) + + carb_settings_iface = carb.settings.get_settings() + self.assertEqual(carb_settings_iface.get("/rtx/translucency/enabled"), sim.cfg.render.enable_translucency) + self.assertEqual(carb_settings_iface.get("/rtx/reflections/enabled"), sim.cfg.render.enable_reflections) + self.assertEqual( + carb_settings_iface.get("/rtx/indirectDiffuse/enabled"), sim.cfg.render.enable_global_illumination + ) + self.assertEqual(carb_settings_iface.get("/rtx/transient/dlssg/enabled"), sim.cfg.render.enable_dlssg) + self.assertEqual(carb_settings_iface.get("/rtx/post/dlss/execMode"), sim.cfg.render.dlss_mode) + self.assertEqual(carb_settings_iface.get("/rtx/directLighting/enabled"), sim.cfg.render.enable_direct_lighting) + self.assertEqual( + carb_settings_iface.get("/rtx/directLighting/sampledLighting/samplesPerPixel"), + sim.cfg.render.samples_per_pixel, + ) + self.assertEqual(carb_settings_iface.get("/rtx/shadows/enabled"), sim.cfg.render.enable_shadows) + self.assertEqual( + carb_settings_iface.get("/rtx/ambientOcclusion/enabled"), sim.cfg.render.enable_ambient_occlusion + ) + self.assertEqual(carb_settings_iface.get("/rtx/post/aa/op"), 4) # dlss = 3, dlaa=4 + + def test_render_cfg_defaults(self): + """Test that the simulation context is created with the correct render cfg.""" + enable_translucency = False + enable_reflections = False + enable_global_illumination = False + antialiasing_mode = "DLSS" + enable_dlssg = False + dlss_mode = 0 + enable_direct_lighting = False + samples_per_pixel = 1 + enable_shadows = False + enable_ambient_occlusion = False + + render_cfg = RenderCfg( + enable_translucency=enable_translucency, + enable_reflections=enable_reflections, + enable_global_illumination=enable_global_illumination, + antialiasing_mode=antialiasing_mode, + enable_dlssg=enable_dlssg, + dlss_mode=dlss_mode, + enable_direct_lighting=enable_direct_lighting, + samples_per_pixel=samples_per_pixel, + enable_shadows=enable_shadows, + enable_ambient_occlusion=enable_ambient_occlusion, + ) + + cfg = SimulationCfg(render=render_cfg) + + sim = SimulationContext(cfg) + + self.assertEqual(sim.cfg.render.enable_translucency, enable_translucency) + self.assertEqual(sim.cfg.render.enable_reflections, enable_reflections) + self.assertEqual(sim.cfg.render.enable_global_illumination, enable_global_illumination) + self.assertEqual(sim.cfg.render.antialiasing_mode, antialiasing_mode) + self.assertEqual(sim.cfg.render.enable_dlssg, enable_dlssg) + self.assertEqual(sim.cfg.render.dlss_mode, dlss_mode) + self.assertEqual(sim.cfg.render.enable_direct_lighting, enable_direct_lighting) + self.assertEqual(sim.cfg.render.samples_per_pixel, samples_per_pixel) + self.assertEqual(sim.cfg.render.enable_shadows, enable_shadows) + self.assertEqual(sim.cfg.render.enable_ambient_occlusion, enable_ambient_occlusion) + + carb_settings_iface = carb.settings.get_settings() + self.assertEqual(carb_settings_iface.get("/rtx/translucency/enabled"), sim.cfg.render.enable_translucency) + self.assertEqual(carb_settings_iface.get("/rtx/reflections/enabled"), sim.cfg.render.enable_reflections) + self.assertEqual( + carb_settings_iface.get("/rtx/indirectDiffuse/enabled"), sim.cfg.render.enable_global_illumination + ) + self.assertEqual(carb_settings_iface.get("/rtx/transient/dlssg/enabled"), sim.cfg.render.enable_dlssg) + self.assertEqual(carb_settings_iface.get("/rtx/post/dlss/execMode"), sim.cfg.render.dlss_mode) + self.assertEqual(carb_settings_iface.get("/rtx/directLighting/enabled"), sim.cfg.render.enable_direct_lighting) + self.assertEqual( + carb_settings_iface.get("/rtx/directLighting/sampledLighting/samplesPerPixel"), + sim.cfg.render.samples_per_pixel, + ) + self.assertEqual(carb_settings_iface.get("/rtx/shadows/enabled"), sim.cfg.render.enable_shadows) + self.assertEqual( + carb_settings_iface.get("/rtx/ambientOcclusion/enabled"), sim.cfg.render.enable_ambient_occlusion + ) + self.assertEqual(carb_settings_iface.get("/rtx/post/aa/op"), 3) # dlss = 3, dlaa=4 + + +if __name__ == "__main__": + run_tests() From bf689435253009ca010c0ee37be5795556f67f72 Mon Sep 17 00:00:00 2001 From: Kelly Guo Date: Thu, 24 Oct 2024 07:24:08 -0400 Subject: [PATCH 035/111] Adds Kit command line argument support (#1293) # Description This change adds the option to pass command line arguments directly to OV kit. This avoids the need of having to modify the app files to change settings for OV. ## Type of change - New feature (non-breaking change which adds functionality) ## Checklist - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [ ] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [ ] I have added tests that prove my fix is effective or that my feature works - [x] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [x] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --- isaaclab.sh | 2 +- .../omni.isaac.lab/config/extension.toml | 2 +- .../omni.isaac.lab/docs/CHANGELOG.rst | 9 ++++++++ .../omni/isaac/lab/app/app_launcher.py | 22 +++++++++++++++++++ 4 files changed, 33 insertions(+), 2 deletions(-) diff --git a/isaaclab.sh b/isaaclab.sh index 22374fe0ff..b9d2683e1c 100755 --- a/isaaclab.sh +++ b/isaaclab.sh @@ -350,7 +350,7 @@ while [[ $# -gt 0 ]]; do python_exe=$(extract_python_exe) echo "[INFO] Using python from: ${python_exe}" shift # past argument - ${python_exe} $@ + ${python_exe} "$@" # exit neatly break ;; diff --git a/source/extensions/omni.isaac.lab/config/extension.toml b/source/extensions/omni.isaac.lab/config/extension.toml index a1856cd636..b7e06d2a63 100644 --- a/source/extensions/omni.isaac.lab/config/extension.toml +++ b/source/extensions/omni.isaac.lab/config/extension.toml @@ -1,7 +1,7 @@ [package] # Note: Semantic Versioning is used: https://semver.org/ -version = "0.27.1" +version = "0.27.2" # Description title = "Isaac Lab framework for Robot Learning" diff --git a/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst b/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst index c61f2ac870..7da6579283 100644 --- a/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst +++ b/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst @@ -1,6 +1,15 @@ Changelog --------- +0.27.2 (2024-10-21) +~~~~~~~~~~~~~~~~~~~ + +Added +^^^^^ + +* Added ``--kit_args`` to :class:`~omni.isaac.lab.app.AppLauncher` to allow passing command line arguments directly to Omniverse Kit SDK. + + 0.27.1 (2024-10-20) ~~~~~~~~~~~~~~~~~~~ diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/app/app_launcher.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/app/app_launcher.py index 0453cc4cc5..c6dc4b84dc 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/app/app_launcher.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/app/app_launcher.py @@ -185,6 +185,10 @@ def add_app_launcher_args(parser: argparse.ArgumentParser) -> None: * If headless and enable_cameras are False, the experience file is set to ``isaaclab.python.kit``. * If headless is True and enable_cameras is False, the experience file is set to ``isaaclab.python.headless.kit``. + * ``kit_args`` (str): Optional command line arguments to be passed to Omniverse Kit directly. + Arguments should be combined into a single string separated by space. + Example usage: --kit_args "--ext-folder=/path/to/ext1 --ext-folder=/path/to/ext2" + Args: parser: An argument parser instance to be extended with the AppLauncher specific options. """ @@ -271,6 +275,15 @@ def add_app_launcher_args(parser: argparse.ArgumentParser) -> None: " it is resolved relative to the `apps` folder in Isaac Sim and Isaac Lab (in that order)." ), ) + arg_group.add_argument( + "--kit_args", + type=str, + default="", + help=( + "Command line arguments for Omniverse Kit as a string separated by a space delimiter." + ' Example usage: --kit_args "--ext-folder=/path/to/ext1 --ext-folder=/path/to/ext2"' + ), + ) # Corresponding to the beginning of the function, # if we have removed -h/--help handling, we add it back. @@ -557,6 +570,12 @@ def _config_resolution(self, launcher_args: dict): " The file does not exist." ) + # Resolve additional arguments passed to Kit + self._kit_args = [] + if "kit_args" in launcher_args: + self._kit_args = [arg for arg in launcher_args["kit_args"].split()] + sys.argv += self._kit_args + # Resolve the absolute path of the experience file self._sim_experience_file = os.path.abspath(self._sim_experience_file) print(f"[INFO][AppLauncher]: Loading experience file: {self._sim_experience_file}") @@ -595,6 +614,9 @@ def _create_app(self): # remove the threadCount argument from sys.argv if it was added for distributed training pattern = r"--/plugins/carb\.tasking\.plugin/threadCount=\d+" sys.argv = [arg for arg in sys.argv if not re.match(pattern, arg)] + # remove additional OV args from sys.argv + if len(self._kit_args) > 0: + sys.argv = [arg for arg in sys.argv if arg not in self._kit_args] def _rendering_enabled(self) -> bool: """Check if rendering is required by the app.""" From 9c7238d2e5fc83702f0ff8189c9c2fbbd99182df Mon Sep 17 00:00:00 2001 From: Pascal Roth <57946385+pascal-roth@users.noreply.github.com> Date: Thu, 24 Oct 2024 14:08:26 +0200 Subject: [PATCH 036/111] Fixes job submitting for the cluster then an intended image is given (#1296) # Description The path to check if the first passed argument is a container profile included the wrong path. This PR fixes the path. ## Type of change - Bug fix (non-breaking change which fixes an issue) ## Checklist - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [ ] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [ ] I have added tests that prove my fix is effective or that my feature works - [x] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [x] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --- docker/cluster/cluster_interface.sh | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docker/cluster/cluster_interface.sh b/docker/cluster/cluster_interface.sh index 96bdc49b3d..6684d835c9 100755 --- a/docker/cluster/cluster_interface.sh +++ b/docker/cluster/cluster_interface.sh @@ -177,7 +177,7 @@ case $command in job) if [ $# -ge 1 ]; then passed_profile=$1 - if [ -f ".env.$passed_profile" ]; then + if [ -f "$SCRIPT_DIR/../.env.$passed_profile" ]; then profile=$passed_profile shift fi From 41a9dd44fa3d7cb9ba2944907b3e87c28e328970 Mon Sep 17 00:00:00 2001 From: jtigue-bdai <166445701+jtigue-bdai@users.noreply.github.com> Date: Thu, 24 Oct 2024 09:17:01 -0400 Subject: [PATCH 037/111] Allows configclass `to_dict` operation to handle a list of configclasses (#1227) # Description This PR add in the ability to properly convert configclass to dict if a configclass instance contains a list of configclasses. Fixes #1219 ## Type of change - Bug fix (non-breaking change which fixes an issue) ## Checklist - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [x] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [x] I have added tests that prove my fix is effective or that my feature works - [x] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [x] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --- .../omni.isaac.lab/config/extension.toml | 2 +- .../omni.isaac.lab/docs/CHANGELOG.rst | 10 ++++++ .../omni/isaac/lab/utils/dict.py | 6 +++- .../test/utils/test_configclass.py | 34 +++++++++++++++++-- 4 files changed, 47 insertions(+), 5 deletions(-) diff --git a/source/extensions/omni.isaac.lab/config/extension.toml b/source/extensions/omni.isaac.lab/config/extension.toml index b7e06d2a63..157d3aaa5e 100644 --- a/source/extensions/omni.isaac.lab/config/extension.toml +++ b/source/extensions/omni.isaac.lab/config/extension.toml @@ -1,7 +1,7 @@ [package] # Note: Semantic Versioning is used: https://semver.org/ -version = "0.27.2" +version = "0.27.3" # Description title = "Isaac Lab framework for Robot Learning" diff --git a/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst b/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst index 7da6579283..52584a23eb 100644 --- a/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst +++ b/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst @@ -1,6 +1,16 @@ Changelog --------- +0.27.3 (2024-10-22) +~~~~~~~~~~~~~~~~~~~ + +Fixed +^^^^^ + +* Fixed the issue with using list or tuples of ``configclass`` within a ``configclass``. Earlier, the list of + configclass objects were not converted to dictionary properly when ``to_dict`` function was called. + + 0.27.2 (2024-10-21) ~~~~~~~~~~~~~~~~~~~ diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/utils/dict.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/utils/dict.py index ca6b4f2a4b..07086a1f9b 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/utils/dict.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/utils/dict.py @@ -40,8 +40,10 @@ def class_to_dict(obj: object) -> dict[str, Any]: # convert object to dictionary if isinstance(obj, dict): obj_dict = obj - else: + elif hasattr(obj, "__dict__"): obj_dict = obj.__dict__ + else: + return obj # convert to dictionary data = dict() @@ -55,6 +57,8 @@ def class_to_dict(obj: object) -> dict[str, Any]: # check if attribute is a dictionary elif hasattr(value, "__dict__") or isinstance(value, dict): data[key] = class_to_dict(value) + elif isinstance(value, (list, tuple)): + data[key] = type(value)([class_to_dict(v) for v in value]) else: data[key] = value return data diff --git a/source/extensions/omni.isaac.lab/test/utils/test_configclass.py b/source/extensions/omni.isaac.lab/test/utils/test_configclass.py index f899534033..4b2f5a7ff1 100644 --- a/source/extensions/omni.isaac.lab/test/utils/test_configclass.py +++ b/source/extensions/omni.isaac.lab/test/utils/test_configclass.py @@ -23,7 +23,7 @@ from collections.abc import Callable from dataclasses import MISSING, asdict, field from functools import wraps -from typing import ClassVar +from typing import Any, ClassVar from omni.isaac.lab.utils.configclass import configclass from omni.isaac.lab.utils.dict import class_to_dict, dict_to_md5_hash, update_class_from_dict @@ -85,6 +85,11 @@ def double(x): return 2 * x +@configclass +class ModifierCfg: + params: dict[str, Any] = {"A": 1, "B": 2} + + @configclass class ViewerCfg: eye: list = [7.5, 7.5, 7.5] # field missing on purpose @@ -113,6 +118,7 @@ class BasicDemoCfg: device_id: int = 0 env: EnvCfg = EnvCfg() robot_default_state: RobotDefaultStateCfg = RobotDefaultStateCfg() + list_config = [ModifierCfg(), ModifierCfg(params={"A": 3, "B": 4})] @configclass @@ -381,6 +387,7 @@ class MissingChildDemoCfg(MissingParentDemoCfg): "dof_vel": [0.0, 0.0, 0.0, 0.0, 0.0, 1.0], }, "device_id": 0, + "list_config": [{"params": {"A": 1, "B": 2}}, {"params": {"A": 3, "B": 4}}], } basic_demo_cfg_change_correct = { @@ -392,6 +399,7 @@ class MissingChildDemoCfg(MissingParentDemoCfg): "dof_vel": [0.0, 0.0, 0.0, 0.0, 0.0, 1.0], }, "device_id": 0, + "list_config": [{"params": {"A": 1, "B": 2}}, {"params": {"A": 3, "B": 4}}], } basic_demo_cfg_change_with_none_correct = { @@ -403,6 +411,19 @@ class MissingChildDemoCfg(MissingParentDemoCfg): "dof_vel": [0.0, 0.0, 0.0, 0.0, 0.0, 1.0], }, "device_id": 0, + "list_config": [{"params": {"A": 1, "B": 2}}, {"params": {"A": 3, "B": 4}}], +} + +basic_demo_cfg_change_with_tuple_correct = { + "env": {"num_envs": 56, "episode_length": 2000, "viewer": {"eye": [7.5, 7.5, 7.5], "lookat": [0.0, 0.0, 0.0]}}, + "robot_default_state": { + "pos": (0.0, 0.0, 0.0), + "rot": (1.0, 0.0, 0.0, 0.0), + "dof_pos": (0.0, 0.0, 0.0, 0.0, 0.0, 0.0), + "dof_vel": [0.0, 0.0, 0.0, 0.0, 0.0, 1.0], + }, + "device_id": 0, + "list_config": [{"params": {"A": -1, "B": -2}}, {"params": {"A": -3, "B": -4}}], } basic_demo_cfg_nested_dict_and_list = { @@ -496,7 +517,7 @@ def test_dict_conversion(self): def test_dict_conversion_order(self): """Tests that order is conserved when converting to dictionary.""" - true_outer_order = ["device_id", "env", "robot_default_state"] + true_outer_order = ["device_id", "env", "robot_default_state", "list_config"] true_env_order = ["num_envs", "episode_length", "viewer"] # create config cfg = BasicDemoCfg() @@ -514,7 +535,7 @@ def test_dict_conversion_order(self): self.assertEqual(label, parsed_value) # check ordering when copied cfg_dict_copied = copy.deepcopy(cfg_dict) - cfg_dict_copied.pop("robot_default_state") + cfg_dict_copied.pop("list_config") # check ordering for label, parsed_value in zip(true_outer_order, cfg_dict_copied.keys()): self.assertEqual(label, parsed_value) @@ -551,6 +572,13 @@ def test_config_update_dict_with_none(self): update_class_from_dict(cfg, cfg_dict) self.assertDictEqual(asdict(cfg), basic_demo_cfg_change_with_none_correct) + def test_config_update_dict_tuple(self): + """Test updating configclass using a dictionary that modifies a tuple.""" + cfg = BasicDemoCfg() + cfg_dict = {"list_config": [{"params": {"A": -1, "B": -2}}, {"params": {"A": -3, "B": -4}}]} + update_class_from_dict(cfg, cfg_dict) + self.assertDictEqual(asdict(cfg), basic_demo_cfg_change_with_tuple_correct) + def test_config_update_nested_dict(self): """Test updating configclass with sub-dictionaries.""" cfg = NestedDictAndListCfg() From 4c91535279ac3e57ef1103473e23a50ce8bf4296 Mon Sep 17 00:00:00 2001 From: Louis LE LAY Date: Fri, 25 Oct 2024 04:48:44 -0400 Subject: [PATCH 038/111] Updates documentation on Isaac Lab installation path for Windows (#1271) # Description This update addresses a minor inconsistency found in the Isaac Lab installation documentation for Windows. While following the installation instructions on Isaac Lab for "Option 2: Installation using Isaac Sim binaries" on Windows, I encountered the following lines: > `C:\Users\%USERPROFILE%\AppData\Local\ov\pkg\isaac_sim-*`, with `*` corresponding to the Isaac Sim version. > `set ISAACSIM_PATH="C:\Users\%USERPROFILE%\AppData\Local\ov\pkg\isaac-sim-4.2.0"` This seemed redundant, as `%USERPROFILE%` already refers to the path `C:\Users\name_of_user`. I have compiled and verified the documentation changes to ensure proper display. Additionally, I tested this update on a Windows system, confirming that it works as intended. ## Type of change - This change requires a documentation update ## Checklist - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [x] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [x] I have added tests that prove my fix is effective or that my feature works - [x] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [x] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --- CONTRIBUTORS.md | 1 + docs/source/setup/installation/binaries_installation.rst | 4 ++-- source/extensions/omni.isaac.lab/config/extension.toml | 2 +- source/extensions/omni.isaac.lab/docs/CHANGELOG.rst | 9 +++++++++ 4 files changed, 13 insertions(+), 3 deletions(-) diff --git a/CONTRIBUTORS.md b/CONTRIBUTORS.md index a0e671618c..49497a9909 100644 --- a/CONTRIBUTORS.md +++ b/CONTRIBUTORS.md @@ -54,6 +54,7 @@ Guidelines for modifications: * Kaixi Bao * Kourosh Darvish * Lionel Gulich +* Louis Le Lay * Lorenz Wellhausen * Masoud Moghani * Michael Gussert diff --git a/docs/source/setup/installation/binaries_installation.rst b/docs/source/setup/installation/binaries_installation.rst index e9c4469bca..9fef4f5fa3 100644 --- a/docs/source/setup/installation/binaries_installation.rst +++ b/docs/source/setup/installation/binaries_installation.rst @@ -38,7 +38,7 @@ To check the minimum system requirements,refer to the documentation :sync: windows On Windows systems, by default,Isaac Sim is installed in the directory - ``C:\Users\%USERPROFILE%\AppData\Local\ov\pkg\isaac_sim-*``, with ``*`` corresponding to the Isaac Sim version. + ``%USERPROFILE%\AppData\Local\ov\pkg\isaac_sim-*``, with ``*`` corresponding to the Isaac Sim version. Verifying the Isaac Sim installation ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ @@ -66,7 +66,7 @@ variables to your terminal for the remaining of the installation instructions: .. code:: batch :: Isaac Sim root directory - set ISAACSIM_PATH="C:\Users\%USERPROFILE%\AppData\Local\ov\pkg\isaac-sim-4.2.0" + set ISAACSIM_PATH="%USERPROFILE%\AppData\Local\ov\pkg\isaac-sim-4.2.0" :: Isaac Sim python executable set ISAACSIM_PYTHON_EXE="%ISAACSIM_PATH:"=%\python.bat" diff --git a/source/extensions/omni.isaac.lab/config/extension.toml b/source/extensions/omni.isaac.lab/config/extension.toml index 157d3aaa5e..feee940cdb 100644 --- a/source/extensions/omni.isaac.lab/config/extension.toml +++ b/source/extensions/omni.isaac.lab/config/extension.toml @@ -1,7 +1,7 @@ [package] # Note: Semantic Versioning is used: https://semver.org/ -version = "0.27.3" +version = "0.27.4" # Description title = "Isaac Lab framework for Robot Learning" diff --git a/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst b/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst index 52584a23eb..c0ac6cd460 100644 --- a/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst +++ b/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst @@ -1,6 +1,15 @@ Changelog --------- +0.27.4 (2024-10-18) +~~~~~~~~~~~~~~~~~~~ + +Fixed +^^^^^ + +* Updated installation path instructions for Windows in the Isaac Lab documentation to remove redundancy in the use of %USERPROFILE% for path definitions. + + 0.27.3 (2024-10-22) ~~~~~~~~~~~~~~~~~~~ From 002fec41697103123170b4857f7b97cf64b53cd2 Mon Sep 17 00:00:00 2001 From: Toni-SM Date: Fri, 25 Oct 2024 22:23:19 -0400 Subject: [PATCH 039/111] Fixes Gymnasium spaces issues due to Hydra/OmegaConf limitations (#1306) # Description Fixed issues with defining Gymnasium spaces in Direct workflows due to Hydra/OmegaConf limitations with non-primitive types (see https://github.com/isaac-sim/IsaacLab/discussions/1264#discussioncomment-11045011) ``` omegaconf.errors.UnsupportedValueType: Value 'XXXXX' is not a supported primitive type ``` ## Type of change - Bug fix (non-breaking change which fixes an issue) ## Checklist - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [ ] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [x] I have added tests that prove my fix is effective or that my feature works - [x] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [x] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --- .../omni.isaac.lab/config/extension.toml | 2 +- .../omni.isaac.lab/docs/CHANGELOG.rst | 9 ++ .../omni/isaac/lab/envs/utils/spaces.py | 129 ++++++++++++++++++ .../test/envs/test_spaces_utils.py | 55 +++++++- .../config/extension.toml | 2 +- .../omni.isaac.lab_tasks/docs/CHANGELOG.rst | 9 ++ .../omni/isaac/lab_tasks/utils/hydra.py | 8 ++ 7 files changed, 211 insertions(+), 3 deletions(-) diff --git a/source/extensions/omni.isaac.lab/config/extension.toml b/source/extensions/omni.isaac.lab/config/extension.toml index feee940cdb..1c6e79d43b 100644 --- a/source/extensions/omni.isaac.lab/config/extension.toml +++ b/source/extensions/omni.isaac.lab/config/extension.toml @@ -1,7 +1,7 @@ [package] # Note: Semantic Versioning is used: https://semver.org/ -version = "0.27.4" +version = "0.27.5" # Description title = "Isaac Lab framework for Robot Learning" diff --git a/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst b/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst index c0ac6cd460..ac36f51549 100644 --- a/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst +++ b/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst @@ -1,6 +1,15 @@ Changelog --------- +0.27.5 (2024-10-25) +~~~~~~~~~~~~~~~~~~~ + +Added +^^^^^ + +* Added utilities for serializing/deserializing Gymnasium spaces. + + 0.27.4 (2024-10-18) ~~~~~~~~~~~~~~~~~~~ diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/utils/spaces.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/utils/spaces.py index 8604392ec6..2a1e30c1ee 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/utils/spaces.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/utils/spaces.py @@ -4,6 +4,7 @@ # SPDX-License-Identifier: BSD-3-Clause import gymnasium as gym +import json import numpy as np import torch from typing import Any @@ -90,3 +91,131 @@ def tensorize(s, x): sample = (gym.vector.utils.batch_space(space, batch_size) if batch_size > 0 else space).sample() return tensorize(space, sample) + + +def serialize_space(space: SpaceType) -> str: + """Serialize a space specification as JSON. + + Args: + space: Space specification. + + Returns: + Serialized JSON representation. + """ + # Gymnasium spaces + if isinstance(space, gym.spaces.Discrete): + return json.dumps({"type": "gymnasium", "space": "Discrete", "n": int(space.n)}) + elif isinstance(space, gym.spaces.Box): + return json.dumps({ + "type": "gymnasium", + "space": "Box", + "low": space.low.tolist(), + "high": space.high.tolist(), + "shape": space.shape, + }) + elif isinstance(space, gym.spaces.MultiDiscrete): + return json.dumps({"type": "gymnasium", "space": "MultiDiscrete", "nvec": space.nvec.tolist()}) + elif isinstance(space, gym.spaces.Tuple): + return json.dumps({"type": "gymnasium", "space": "Tuple", "spaces": tuple(map(serialize_space, space.spaces))}) + elif isinstance(space, gym.spaces.Dict): + return json.dumps( + {"type": "gymnasium", "space": "Dict", "spaces": {k: serialize_space(v) for k, v in space.spaces.items()}} + ) + # Python data types + # Box + elif isinstance(space, int) or (isinstance(space, list) and all(isinstance(x, int) for x in space)): + return json.dumps({"type": "python", "space": "Box", "value": space}) + # Discrete + elif isinstance(space, set) and len(space) == 1: + return json.dumps({"type": "python", "space": "Discrete", "value": next(iter(space))}) + # MultiDiscrete + elif isinstance(space, list) and all(isinstance(x, set) and len(x) == 1 for x in space): + return json.dumps({"type": "python", "space": "MultiDiscrete", "value": [next(iter(x)) for x in space]}) + # composite spaces + # Tuple + elif isinstance(space, tuple): + return json.dumps({"type": "python", "space": "Tuple", "value": [serialize_space(x) for x in space]}) + # Dict + elif isinstance(space, dict): + return json.dumps( + {"type": "python", "space": "Dict", "value": {k: serialize_space(v) for k, v in space.items()}} + ) + raise ValueError(f"Unsupported space ({space})") + + +def deserialize_space(string: str) -> gym.spaces.Space: + """Deserialize a space specification encoded as JSON. + + Args: + string: Serialized JSON representation. + + Returns: + Space specification. + """ + obj = json.loads(string) + # Gymnasium spaces + if obj["type"] == "gymnasium": + if obj["space"] == "Discrete": + return gym.spaces.Discrete(n=obj["n"]) + elif obj["space"] == "Box": + return gym.spaces.Box(low=np.array(obj["low"]), high=np.array(obj["high"]), shape=obj["shape"]) + elif obj["space"] == "MultiDiscrete": + return gym.spaces.MultiDiscrete(nvec=np.array(obj["nvec"])) + elif obj["space"] == "Tuple": + return gym.spaces.Tuple(spaces=tuple(map(deserialize_space, obj["spaces"]))) + elif obj["space"] == "Dict": + return gym.spaces.Dict(spaces={k: deserialize_space(v) for k, v in obj["spaces"].items()}) + else: + raise ValueError(f"Unsupported space ({obj['spaces']})") + # Python data types + elif obj["type"] == "python": + if obj["space"] == "Discrete": + return {obj["value"]} + elif obj["space"] == "Box": + return obj["value"] + elif obj["space"] == "MultiDiscrete": + return [{x} for x in obj["value"]] + elif obj["space"] == "Tuple": + return tuple(map(deserialize_space, obj["value"])) + elif obj["space"] == "Dict": + return {k: deserialize_space(v) for k, v in obj["value"].items()} + else: + raise ValueError(f"Unsupported space ({obj['spaces']})") + else: + raise ValueError(f"Unsupported type ({obj['type']})") + + +def replace_env_cfg_spaces_with_strings(env_cfg: object) -> object: + """Replace spaces objects with their serialized JSON representations in an environment config. + + Args: + env_cfg: Environment config instance. + + Returns: + Environment config instance with spaces replaced if any. + """ + for attr in ["observation_space", "action_space", "state_space"]: + if hasattr(env_cfg, attr): + setattr(env_cfg, attr, serialize_space(getattr(env_cfg, attr))) + for attr in ["observation_spaces", "action_spaces"]: + if hasattr(env_cfg, attr): + setattr(env_cfg, attr, {k: serialize_space(v) for k, v in getattr(env_cfg, attr).items()}) + return env_cfg + + +def replace_strings_with_env_cfg_spaces(env_cfg: object) -> object: + """Replace spaces objects with their serialized JSON representations in an environment config. + + Args: + env_cfg: Environment config instance. + + Returns: + Environment config instance with spaces replaced if any. + """ + for attr in ["observation_space", "action_space", "state_space"]: + if hasattr(env_cfg, attr): + setattr(env_cfg, attr, deserialize_space(getattr(env_cfg, attr))) + for attr in ["observation_spaces", "action_spaces"]: + if hasattr(env_cfg, attr): + setattr(env_cfg, attr, {k: deserialize_space(v) for k, v in getattr(env_cfg, attr).items()}) + return env_cfg diff --git a/source/extensions/omni.isaac.lab/test/envs/test_spaces_utils.py b/source/extensions/omni.isaac.lab/test/envs/test_spaces_utils.py index 274f0de650..791c61380c 100644 --- a/source/extensions/omni.isaac.lab/test/envs/test_spaces_utils.py +++ b/source/extensions/omni.isaac.lab/test/envs/test_spaces_utils.py @@ -26,7 +26,7 @@ import unittest from gymnasium.spaces import Box, Dict, Discrete, MultiDiscrete, Tuple -from omni.isaac.lab.envs.utils.spaces import sample_space, spec_to_gym_space +from omni.isaac.lab.envs.utils.spaces import deserialize_space, sample_space, serialize_space, spec_to_gym_space class TestSpacesUtils(unittest.TestCase): @@ -104,6 +104,59 @@ def test_sample_space(self): self.assertIsInstance(sample, dict) self._check_tensorized(sample, batch_size=5) + def test_space_serialization_deserialization(self): + # fundamental spaces + # Box + space = 1 + output = deserialize_space(serialize_space(space)) + self.assertEqual(space, output) + space = [1, 2, 3, 4, 5] + output = deserialize_space(serialize_space(space)) + self.assertEqual(space, output) + space = Box(low=-1.0, high=1.0, shape=(1, 2)) + output = deserialize_space(serialize_space(space)) + self.assertIsInstance(output, Box) + self.assertTrue((space.low == output.low).all()) + self.assertTrue((space.high == output.high).all()) + self.assertEqual(space.shape, output.shape) + # Discrete + space = {2} + output = deserialize_space(serialize_space(space)) + self.assertEqual(space, output) + space = Discrete(2) + output = deserialize_space(serialize_space(space)) + self.assertIsInstance(output, Discrete) + self.assertEqual(space.n, output.n) + # MultiDiscrete + space = [{1}, {2}, {3}] + output = deserialize_space(serialize_space(space)) + self.assertEqual(space, output) + space = MultiDiscrete(np.array([1, 2, 3])) + output = deserialize_space(serialize_space(space)) + self.assertIsInstance(output, MultiDiscrete) + self.assertTrue((space.nvec == output.nvec).all()) + # composite spaces + # Tuple + space = ([1, 2, 3, 4, 5], {2}, [{1}, {2}, {3}]) + output = deserialize_space(serialize_space(space)) + self.assertEqual(space, output) + space = Tuple((Box(-1, 1, shape=(1,)), Discrete(2))) + output = deserialize_space(serialize_space(space)) + self.assertIsInstance(output, Tuple) + self.assertEqual(len(output), 2) + self.assertIsInstance(output[0], Box) + self.assertIsInstance(output[1], Discrete) + # Dict + space = {"box": [1, 2, 3, 4, 5], "discrete": {2}, "multi_discrete": [{1}, {2}, {3}]} + output = deserialize_space(serialize_space(space)) + self.assertEqual(space, output) + space = Dict({"box": Box(-1, 1, shape=(1,)), "discrete": Discrete(2)}) + output = deserialize_space(serialize_space(space)) + self.assertIsInstance(output, Dict) + self.assertEqual(len(output), 2) + self.assertIsInstance(output["box"], Box) + self.assertIsInstance(output["discrete"], Discrete) + """ Helper functions. """ diff --git a/source/extensions/omni.isaac.lab_tasks/config/extension.toml b/source/extensions/omni.isaac.lab_tasks/config/extension.toml index a739dc74a0..a0b2718609 100644 --- a/source/extensions/omni.isaac.lab_tasks/config/extension.toml +++ b/source/extensions/omni.isaac.lab_tasks/config/extension.toml @@ -1,7 +1,7 @@ [package] # Note: Semantic Versioning is used: https://semver.org/ -version = "0.10.9" +version = "0.10.10" # Description title = "Isaac Lab Environments" diff --git a/source/extensions/omni.isaac.lab_tasks/docs/CHANGELOG.rst b/source/extensions/omni.isaac.lab_tasks/docs/CHANGELOG.rst index 5bf5d9eeea..a0a2b39346 100644 --- a/source/extensions/omni.isaac.lab_tasks/docs/CHANGELOG.rst +++ b/source/extensions/omni.isaac.lab_tasks/docs/CHANGELOG.rst @@ -1,6 +1,15 @@ Changelog --------- +0.10.10 (2024-10-25) +~~~~~~~~~~~~~~~~~~~~ + +Fixed +^^^^^ + +* Fixed issues with defining Gymnasium spaces in Direct workflows due to Hydra/OmegaConf limitations with non-primitive types. + + 0.10.9 (2024-10-22) ~~~~~~~~~~~~~~~~~~~ diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/utils/hydra.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/utils/hydra.py index 1522e9f25e..5d6a8b7c61 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/utils/hydra.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/utils/hydra.py @@ -17,6 +17,7 @@ raise ImportError("Hydra is not installed. Please install it by running 'pip install hydra-core'.") from omni.isaac.lab.envs import DirectRLEnvCfg, ManagerBasedRLEnvCfg +from omni.isaac.lab.envs.utils.spaces import replace_env_cfg_spaces_with_strings, replace_strings_with_env_cfg_spaces from omni.isaac.lab.utils import replace_slices_with_strings, replace_strings_with_slices from omni.isaac.lab_tasks.utils.parse_cfg import load_cfg_from_registry @@ -40,6 +41,9 @@ def register_task_to_hydra( # load the configurations env_cfg = load_cfg_from_registry(task_name, "env_cfg_entry_point") agent_cfg = load_cfg_from_registry(task_name, agent_cfg_entry_point) + # replace gymnasium spaces with strings because OmegaConf does not support them. + # this must be done before converting the env configs to dictionary to avoid internal reinterpretations + replace_env_cfg_spaces_with_strings(env_cfg) # convert the configs to dictionary env_cfg_dict = env_cfg.to_dict() if isinstance(agent_cfg, dict): @@ -83,6 +87,10 @@ def hydra_main(hydra_env_cfg: DictConfig, env_cfg=env_cfg, agent_cfg=agent_cfg): hydra_env_cfg = replace_strings_with_slices(hydra_env_cfg) # update the configs with the Hydra command line arguments env_cfg.from_dict(hydra_env_cfg["env"]) + # replace strings that represent gymnasium spaces because OmegaConf does not support them. + # this must be done after converting the env configs from dictionary to avoid internal reinterpretations + replace_strings_with_env_cfg_spaces(env_cfg) + # get agent configs if isinstance(agent_cfg, dict): agent_cfg = hydra_env_cfg["agent"] else: From c8f77a78cbc38e02f794ed54d9b2813a9597800f Mon Sep 17 00:00:00 2001 From: lgulich <22480644+lgulich@users.noreply.github.com> Date: Mon, 28 Oct 2024 03:54:03 -0700 Subject: [PATCH 040/111] Adds missing typehint in reward function (#1303) # Description Adds missing typehint in reward function ## Type of change - Bug fix (non-breaking change which fixes an issue) ## Checklist - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [ ] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [ ] I have added tests that prove my fix is effective or that my feature works - [ ] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [x] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --- .../omni.isaac.lab/omni/isaac/lab/envs/mdp/rewards.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/rewards.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/rewards.py index 7f03bf41f0..1a68d321ab 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/rewards.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/rewards.py @@ -159,7 +159,7 @@ def joint_acc_l2(env: ManagerBasedRLEnv, asset_cfg: SceneEntityCfg = SceneEntity return torch.sum(torch.square(asset.data.joint_acc[:, asset_cfg.joint_ids]), dim=1) -def joint_deviation_l1(env, asset_cfg: SceneEntityCfg = SceneEntityCfg("robot")) -> torch.Tensor: +def joint_deviation_l1(env: ManagerBasedRLEnv, asset_cfg: SceneEntityCfg = SceneEntityCfg("robot")) -> torch.Tensor: """Penalize joint positions that deviate from the default one.""" # extract the used quantities (to enable type-hinting) asset: Articulation = env.scene[asset_cfg.name] From 1e3b6ec241eeadd499e1d6ea40a1ecddba1dcebd Mon Sep 17 00:00:00 2001 From: Lingheng Meng Date: Tue, 29 Oct 2024 02:14:47 +1100 Subject: [PATCH 041/111] Fixes `net_arch` in `sb3_ppo_cfg.yaml` for Isaac-Lift-Cube-Franka-v0 task (#1249) # Description Two changes are made to fix _[Bug Report] sb3_ppo_cfg.yaml not work for Isaac-Lift-Cube-Franka-v0 #1248_: 1. Add `sb3_cfg_entry_point` to `source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/lift/config/franka/init.py` 2. Change `net_arch=[32, 32, dict(pi=[256, 128, 64], vf=[256, 128, 64])]` to `net_arch=dict(pi=[256, 128, 64], vf=[256, 128, 64])` in line 19 of `sb3_ppo_cfg.yaml`. Fixes #1248 ## Type of change - Bug fix (non-breaking change which fixes an issue) - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [x] My changes generate no new warnings --- .../manager_based/manipulation/lift/config/franka/__init__.py | 2 ++ .../manipulation/lift/config/franka/agents/sb3_ppo_cfg.yaml | 2 +- 2 files changed, 3 insertions(+), 1 deletion(-) diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/lift/config/franka/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/lift/config/franka/__init__.py index 14657e4f92..651d84ed63 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/lift/config/franka/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/lift/config/franka/__init__.py @@ -23,6 +23,7 @@ "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:LiftCubePPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_ppo_cfg.yaml", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_cfg.yaml", + "sb3_cfg_entry_point": f"{agents.__name__}:sb3_ppo_cfg.yaml", }, disable_env_checker=True, ) @@ -35,6 +36,7 @@ "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:LiftCubePPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_ppo_cfg.yaml", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_cfg.yaml", + "sb3_cfg_entry_point": f"{agents.__name__}:sb3_ppo_cfg.yaml", }, disable_env_checker=True, ) diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/lift/config/franka/agents/sb3_ppo_cfg.yaml b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/lift/config/franka/agents/sb3_ppo_cfg.yaml index 57960b8822..6d6f15781a 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/lift/config/franka/agents/sb3_ppo_cfg.yaml +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/lift/config/franka/agents/sb3_ppo_cfg.yaml @@ -16,7 +16,7 @@ learning_rate: !!float 3e-4 clip_range: 0.2 policy_kwargs: "dict( activation_fn=nn.ELU, - net_arch=[32, 32, dict(pi=[256, 128, 64], vf=[256, 128, 64])] + net_arch=dict(pi=[256, 128, 64], vf=[256, 128, 64]) )" target_kl: 0.01 max_grad_norm: 1.0 From cace5c50a1e421b4e5ba2a5b59a7e93e868a1e89 Mon Sep 17 00:00:00 2001 From: Kelly Guo Date: Mon, 28 Oct 2024 11:17:07 -0400 Subject: [PATCH 042/111] Fixes minor bugs in RayCasterCamera and BaseEnvWindow (#1308) # Description * Fixes a bug in RayCasterCamera's print function that was accessing `RayCaster.meshes` instead of `self.meshes` * Fixes a bug in BaseEnvWindow that was trying to access attributes from undefined configs when building UI elements for action and command terms ## Type of change - Bug fix (non-breaking change which fixes an issue) ## Checklist - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [ ] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [x] I have added tests that prove my fix is effective or that my feature works - [x] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [x] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --- .../omni.isaac.lab/config/extension.toml | 2 +- .../omni.isaac.lab/docs/CHANGELOG.rst | 10 ++ .../omni/isaac/lab/envs/ui/base_env_window.py | 2 +- .../sensors/ray_caster/ray_caster_camera.py | 2 +- .../test/envs/test_manager_based_rl_env_ui.py | 104 ++++++++++++++++++ .../test/sensors/test_camera.py | 9 ++ .../test/sensors/test_contact_sensor.py | 21 ++++ .../test/sensors/test_frame_transformer.py | 19 ++++ .../omni.isaac.lab/test/sensors/test_imu.py | 48 ++++---- .../test/sensors/test_ray_caster_camera.py | 9 ++ .../test/sensors/test_tiled_camera.py | 9 ++ 11 files changed, 211 insertions(+), 24 deletions(-) create mode 100644 source/extensions/omni.isaac.lab/test/envs/test_manager_based_rl_env_ui.py diff --git a/source/extensions/omni.isaac.lab/config/extension.toml b/source/extensions/omni.isaac.lab/config/extension.toml index 1c6e79d43b..1d78d22a46 100644 --- a/source/extensions/omni.isaac.lab/config/extension.toml +++ b/source/extensions/omni.isaac.lab/config/extension.toml @@ -1,7 +1,7 @@ [package] # Note: Semantic Versioning is used: https://semver.org/ -version = "0.27.5" +version = "0.27.6" # Description title = "Isaac Lab framework for Robot Learning" diff --git a/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst b/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst index ac36f51549..16bc34b7ed 100644 --- a/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst +++ b/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst @@ -1,6 +1,16 @@ Changelog --------- +0.27.6 (2024-10-25) +~~~~~~~~~~~~~~~~~~~ + +Fixed +^^^^^ + +* Fixed usage of ``meshes`` property in :class:`omni.isaac.lab.sensors.RayCasterCamera` to use ``self.meshes`` instead of the undefined ``RayCaster.meshes``. +* Fixed issue in :class:`omni.isaac.lab.envs.ui.BaseEnvWindow` where undefined configs were being accessed when creating debug visualization elements in UI. + + 0.27.5 (2024-10-25) ~~~~~~~~~~~~~~~~~~~ diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/ui/base_env_window.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/ui/base_env_window.py index a37a8723ec..850ad0a355 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/ui/base_env_window.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/ui/base_env_window.py @@ -382,7 +382,7 @@ def _create_debug_vis_ui_element(self, name: str, elem: object): self.ui_window_elements[f"{name}_cb"] = SimpleCheckBox( model=omni.ui.SimpleBoolModel(), enabled=elem.has_debug_vis_implementation, - checked=elem.cfg.debug_vis, + checked=elem.cfg.debug_vis if elem.cfg else False, on_checked_fn=lambda value, e=weakref.proxy(elem): e.set_debug_vis(value), ) omni.isaac.ui.ui_utils.add_line_rect_flourish() diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/ray_caster/ray_caster_camera.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/ray_caster/ray_caster_camera.py index 03da4ca9b8..91689b03ee 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/ray_caster/ray_caster_camera.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/ray_caster/ray_caster_camera.py @@ -87,7 +87,7 @@ def __str__(self) -> str: f"Ray-Caster-Camera @ '{self.cfg.prim_path}': \n" f"\tview type : {self._view.__class__}\n" f"\tupdate period (s) : {self.cfg.update_period}\n" - f"\tnumber of meshes : {len(RayCaster.meshes)}\n" + f"\tnumber of meshes : {len(self.meshes)}\n" f"\tnumber of sensors : {self._view.count}\n" f"\tnumber of rays/sensor: {self.num_rays}\n" f"\ttotal number of rays : {self.num_rays * self._view.count}\n" diff --git a/source/extensions/omni.isaac.lab/test/envs/test_manager_based_rl_env_ui.py b/source/extensions/omni.isaac.lab/test/envs/test_manager_based_rl_env_ui.py new file mode 100644 index 0000000000..f61af77b8d --- /dev/null +++ b/source/extensions/omni.isaac.lab/test/envs/test_manager_based_rl_env_ui.py @@ -0,0 +1,104 @@ +# Copyright (c) 2022-2024, The Isaac Lab Project Developers. +# All rights reserved. +# +# SPDX-License-Identifier: BSD-3-Clause + +# ignore private usage of variables warning +# pyright: reportPrivateUsage=none + +from __future__ import annotations + +"""Launch Isaac Sim Simulator first.""" + +from omni.isaac.lab.app import AppLauncher, run_tests + +# Can set this to False to see the GUI for debugging +HEADLESS = True + +# launch omniverse app +app_launcher = AppLauncher(headless=HEADLESS, enable_cameras=True) +simulation_app = app_launcher.app + +"""Rest everything follows.""" + +import unittest + +import carb +import omni.usd +from omni.isaac.core.utils.extensions import enable_extension + +from omni.isaac.lab.envs import ManagerBasedRLEnv, ManagerBasedRLEnvCfg +from omni.isaac.lab.envs.ui import ManagerBasedRLEnvWindow +from omni.isaac.lab.scene import InteractiveSceneCfg +from omni.isaac.lab.utils import configclass + +enable_extension("omni.isaac.ui") + + +@configclass +class EmptyManagerCfg: + """Empty manager specifications for the environment.""" + + pass + + +@configclass +class EmptySceneCfg(InteractiveSceneCfg): + """Configuration for an empty scene.""" + + pass + + +def get_empty_base_env_cfg(device: str = "cuda:0", num_envs: int = 1, env_spacing: float = 1.0): + """Generate base environment config based on device""" + + @configclass + class EmptyEnvCfg(ManagerBasedRLEnvCfg): + """Configuration for the empty test environment.""" + + # Scene settings + scene: EmptySceneCfg = EmptySceneCfg(num_envs=num_envs, env_spacing=env_spacing) + # Basic settings + actions: EmptyManagerCfg = EmptyManagerCfg() + observations: EmptyManagerCfg = EmptyManagerCfg() + rewards: EmptyManagerCfg = EmptyManagerCfg() + terminations: EmptyManagerCfg = EmptyManagerCfg() + # Define window + ui_window_class_type: ManagerBasedRLEnvWindow = ManagerBasedRLEnvWindow + + def __post_init__(self): + """Post initialization.""" + # step settings + self.decimation = 4 # env step every 4 sim steps: 200Hz / 4 = 50Hz + # simulation settings + self.sim.dt = 0.005 # sim step every 5ms: 200Hz + self.sim.render_interval = self.decimation # render every 4 sim steps + # pass device down from test + self.sim.device = device + # episode length + self.episode_length_s = 5.0 + + return EmptyEnvCfg() + + +class TestManagerBasedRLEnvUI(unittest.TestCase): + """Test for manager-based RL env class UI""" + + """ + Tests + """ + + def test_ui_window(self): + device = "cuda:0" + # override sim setting to enable UI + carb.settings.get_settings().set_bool("/app/window/enabled", True) + # create a new stage + omni.usd.get_context().new_stage() + # create environment + env = ManagerBasedRLEnv(cfg=get_empty_base_env_cfg(device=device)) + # close the environment + env.close() + + +if __name__ == "__main__": + run_tests() diff --git a/source/extensions/omni.isaac.lab/test/sensors/test_camera.py b/source/extensions/omni.isaac.lab/test/sensors/test_camera.py index fc6953e166..bc8f8722df 100644 --- a/source/extensions/omni.isaac.lab/test/sensors/test_camera.py +++ b/source/extensions/omni.isaac.lab/test/sensors/test_camera.py @@ -719,6 +719,15 @@ def test_throughput(self): for im_data in camera.data.output.values(): self.assertEqual(im_data.shape, (1, camera_cfg.height, camera_cfg.width, 1)) + def test_sensor_print(self): + """Test sensor print is working correctly.""" + # Create sensor + sensor = Camera(cfg=self.camera_cfg) + # Play sim + self.sim.reset() + # print info + print(sensor) + """ Helper functions. """ diff --git a/source/extensions/omni.isaac.lab/test/sensors/test_contact_sensor.py b/source/extensions/omni.isaac.lab/test/sensors/test_contact_sensor.py index 8390ee2269..6bba29b858 100644 --- a/source/extensions/omni.isaac.lab/test/sensors/test_contact_sensor.py +++ b/source/extensions/omni.isaac.lab/test/sensors/test_contact_sensor.py @@ -294,6 +294,27 @@ def test_cube_stack_contact_filtering(self): contact_sensor_2.data.force_matrix_w[:, :, 0], contact_sensor.data.force_matrix_w[:, :, 0] ) + def test_sensor_print(self): + """Test sensor print is working correctly.""" + with build_simulation_context(device="cuda:0", dt=self.sim_dt, add_lighting=False) as sim: + # Spawn things into stage + scene_cfg = ContactSensorSceneCfg(num_envs=1, env_spacing=1.0, lazy_sensor_update=False) + scene_cfg.terrain = FLAT_TERRAIN_CFG.replace(prim_path="/World/ground") + scene_cfg.shape = CUBE_CFG + scene_cfg.contact_sensor = ContactSensorCfg( + prim_path=scene_cfg.shape.prim_path, + track_pose=True, + debug_vis=False, + update_period=0.0, + track_air_time=True, + history_length=3, + ) + scene = InteractiveScene(scene_cfg) + # Play the simulator + sim.reset() + # print info + print(scene.sensors["contact_sensor"]) + """ Internal helpers. """ diff --git a/source/extensions/omni.isaac.lab/test/sensors/test_frame_transformer.py b/source/extensions/omni.isaac.lab/test/sensors/test_frame_transformer.py index aeab3d9e72..34321e76da 100644 --- a/source/extensions/omni.isaac.lab/test/sensors/test_frame_transformer.py +++ b/source/extensions/omni.isaac.lab/test/sensors/test_frame_transformer.py @@ -579,6 +579,25 @@ def test_frame_transformer_all_bodies(self): torch.testing.assert_close(bodies_pos_source_tf[:, index], body_pos_b) torch.testing.assert_close(bodies_quat_source_tf[:, index], body_quat_b) + def test_sensor_print(self): + """Test sensor print is working correctly.""" + # Spawn things into stage + scene_cfg = MySceneCfg(num_envs=2, env_spacing=5.0, lazy_sensor_update=False) + scene_cfg.frame_transformer = FrameTransformerCfg( + prim_path="{ENV_REGEX_NS}/Robot/base", + target_frames=[ + FrameTransformerCfg.FrameCfg( + prim_path="{ENV_REGEX_NS}/Robot/.*", + ), + ], + ) + scene = InteractiveScene(scene_cfg) + + # Play the simulator + self.sim.reset() + # print info + print(scene.sensors["frame_transformer"]) + if __name__ == "__main__": run_tests() diff --git a/source/extensions/omni.isaac.lab/test/sensors/test_imu.py b/source/extensions/omni.isaac.lab/test/sensors/test_imu.py index ee0db71bf7..e04211d1a9 100644 --- a/source/extensions/omni.isaac.lab/test/sensors/test_imu.py +++ b/source/extensions/omni.isaac.lab/test/sensors/test_imu.py @@ -498,34 +498,40 @@ def test_offset_calculation(self): atol=1e-4, ) + def test_env_ids_propogation(self): + """Test that env_ids argument propagates through update and reset methods""" + self.scene.reset() -def test_env_ids_propogation(self): - """Test that env_ids argument propagates through update and reset methods""" - self.scene.reset() - - for idx in range(10): - # set acceleration - self.scene.articulations["robot"].write_root_velocity_to_sim( - torch.tensor([[0.5, 0.0, 0.0, 0.0, 0.0, 0.0]], dtype=torch.float32, device=self.scene.device).repeat( - self.scene.num_envs, 1 + for idx in range(10): + # set acceleration + self.scene.articulations["robot"].write_root_velocity_to_sim( + torch.tensor([[0.5, 0.0, 0.0, 0.0, 0.0, 0.0]], dtype=torch.float32, device=self.scene.device).repeat( + self.scene.num_envs, 1 + ) + * (idx + 1) ) - * (idx + 1) - ) - # write data to sim - self.scene.write_data_to_sim() + # write data to sim + self.scene.write_data_to_sim() + # perform step + self.sim.step() + # read data from sim + self.scene.update(self.sim.get_physics_dt()) + + # reset scene for env 1 + self.scene.reset(env_ids=[1]) + # read data from sim + self.scene.update(self.sim.get_physics_dt()) # perform step self.sim.step() # read data from sim self.scene.update(self.sim.get_physics_dt()) - # reset scene for env 1 - self.scene.reset(env_ids=[1]) - # read data from sim - self.scene.update(self.sim.get_physics_dt()) - # perform step - self.sim.step() - # read data from sim - self.scene.update(self.sim.get_physics_dt()) + def test_sensor_print(self): + """Test sensor print is working correctly.""" + # Create sensor + sensor = self.scene.sensors["imu_ball"] + # print info + print(sensor) if __name__ == "__main__": diff --git a/source/extensions/omni.isaac.lab/test/sensors/test_ray_caster_camera.py b/source/extensions/omni.isaac.lab/test/sensors/test_ray_caster_camera.py index b28d023c85..ec932429ba 100644 --- a/source/extensions/omni.isaac.lab/test/sensors/test_ray_caster_camera.py +++ b/source/extensions/omni.isaac.lab/test/sensors/test_ray_caster_camera.py @@ -817,6 +817,15 @@ def test_output_equal_to_usd_camera_when_intrinsics_set(self): atol=1e-4, ) + def test_sensor_print(self): + """Test sensor print is working correctly.""" + # Create sensor + sensor = RayCasterCamera(cfg=self.camera_cfg) + # Play sim + self.sim.reset() + # print info + print(sensor) + if __name__ == "__main__": run_tests() diff --git a/source/extensions/omni.isaac.lab/test/sensors/test_tiled_camera.py b/source/extensions/omni.isaac.lab/test/sensors/test_tiled_camera.py index 269cb4bd81..28446a52ef 100644 --- a/source/extensions/omni.isaac.lab/test/sensors/test_tiled_camera.py +++ b/source/extensions/omni.isaac.lab/test/sensors/test_tiled_camera.py @@ -1304,6 +1304,15 @@ def test_output_equal_to_usd_camera_intrinsics(self): del camera_tiled del camera_usd + def test_sensor_print(self): + """Test sensor print is working correctly.""" + # Create sensor + sensor = TiledCamera(cfg=self.camera_cfg) + # Play sim + self.sim.reset() + # print info + print(sensor) + """ Helper functions. """ From 9cc298e938c8903f4ba3d50a222c9c1f3a76c435 Mon Sep 17 00:00:00 2001 From: glvov-bdai Date: Mon, 28 Oct 2024 12:58:50 -0400 Subject: [PATCH 043/111] Adds image extracted features observation term and cartpole examples for it (#1191) # Description This adds an observation term to be able to easily extract features from the images, and adds a cartpole example of using this new term. The new ResNet18 cartpole converges in less than 100 epochs. ## Type of change - New feature (non-breaking change which adds functionality) - This change requires a documentation update ## Checklist - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [x] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [x] I have added tests that prove my fix is effective or that my feature works - [x] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [x] I have added my name to the `CONTRIBUTORS.md` or my name already exists there I will update the version in the changelog and extension.toml after approval prior to merging in due to it causing merge conflicts when main updates --------- Signed-off-by: glvov-bdai Signed-off-by: garylvov <67614381+garylvov@users.noreply.github.com> Co-authored-by: garylvov <67614381+garylvov@users.noreply.github.com> Co-authored-by: garylvov Co-authored-by: David Hoeller Co-authored-by: James Smith <142246516+jsmith-bdai@users.noreply.github.com> --- CONTRIBUTORS.md | 1 + docs/source/overview/environments.rst | 11 +- pyproject.toml | 3 + .../omni.isaac.lab/config/extension.toml | 3 +- .../omni.isaac.lab/docs/CHANGELOG.rst | 10 ++ .../omni/isaac/lab/envs/mdp/observations.py | 131 ++++++++++++++++++ .../config/extension.toml | 2 +- .../omni.isaac.lab_tasks/docs/CHANGELOG.rst | 17 +++ .../direct/shadow_hand/feature_extractor.py | 1 - .../classic/cartpole/__init__.py | 31 ++++- .../agents/rl_games_feature_ppo_cfg.yaml | 79 +++++++++++ .../cartpole/cartpole_camera_env_cfg.py | 56 +++++++- 12 files changed, 336 insertions(+), 9 deletions(-) create mode 100644 source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/cartpole/agents/rl_games_feature_ppo_cfg.yaml diff --git a/CONTRIBUTORS.md b/CONTRIBUTORS.md index 49497a9909..e90992ca29 100644 --- a/CONTRIBUTORS.md +++ b/CONTRIBUTORS.md @@ -43,6 +43,7 @@ Guidelines for modifications: * Chenyu Yang * David Yang * Dorsa Rohani +* Felix Yu * Gary Lvov * Giulio Romualdi * HoJin Jeon diff --git a/docs/source/overview/environments.rst b/docs/source/overview/environments.rst index f42f3c34a5..531588a8de 100644 --- a/docs/source/overview/environments.rst +++ b/docs/source/overview/environments.rst @@ -61,6 +61,10 @@ Classic environments that are based on IsaacGymEnvs implementation of MuJoCo-sty | | | | | | |cartpole-depth-direct-link|| | +------------------+-----------------------------+-------------------------------------------------------------------------+ + | |cartpole| | |cartpole-resnet-link| | Move the cart to keep the pole upwards in the classic cartpole control | + | | | based off of features extracted from perceptive inputs with pre-trained | + | | |cartpole-theia-link| | frozen vision encoders | + +------------------+-----------------------------+-------------------------------------------------------------------------+ .. |humanoid| image:: ../_static/tasks/classic/humanoid.jpg .. |ant| image:: ../_static/tasks/classic/ant.jpg @@ -69,8 +73,11 @@ Classic environments that are based on IsaacGymEnvs implementation of MuJoCo-sty .. |humanoid-link| replace:: `Isaac-Humanoid-v0 `__ .. |ant-link| replace:: `Isaac-Ant-v0 `__ .. |cartpole-link| replace:: `Isaac-Cartpole-v0 `__ -.. |cartpole-rgb-link| replace:: `Isaac-Cartpole-RGB-Camera-v0 `__ -.. |cartpole-depth-link| replace:: `Isaac-Cartpole-Depth-Camera-v0 `__ +.. |cartpole-rgb-link| replace:: `Isaac-Cartpole-RGB-v0 `__ +.. |cartpole-depth-link| replace:: `Isaac-Cartpole-Depth-v0 `__ +.. |cartpole-resnet-link| replace:: `Isaac-Cartpole-RGB-ResNet18-v0 `__ +.. |cartpole-theia-link| replace:: `Isaac-Cartpole-RGB-TheiaTiny-v0 `__ + .. |humanoid-direct-link| replace:: `Isaac-Humanoid-Direct-v0 `__ .. |ant-direct-link| replace:: `Isaac-Ant-Direct-v0 `__ diff --git a/pyproject.toml b/pyproject.toml index 51d4375907..63ec9afd2a 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -36,6 +36,9 @@ extra_standard_library = [ "toml", "trimesh", "tqdm", + "torchvision", + "transformers", + "einops" # Needed for transformers, doesn't always auto-install ] # Imports from Isaac Sim and Omniverse known_third_party = [ diff --git a/source/extensions/omni.isaac.lab/config/extension.toml b/source/extensions/omni.isaac.lab/config/extension.toml index 1d78d22a46..4a6faf6114 100644 --- a/source/extensions/omni.isaac.lab/config/extension.toml +++ b/source/extensions/omni.isaac.lab/config/extension.toml @@ -1,7 +1,8 @@ [package] # Note: Semantic Versioning is used: https://semver.org/ -version = "0.27.6" + +version = "0.27.7" # Description title = "Isaac Lab framework for Robot Learning" diff --git a/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst b/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst index 16bc34b7ed..ecc0471794 100644 --- a/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst +++ b/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst @@ -1,6 +1,16 @@ Changelog --------- + +0.27.7 (2024-10-28) +~~~~~~~~~~~~~~~~~~~ + +Added +^^^^^ + +* Added frozen encoder feature extraction observation space with ResNet and Theia + + 0.27.6 (2024-10-25) ~~~~~~~~~~~~~~~~~~~ diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/observations.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/observations.py index fbae1d21cc..aca0f579ce 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/observations.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/observations.py @@ -17,11 +17,14 @@ import omni.isaac.lab.utils.math as math_utils from omni.isaac.lab.assets import Articulation, RigidObject from omni.isaac.lab.managers import SceneEntityCfg +from omni.isaac.lab.managers.manager_base import ManagerTermBase +from omni.isaac.lab.managers.manager_term_cfg import ObservationTermCfg from omni.isaac.lab.sensors import Camera, Imu, RayCaster, RayCasterCamera, TiledCamera if TYPE_CHECKING: from omni.isaac.lab.envs import ManagerBasedEnv, ManagerBasedRLEnv + """ Root state. """ @@ -273,6 +276,134 @@ def image( return images.clone() +class image_features(ManagerTermBase): + """Extracted image features from a pre-trained frozen encoder. + + This method calls the :meth:`image` function to retrieve images, and then performs + inference on those images. + """ + + def __init__(self, cfg: ObservationTermCfg, env: ManagerBasedEnv): + super().__init__(cfg, env) + from torchvision import models + from transformers import AutoModel + + def create_theia_model(model_name): + return { + "model": ( + lambda: AutoModel.from_pretrained(f"theaiinstitute/{model_name}", trust_remote_code=True) + .eval() + .to("cuda:0") + ), + "preprocess": lambda img: (img - torch.amin(img, dim=(1, 2), keepdim=True)) / ( + torch.amax(img, dim=(1, 2), keepdim=True) - torch.amin(img, dim=(1, 2), keepdim=True) + ), + "inference": lambda model, images: model.forward_feature( + images, do_rescale=False, interpolate_pos_encoding=True + ), + } + + def create_resnet_model(resnet_name): + return { + "model": lambda: getattr(models, resnet_name)(pretrained=True).eval().to("cuda:0"), + "preprocess": lambda img: ( + img.permute(0, 3, 1, 2) # Convert [batch, height, width, 3] -> [batch, 3, height, width] + - torch.tensor([0.485, 0.456, 0.406], device=img.device).view(1, 3, 1, 1) + ) / torch.tensor([0.229, 0.224, 0.225], device=img.device).view(1, 3, 1, 1), + "inference": lambda model, images: model(images), + } + + # List of Theia models + theia_models = [ + "theia-tiny-patch16-224-cddsv", + "theia-tiny-patch16-224-cdiv", + "theia-small-patch16-224-cdiv", + "theia-base-patch16-224-cdiv", + "theia-small-patch16-224-cddsv", + "theia-base-patch16-224-cddsv", + ] + + # List of ResNet models + resnet_models = ["resnet18", "resnet34", "resnet50", "resnet101"] + + self.default_model_zoo_cfg = {} + + # Add Theia models to the zoo + for model_name in theia_models: + self.default_model_zoo_cfg[model_name] = create_theia_model(model_name) + + # Add ResNet models to the zoo + for resnet_name in resnet_models: + self.default_model_zoo_cfg[resnet_name] = create_resnet_model(resnet_name) + + self.model_zoo_cfg = self.default_model_zoo_cfg + self.model_zoo = {} + + def __call__( + self, + env: ManagerBasedEnv, + sensor_cfg: SceneEntityCfg = SceneEntityCfg("tiled_camera"), + data_type: str = "rgb", + convert_perspective_to_orthogonal: bool = False, + model_zoo_cfg: dict | None = None, + model_name: str = "ResNet18", + model_device: str | None = "cuda:0", + reset_model: bool = False, + ) -> torch.Tensor: + """Extracted image features from a pre-trained frozen encoder. + + Args: + env: The environment. + sensor_cfg: The sensor configuration to poll. Defaults to SceneEntityCfg("tiled_camera"). + data_type: THe sensor configuration datatype. Defaults to "rgb". + convert_perspective_to_orthogonal: Whether to orthogonalize perspective depth images. + This is used only when the data type is "distance_to_camera". Defaults to False. + model_zoo_cfg: Map from model name to model configuration dictionary. Each model + configuration dictionary should include the following entries: + - "model": A callable that returns the model when invoked without arguments. + - "preprocess": A callable that processes the images and returns the preprocessed results. + - "inference": A callable that, when given the model and preprocessed images, + returns the extracted features. + model_name: The name of the model to use for inference. Defaults to "ResNet18". + model_device: The device to store and infer models on. This can be used help offload + computation from the main environment GPU. Defaults to "cuda:0". + reset_model: Initialize the model even if it already exists. Defaults to False. + + Returns: + torch.Tensor: the image features, on the same device as the image + """ + if model_zoo_cfg is not None: # use other than default + self.model_zoo_cfg.update(model_zoo_cfg) + + if model_name not in self.model_zoo or reset_model: + # The following allows to only load a desired subset of a model zoo into GPU memory + # as it becomes needed, in a "lazy" evaluation. + print(f"[INFO]: Adding {model_name} to the model zoo") + self.model_zoo[model_name] = self.model_zoo_cfg[model_name]["model"]() + + if model_device is not None and self.model_zoo[model_name].device != model_device: + # want to offload vision model inference to another device + self.model_zoo[model_name] = self.model_zoo[model_name].to(model_device) + + images = image( + env=env, + sensor_cfg=sensor_cfg, + data_type=data_type, + convert_perspective_to_orthogonal=convert_perspective_to_orthogonal, + normalize=True, # want this for training stability + ) + + image_device = images.device + + if model_device is not None: + images = images.to(model_device) + + proc_images = self.model_zoo_cfg[model_name]["preprocess"](images) + features = self.model_zoo_cfg[model_name]["inference"](self.model_zoo[model_name], proc_images) + + return features.to(image_device).clone() + + """ Actions. """ diff --git a/source/extensions/omni.isaac.lab_tasks/config/extension.toml b/source/extensions/omni.isaac.lab_tasks/config/extension.toml index a0b2718609..544cd97377 100644 --- a/source/extensions/omni.isaac.lab_tasks/config/extension.toml +++ b/source/extensions/omni.isaac.lab_tasks/config/extension.toml @@ -1,7 +1,7 @@ [package] # Note: Semantic Versioning is used: https://semver.org/ -version = "0.10.10" +version = "0.10.12" # Description title = "Isaac Lab Environments" diff --git a/source/extensions/omni.isaac.lab_tasks/docs/CHANGELOG.rst b/source/extensions/omni.isaac.lab_tasks/docs/CHANGELOG.rst index a0a2b39346..c194591492 100644 --- a/source/extensions/omni.isaac.lab_tasks/docs/CHANGELOG.rst +++ b/source/extensions/omni.isaac.lab_tasks/docs/CHANGELOG.rst @@ -1,6 +1,23 @@ Changelog --------- +0.10.12 (2024-10-28) +~~~~~~~~~~~~~~~~~~~~ + +Changed +^^^^^^^ + +* Changed manager-based vision cartpole environment names from Isaac-Cartpole-RGB-Camera-v0 + and Isaac-Cartpole-Depth-Camera-v0 to Isaac-Cartpole-RGB-v0 and Isaac-Cartpole-Depth-v0 + +0.10.11 (2024-10-28) +~~~~~~~~~~~~~~~~~~~~ + +Added +^^^^^ + +* Added feature extracted observation cartpole examples. + 0.10.10 (2024-10-25) ~~~~~~~~~~~~~~~~~~~~ diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/shadow_hand/feature_extractor.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/shadow_hand/feature_extractor.py index 1dbfb39b1a..fc92bbfb1b 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/shadow_hand/feature_extractor.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/shadow_hand/feature_extractor.py @@ -7,7 +7,6 @@ import os import torch import torch.nn as nn - import torchvision from omni.isaac.lab.sensors import save_images_to_file diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/cartpole/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/cartpole/__init__.py index 7a3070d775..43040be70a 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/cartpole/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/cartpole/__init__.py @@ -10,7 +10,12 @@ import gymnasium as gym from . import agents -from .cartpole_camera_env_cfg import CartpoleDepthCameraEnvCfg, CartpoleRGBCameraEnvCfg +from .cartpole_camera_env_cfg import ( + CartpoleDepthCameraEnvCfg, + CartpoleResNet18CameraEnvCfg, + CartpoleRGBCameraEnvCfg, + CartpoleTheiaTinyCameraEnvCfg, +) from .cartpole_env_cfg import CartpoleEnvCfg ## @@ -31,7 +36,7 @@ ) gym.register( - id="Isaac-Cartpole-RGB-Camera-v0", + id="Isaac-Cartpole-RGB-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ @@ -41,7 +46,7 @@ ) gym.register( - id="Isaac-Cartpole-Depth-Camera-v0", + id="Isaac-Cartpole-Depth-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ @@ -49,3 +54,23 @@ "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_camera_ppo_cfg.yaml", }, ) + +gym.register( + id="Isaac-Cartpole-RGB-ResNet18-v0", + entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", + disable_env_checker=True, + kwargs={ + "env_cfg_entry_point": CartpoleResNet18CameraEnvCfg, + "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_feature_ppo_cfg.yaml", + }, +) + +gym.register( + id="Isaac-Cartpole-RGB-TheiaTiny-v0", + entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", + disable_env_checker=True, + kwargs={ + "env_cfg_entry_point": CartpoleTheiaTinyCameraEnvCfg, + "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_feature_ppo_cfg.yaml", + }, +) diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/cartpole/agents/rl_games_feature_ppo_cfg.yaml b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/cartpole/agents/rl_games_feature_ppo_cfg.yaml new file mode 100644 index 0000000000..18e0ffd022 --- /dev/null +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/cartpole/agents/rl_games_feature_ppo_cfg.yaml @@ -0,0 +1,79 @@ +params: + seed: 42 + + # environment wrapper clipping + env: + # added to the wrapper + clip_observations: 5.0 + # can make custom wrapper? + clip_actions: 1.0 + + algo: + name: a2c_continuous + + model: + name: continuous_a2c_logstd + + # doesn't have this fine grained control but made it close + network: + name: actor_critic + separate: False + space: + continuous: + mu_activation: None + sigma_activation: None + + mu_init: + name: default + sigma_init: + name: const_initializer + val: 0 + fixed_sigma: True + mlp: + units: [256] + activation: elu + d2rl: False + + initializer: + name: default + regularizer: + name: None + + load_checkpoint: False # flag which sets whether to load the checkpoint + load_path: '' # path to the checkpoint to load + + config: + name: cartpole_features + env_name: rlgpu + device: 'cuda:0' + device_name: 'cuda:0' + multi_gpu: False + ppo: True + mixed_precision: False + normalize_input: True + normalize_value: True + value_bootstraop: True + num_actors: -1 # configured from the script (based on num_envs) + reward_shaper: + scale_value: 1.0 + normalize_advantage: True + gamma: 0.99 + tau : 0.95 + learning_rate: 3e-4 + lr_schedule: adaptive + kl_threshold: 0.008 + score_to_win: 20000 + max_epochs: 5000 + save_best_after: 50 + save_frequency: 25 + grad_norm: 1.0 + entropy_coef: 0.0 + truncate_grads: True + e_clip: 0.2 + horizon_length: 16 + minibatch_size: 2048 + mini_epochs: 8 + critic_coef: 4 + clip_value: True + seq_length: 4 + bounds_loss_coef: 0.0001 diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/cartpole/cartpole_camera_env_cfg.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/cartpole/cartpole_camera_env_cfg.py index ce5a6c90b8..f767a21962 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/cartpole/cartpole_camera_env_cfg.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/cartpole/cartpole_camera_env_cfg.py @@ -78,7 +78,7 @@ class DepthObservationsCfg: """Observation specifications for the MDP.""" @configclass - class DepthCameraPolicyCfg(RGBObservationsCfg.RGBCameraPolicyCfg): + class DepthCameraPolicyCfg(ObsGroup): """Observations for policy group with depth images.""" image = ObsTerm( @@ -88,6 +88,43 @@ class DepthCameraPolicyCfg(RGBObservationsCfg.RGBCameraPolicyCfg): policy: ObsGroup = DepthCameraPolicyCfg() +@configclass +class ResNet18ObservationCfg: + """Observation specifications for the MDP.""" + + @configclass + class ResNet18FeaturesCameraPolicyCfg(ObsGroup): + """Observations for policy group with features extracted from RGB images with a frozen ResNet18.""" + + image = ObsTerm( + func=mdp.image_features, + params={"sensor_cfg": SceneEntityCfg("tiled_camera"), "data_type": "rgb", "model_name": "resnet18"}, + ) + + policy: ObsGroup = ResNet18FeaturesCameraPolicyCfg() + + +@configclass +class TheiaTinyObservationCfg: + """Observation specifications for the MDP.""" + + @configclass + class TheiaTinyFeaturesCameraPolicyCfg(ObsGroup): + """Observations for policy group with features extracted from RGB images with a frozen Theia-Tiny Transformer""" + + image = ObsTerm( + func=mdp.image_features, + params={ + "sensor_cfg": SceneEntityCfg("tiled_camera"), + "data_type": "rgb", + "model_name": "theia-tiny-patch16-224-cddsv", + "model_device": "cuda:0", + }, + ) + + policy: ObsGroup = TheiaTinyFeaturesCameraPolicyCfg() + + ## # Environment configuration ## @@ -107,3 +144,20 @@ class CartpoleDepthCameraEnvCfg(CartpoleEnvCfg): scene: CartpoleSceneCfg = CartpoleDepthCameraSceneCfg(num_envs=1024, env_spacing=20) observations: DepthObservationsCfg = DepthObservationsCfg() + + +@configclass +class CartpoleResNet18CameraEnvCfg(CartpoleRGBCameraEnvCfg): + observations: ResNet18ObservationCfg = ResNet18ObservationCfg() + + +@configclass +class CartpoleTheiaTinyCameraEnvCfg(CartpoleRGBCameraEnvCfg): + """ + Due to TheiaTiny's size in GPU memory, we reduce the number of environments by default. + This helps reduce the possibility of crashing on more modest hardware. + The following configuration uses ~12gb VRAM at peak. + """ + + scene: CartpoleSceneCfg = CartpoleRGBCameraSceneCfg(num_envs=128, env_spacing=20) + observations: TheiaTinyObservationCfg = TheiaTinyObservationCfg() From 3e0d7ad77fe9475f09758cb009bd778f12bca2df Mon Sep 17 00:00:00 2001 From: OOmotuyi <159472067+OOmotuyi@users.noreply.github.com> Date: Wed, 30 Oct 2024 13:38:50 -0700 Subject: [PATCH 044/111] Adds figures for manager-based and direct RL environments (#1337) # Description Adding reference flow diagram for manager-based and direct RL task workflows ## Type of change - Documentation Change ## Checklist - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [x] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [x] I have added tests that prove my fix is effective or that my feature works - [x] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [ ] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --------- Signed-off-by: OOmotuyi <159472067+OOmotuyi@users.noreply.github.com> --- .../core-concepts/Direct-basedTaskWorkflow.jpg | Bin 0 -> 60552 bytes .../Manager-basedTaskWorkflow.jpg | Bin 0 -> 119227 bytes .../overview/core-concepts/task_workflows.rst | 8 ++++++++ 3 files changed, 8 insertions(+) create mode 100644 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z1qhS=p>_>wI?qO+Tk`rLH3`-s2(=S9ZZ3J@eNHz22Xem`{7-H*LXYJ8%YjZK_`9?s zl{SV@E+qH$vhhcJyBVOfMj!zkNp!d-*Z0oP{(F2vM2RQu)mkM!_g;LD-UL&i5@(C6 z6Kix?l4EN~r}HM@V6PXY@~9tc}UP8Y>43Mr5j2z#zt8 zF%nT=8wZ6jhi{gMcLPUA=X_s%u$VMT(HlAKJyAXu@WAG`Hnz<+B?X;2Vx8bhl{FY^mCD(!mWcT!7%hdu`KvCep%$ z46pQ$R&h|AYJK{ptDSd0?N+bZ&3jCi{v@(*ihtP#Rgnw!7;#_or#g1su>PoH)sPyV zF1#R7>6Urg!pQY~adqK<6>6AOdf7`X*biTloObID-iF`ZWOt+_z9QXqq`7!kpH|~_ z)J;XyVFpZ}@kNYmo8MekxP&dlBp6sU)t?_RN>5sa_oO|CzXPww2lv>NscfstcPQfP z&Aj6!y*CMvIvGT#nsJSJ+7BpT+k7uF3>E)_;9l)j&fHvlJ)`1qDOiAe{%JOyB7yO>IVZ z_z?RmGt$mg^vq8>c@M6Eplqsn1h(`q&d|yBft`!VWJK?0j%l~Mb)zH5io?=Dy;Pfb zjpyk={%F!PqvGm+(0RCjo(i>%LK5U3Cq7<+8*-i45_YB|zjhR#azA${U4=;v)6;iQ zKu{$6*cdz&IB~hFLPP*)qO42fS-LkDn~< zh^kvg`Lodt#{@)4qfyi5YpvlPG2;On>4vRe>TxqCULHiZc0)yl!v3iI-)A=d8V{%W z?$-7}N)A?AeGX0Pw_}J)r Date: Thu, 31 Oct 2024 13:41:43 +0100 Subject: [PATCH 045/111] Fixes the image feature extractor in observations (#1340) # Description - Fixes the image feature extractor in observations - Adds missing dependencies in setup.py ## Type of change - Bug fix (non-breaking change which fixes an issue) ## Checklist - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [x] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [ ] I have added tests that prove my fix is effective or that my feature works - [ ] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [x] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --- CONTRIBUTORS.md | 1 + docs/licenses/dependencies/einops-license.txt | 21 ++ .../dependencies/transformers-license.txt | 203 ++++++++++++ docs/source/_static/refs.bib | 15 + .../isaaclab.python.headless.rendering.kit | 4 + source/apps/isaaclab.python.rendering.kit | 4 + .../omni/isaac/lab/envs/mdp/observations.py | 296 ++++++++++++------ source/extensions/omni.isaac.lab/setup.py | 3 + .../agents/rl_games_feature_ppo_cfg.yaml | 2 +- .../cartpole/cartpole_camera_env_cfg.py | 29 +- .../classic/cartpole/cartpole_env_cfg.py | 5 - 11 files changed, 471 insertions(+), 112 deletions(-) create mode 100644 docs/licenses/dependencies/einops-license.txt create mode 100644 docs/licenses/dependencies/transformers-license.txt diff --git a/CONTRIBUTORS.md b/CONTRIBUTORS.md index e90992ca29..e59d3de8d4 100644 --- a/CONTRIBUTORS.md +++ b/CONTRIBUTORS.md @@ -50,6 +50,7 @@ Guidelines for modifications: * Jan Kerner * Jean Tampon * Jia Lin Yuan +* Jinghuan Shang * Jingzhou Liu * Johnson Sun * Kaixi Bao diff --git a/docs/licenses/dependencies/einops-license.txt b/docs/licenses/dependencies/einops-license.txt new file mode 100644 index 0000000000..3a654e9066 --- /dev/null +++ b/docs/licenses/dependencies/einops-license.txt @@ -0,0 +1,21 @@ +MIT License + +Copyright (c) 2018 Alex Rogozhnikov + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. diff --git a/docs/licenses/dependencies/transformers-license.txt b/docs/licenses/dependencies/transformers-license.txt new file mode 100644 index 0000000000..68b7d66c97 --- /dev/null +++ b/docs/licenses/dependencies/transformers-license.txt @@ -0,0 +1,203 @@ +Copyright 2018- The Hugging Face team. All rights reserved. + + Apache License + Version 2.0, January 2004 + http://www.apache.org/licenses/ + + TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION + + 1. 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We also recommend that a + file or class name and description of purpose be included on the + same "printed page" as the copyright notice for easier + identification within third-party archives. + + Copyright [yyyy] [name of copyright owner] + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. diff --git a/docs/source/_static/refs.bib b/docs/source/_static/refs.bib index e7f82d17da..c87c90c076 100644 --- a/docs/source/_static/refs.bib +++ b/docs/source/_static/refs.bib @@ -139,3 +139,18 @@ @article{mittal2023orbit pages={3740-3747}, doi={10.1109/LRA.2023.3270034} } + +@article{shang2024theia, + title={Theia: Distilling diverse vision foundation models for robot learning}, + author={Shang, Jinghuan and Schmeckpeper, Karl and May, Brandon B and Minniti, Maria Vittoria and Kelestemur, Tarik and Watkins, David and Herlant, Laura}, + journal={arXiv preprint arXiv:2407.20179}, + year={2024} +} + +@inproceedings{he2016deep, + title={Deep residual learning for image recognition}, + author={He, Kaiming and Zhang, Xiangyu and Ren, Shaoqing and Sun, Jian}, + booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition}, + pages={770--778}, + year={2016} +} diff --git a/source/apps/isaaclab.python.headless.rendering.kit b/source/apps/isaaclab.python.headless.rendering.kit index 5d14c551dc..0e808021ee 100644 --- a/source/apps/isaaclab.python.headless.rendering.kit +++ b/source/apps/isaaclab.python.headless.rendering.kit @@ -35,6 +35,10 @@ app.folder = "${exe-path}/" app.name = "Isaac-Sim" app.version = "4.2.0" +# Disable print outs on extension startup information +# this only disables the app print_and_log function +app.enableStdoutOutput = false + # set the default ros bridge to disable on startup isaac.startup.ros_bridge_extension = "" diff --git a/source/apps/isaaclab.python.rendering.kit b/source/apps/isaaclab.python.rendering.kit index 539b109a19..abd272a5fe 100644 --- a/source/apps/isaaclab.python.rendering.kit +++ b/source/apps/isaaclab.python.rendering.kit @@ -35,6 +35,10 @@ app.folder = "${exe-path}/" app.name = "Isaac-Sim" app.version = "4.2.0" +# Disable print outs on extension startup information +# this only disables the app print_and_log function +app.enableStdoutOutput = false + # set the default ros bridge to disable on startup isaac.startup.ros_bridge_extension = "" diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/observations.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/observations.py index aca0f579ce..2c97cf151e 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/observations.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/observations.py @@ -186,42 +186,46 @@ def body_incoming_wrench(env: ManagerBasedEnv, asset_cfg: SceneEntityCfg) -> tor def imu_orientation(env: ManagerBasedEnv, asset_cfg: SceneEntityCfg = SceneEntityCfg("imu")) -> torch.Tensor: - """Imu sensor orientation w.r.t the env.scene.origin. + """Imu sensor orientation in the simulation world frame. Args: env: The environment. - asset_cfg: The SceneEntity associated with an Imu sensor. + asset_cfg: The SceneEntity associated with an IMU sensor. Defaults to SceneEntityCfg("imu"). Returns: - Orientation quaternion (wxyz), shape of torch.tensor is (num_env,4). + Orientation in the world frame in (w, x, y, z) quaternion form. Shape is (num_envs, 4). """ + # extract the used quantities (to enable type-hinting) asset: Imu = env.scene[asset_cfg.name] + # return the orientation quaternion return asset.data.quat_w def imu_ang_vel(env: ManagerBasedEnv, asset_cfg: SceneEntityCfg = SceneEntityCfg("imu")) -> torch.Tensor: - """Imu sensor angular velocity w.r.t. env.scene.origin expressed in the sensor frame. + """Imu sensor angular velocity w.r.t. environment origin expressed in the sensor frame. Args: env: The environment. - asset_cfg: The SceneEntity associated with an Imu sensor. + asset_cfg: The SceneEntity associated with an IMU sensor. Defaults to SceneEntityCfg("imu"). Returns: - Angular velocity (rad/s), shape of torch.tensor is (num_env,3). + The angular velocity (rad/s) in the sensor frame. Shape is (num_envs, 3). """ + # extract the used quantities (to enable type-hinting) asset: Imu = env.scene[asset_cfg.name] + # return the angular velocity return asset.data.ang_vel_b def imu_lin_acc(env: ManagerBasedEnv, asset_cfg: SceneEntityCfg = SceneEntityCfg("imu")) -> torch.Tensor: - """Imu sensor linear acceleration w.r.t. env.scene.origin expressed in sensor frame. + """Imu sensor linear acceleration w.r.t. the environment origin expressed in sensor frame. Args: env: The environment. - asset_cfg: The SceneEntity associated with an Imu sensor. + asset_cfg: The SceneEntity associated with an IMU sensor. Defaults to SceneEntityCfg("imu"). Returns: - linear acceleration (m/s^2), shape of torch.tensor is (num_env,3). + The linear acceleration (m/s^2) in the sensor frame. Shape is (num_envs, 3). """ asset: Imu = env.scene[asset_cfg.name] return asset.data.lin_acc_b @@ -279,42 +283,56 @@ def image( class image_features(ManagerTermBase): """Extracted image features from a pre-trained frozen encoder. - This method calls the :meth:`image` function to retrieve images, and then performs - inference on those images. + This term uses models from the model zoo in PyTorch and extracts features from the images. + + It calls the :func:`image` function to get the images and then processes them using the model zoo. + + A user can provide their own model zoo configuration to use different models for feature extraction. + The model zoo configuration should be a dictionary that maps different model names to a dictionary + that defines the model, preprocess and inference functions. The dictionary should have the following + entries: + + - "model": A callable that returns the model when invoked without arguments. + - "reset": A callable that resets the model. This is useful when the model has a state that needs to be reset. + - "inference": A callable that, when given the model and the images, returns the extracted features. + + If the model zoo configuration is not provided, the default model zoo configurations are used. The default + model zoo configurations include the models from Theia :cite:`shang2024theia` and ResNet :cite:`he2016deep`. + These models are loaded from `Hugging-Face transformers `_ and + `PyTorch torchvision `_ respectively. + + Args: + sensor_cfg: The sensor configuration to poll. Defaults to SceneEntityCfg("tiled_camera"). + data_type: The sensor data type. Defaults to "rgb". + convert_perspective_to_orthogonal: Whether to orthogonalize perspective depth images. + This is used only when the data type is "distance_to_camera". Defaults to False. + model_zoo_cfg: A user-defined dictionary that maps different model names to their respective configurations. + Defaults to None. If None, the default model zoo configurations are used. + model_name: The name of the model to use for inference. Defaults to "resnet18". + model_device: The device to store and infer the model on. This is useful when offloading the computation + from the environment simulation device. Defaults to the environment device. + inference_kwargs: Additional keyword arguments to pass to the inference function. Defaults to None, + which means no additional arguments are passed. + + Returns: + The extracted features tensor. Shape is (num_envs, feature_dim). + + Raises: + ValueError: When the model name is not found in the provided model zoo configuration. + ValueError: When the model name is not found in the default model zoo configuration. """ def __init__(self, cfg: ObservationTermCfg, env: ManagerBasedEnv): + # initialize the base class super().__init__(cfg, env) - from torchvision import models - from transformers import AutoModel - def create_theia_model(model_name): - return { - "model": ( - lambda: AutoModel.from_pretrained(f"theaiinstitute/{model_name}", trust_remote_code=True) - .eval() - .to("cuda:0") - ), - "preprocess": lambda img: (img - torch.amin(img, dim=(1, 2), keepdim=True)) / ( - torch.amax(img, dim=(1, 2), keepdim=True) - torch.amin(img, dim=(1, 2), keepdim=True) - ), - "inference": lambda model, images: model.forward_feature( - images, do_rescale=False, interpolate_pos_encoding=True - ), - } - - def create_resnet_model(resnet_name): - return { - "model": lambda: getattr(models, resnet_name)(pretrained=True).eval().to("cuda:0"), - "preprocess": lambda img: ( - img.permute(0, 3, 1, 2) # Convert [batch, height, width, 3] -> [batch, 3, height, width] - - torch.tensor([0.485, 0.456, 0.406], device=img.device).view(1, 3, 1, 1) - ) / torch.tensor([0.229, 0.224, 0.225], device=img.device).view(1, 3, 1, 1), - "inference": lambda model, images: model(images), - } + # extract parameters from the configuration + self.model_zoo_cfg: dict = cfg.params.get("model_zoo_cfg") # type: ignore + self.model_name: str = cfg.params.get("model_name", "resnet18") # type: ignore + self.model_device: str = cfg.params.get("model_device", env.device) # type: ignore - # List of Theia models - theia_models = [ + # List of Theia models - These are configured through `_prepare_theia_transformer_model` function + default_theia_models = [ "theia-tiny-patch16-224-cddsv", "theia-tiny-patch16-224-cdiv", "theia-small-patch16-224-cdiv", @@ -322,22 +340,43 @@ def create_resnet_model(resnet_name): "theia-small-patch16-224-cddsv", "theia-base-patch16-224-cddsv", ] - - # List of ResNet models - resnet_models = ["resnet18", "resnet34", "resnet50", "resnet101"] - - self.default_model_zoo_cfg = {} - - # Add Theia models to the zoo - for model_name in theia_models: - self.default_model_zoo_cfg[model_name] = create_theia_model(model_name) - - # Add ResNet models to the zoo - for resnet_name in resnet_models: - self.default_model_zoo_cfg[resnet_name] = create_resnet_model(resnet_name) - - self.model_zoo_cfg = self.default_model_zoo_cfg - self.model_zoo = {} + # List of ResNet models - These are configured through `_prepare_resnet_model` function + default_resnet_models = ["resnet18", "resnet34", "resnet50", "resnet101"] + + # Check if model name is specified in the model zoo configuration + if self.model_zoo_cfg is not None and self.model_name not in self.model_zoo_cfg: + raise ValueError( + f"Model name '{self.model_name}' not found in the provided model zoo configuration." + " Please add the model to the model zoo configuration or use a different model name." + f" Available models in the provided list: {list(self.model_zoo_cfg.keys())}." + "\nHint: If you want to use a default model, consider using one of the following models:" + f" {default_theia_models + default_resnet_models}. In this case, you can remove the" + " 'model_zoo_cfg' parameter from the observation term configuration." + ) + if self.model_zoo_cfg is None: + if self.model_name in default_theia_models: + model_config = self._prepare_theia_transformer_model(self.model_name, self.model_device) + elif self.model_name in default_resnet_models: + model_config = self._prepare_resnet_model(self.model_name, self.model_device) + else: + raise ValueError( + f"Model name '{self.model_name}' not found in the default model zoo configuration." + f" Available models: {default_theia_models + default_resnet_models}." + ) + else: + model_config = self.model_zoo_cfg[self.model_name] + + # Retrieve the model, preprocess and inference functions + self._model = model_config["model"]() + self._reset_fn = model_config.get("reset") + self._inference_fn = model_config["inference"] + + def reset(self, env_ids: torch.Tensor | None = None): + # reset the model if a reset function is provided + # this might be useful when the model has a state that needs to be reset + # for example: video transformers + if self._reset_fn is not None: + self._reset_fn(self._model, env_ids) def __call__( self, @@ -346,62 +385,123 @@ def __call__( data_type: str = "rgb", convert_perspective_to_orthogonal: bool = False, model_zoo_cfg: dict | None = None, - model_name: str = "ResNet18", - model_device: str | None = "cuda:0", - reset_model: bool = False, + model_name: str = "resnet18", + model_device: str | None = None, + inference_kwargs: dict | None = None, ) -> torch.Tensor: - """Extracted image features from a pre-trained frozen encoder. + # obtain the images from the sensor + image_data = image( + env=env, + sensor_cfg=sensor_cfg, + data_type=data_type, + convert_perspective_to_orthogonal=convert_perspective_to_orthogonal, + normalize=False, # we pre-process based on model + ) + # store the device of the image + image_device = image_data.device + # forward the images through the model + features = self._inference_fn(self._model, image_data, **(inference_kwargs or {})) + + # move the features back to the image device + return features.detach().to(image_device) + + """ + Helper functions. + """ + + def _prepare_theia_transformer_model(self, model_name: str, model_device: str) -> dict: + """Prepare the Theia transformer model for inference. Args: - env: The environment. - sensor_cfg: The sensor configuration to poll. Defaults to SceneEntityCfg("tiled_camera"). - data_type: THe sensor configuration datatype. Defaults to "rgb". - convert_perspective_to_orthogonal: Whether to orthogonalize perspective depth images. - This is used only when the data type is "distance_to_camera". Defaults to False. - model_zoo_cfg: Map from model name to model configuration dictionary. Each model - configuration dictionary should include the following entries: - - "model": A callable that returns the model when invoked without arguments. - - "preprocess": A callable that processes the images and returns the preprocessed results. - - "inference": A callable that, when given the model and preprocessed images, - returns the extracted features. - model_name: The name of the model to use for inference. Defaults to "ResNet18". - model_device: The device to store and infer models on. This can be used help offload - computation from the main environment GPU. Defaults to "cuda:0". - reset_model: Initialize the model even if it already exists. Defaults to False. + model_name: The name of the Theia transformer model to prepare. + model_device: The device to store and infer the model on. Returns: - torch.Tensor: the image features, on the same device as the image + A dictionary containing the model and inference functions. """ - if model_zoo_cfg is not None: # use other than default - self.model_zoo_cfg.update(model_zoo_cfg) + from transformers import AutoModel - if model_name not in self.model_zoo or reset_model: - # The following allows to only load a desired subset of a model zoo into GPU memory - # as it becomes needed, in a "lazy" evaluation. - print(f"[INFO]: Adding {model_name} to the model zoo") - self.model_zoo[model_name] = self.model_zoo_cfg[model_name]["model"]() + def _load_model() -> torch.nn.Module: + """Load the Theia transformer model.""" + model = AutoModel.from_pretrained(f"theaiinstitute/{model_name}", trust_remote_code=True).eval() + return model.to(model_device) - if model_device is not None and self.model_zoo[model_name].device != model_device: - # want to offload vision model inference to another device - self.model_zoo[model_name] = self.model_zoo[model_name].to(model_device) + def _inference(model, images: torch.Tensor) -> torch.Tensor: + """Inference the Theia transformer model. - images = image( - env=env, - sensor_cfg=sensor_cfg, - data_type=data_type, - convert_perspective_to_orthogonal=convert_perspective_to_orthogonal, - normalize=True, # want this for training stability - ) + Args: + model: The Theia transformer model. + images: The preprocessed image tensor. Shape is (num_envs, height, width, channel). + + Returns: + The extracted features tensor. Shape is (num_envs, feature_dim). + """ + # Move the image to the model device + image_proc = images.to(model_device) + # permute the image to (num_envs, channel, height, width) + image_proc = image_proc.permute(0, 3, 1, 2).float() / 255.0 + # Normalize the image + mean = torch.tensor([0.485, 0.456, 0.406], device=model_device).view(1, 3, 1, 1) + std = torch.tensor([0.229, 0.224, 0.225], device=model_device).view(1, 3, 1, 1) + image_proc = (image_proc - mean) / std + + # Taken from Transformers; inference converted to be GPU only + features = model.backbone.model(pixel_values=image_proc, interpolate_pos_encoding=True) + return features.last_hidden_state[:, 1:] + + # return the model, preprocess and inference functions + return {"model": _load_model, "inference": _inference} - image_device = images.device + def _prepare_resnet_model(self, model_name: str, model_device: str) -> dict: + """Prepare the ResNet model for inference. - if model_device is not None: - images = images.to(model_device) + Args: + model_name: The name of the ResNet model to prepare. + model_device: The device to store and infer the model on. + + Returns: + A dictionary containing the model and inference functions. + """ + from torchvision import models - proc_images = self.model_zoo_cfg[model_name]["preprocess"](images) - features = self.model_zoo_cfg[model_name]["inference"](self.model_zoo[model_name], proc_images) + def _load_model() -> torch.nn.Module: + """Load the ResNet model.""" + # map the model name to the weights + resnet_weights = { + "resnet18": "ResNet18_Weights.IMAGENET1K_V1", + "resnet34": "ResNet34_Weights.IMAGENET1K_V1", + "resnet50": "ResNet50_Weights.IMAGENET1K_V1", + "resnet101": "ResNet101_Weights.IMAGENET1K_V1", + } - return features.to(image_device).clone() + # load the model + model = getattr(models, model_name)(weights=resnet_weights[model_name]).eval() + return model.to(model_device) + + def _inference(model, images: torch.Tensor) -> torch.Tensor: + """Inference the ResNet model. + + Args: + model: The ResNet model. + images: The preprocessed image tensor. Shape is (num_envs, channel, height, width). + + Returns: + The extracted features tensor. Shape is (num_envs, feature_dim). + """ + # move the image to the model device + image_proc = images.to(model_device) + # permute the image to (num_envs, channel, height, width) + image_proc = image_proc.permute(0, 3, 1, 2).float() / 255.0 + # normalize the image + mean = torch.tensor([0.485, 0.456, 0.406], device=model_device).view(1, 3, 1, 1) + std = torch.tensor([0.229, 0.224, 0.225], device=model_device).view(1, 3, 1, 1) + image_proc = (image_proc - mean) / std + + # forward the image through the model + return model(image_proc) + + # return the model, preprocess and inference functions + return {"model": _load_model, "inference": _inference} """ diff --git a/source/extensions/omni.isaac.lab/setup.py b/source/extensions/omni.isaac.lab/setup.py index 3b68d3c84f..01229c8c4f 100644 --- a/source/extensions/omni.isaac.lab/setup.py +++ b/source/extensions/omni.isaac.lab/setup.py @@ -31,6 +31,9 @@ # procedural-generation "trimesh", "pyglet<2", + # image processing + "transformers", + "einops", # needed for transformers, doesn't always auto-install ] PYTORCH_INDEX_URL = ["https://download.pytorch.org/whl/cu118"] diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/cartpole/agents/rl_games_feature_ppo_cfg.yaml b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/cartpole/agents/rl_games_feature_ppo_cfg.yaml index 18e0ffd022..41e265e9f2 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/cartpole/agents/rl_games_feature_ppo_cfg.yaml +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/cartpole/agents/rl_games_feature_ppo_cfg.yaml @@ -63,7 +63,7 @@ params: lr_schedule: adaptive kl_threshold: 0.008 score_to_win: 20000 - max_epochs: 5000 + max_epochs: 200 save_best_after: 50 save_frequency: 25 grad_norm: 1.0 diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/cartpole/cartpole_camera_env_cfg.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/cartpole/cartpole_camera_env_cfg.py index f767a21962..35c828d2cb 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/cartpole/cartpole_camera_env_cfg.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/cartpole/cartpole_camera_env_cfg.py @@ -134,30 +134,43 @@ class TheiaTinyFeaturesCameraPolicyCfg(ObsGroup): class CartpoleRGBCameraEnvCfg(CartpoleEnvCfg): """Configuration for the cartpole environment with RGB camera.""" - scene: CartpoleSceneCfg = CartpoleRGBCameraSceneCfg(num_envs=1024, env_spacing=20) + scene: CartpoleRGBCameraSceneCfg = CartpoleRGBCameraSceneCfg(num_envs=1024, env_spacing=20) observations: RGBObservationsCfg = RGBObservationsCfg() + def __post_init__(self): + super().__post_init__() + # remove ground as it obstructs the camera + self.scene.ground = None + # viewer settings + self.viewer.eye = (7.0, 0.0, 2.5) + self.viewer.lookat = (0.0, 0.0, 2.5) + @configclass class CartpoleDepthCameraEnvCfg(CartpoleEnvCfg): """Configuration for the cartpole environment with depth camera.""" - scene: CartpoleSceneCfg = CartpoleDepthCameraSceneCfg(num_envs=1024, env_spacing=20) + scene: CartpoleDepthCameraSceneCfg = CartpoleDepthCameraSceneCfg(num_envs=1024, env_spacing=20) observations: DepthObservationsCfg = DepthObservationsCfg() + def __post_init__(self): + super().__post_init__() + # remove ground as it obstructs the camera + self.scene.ground = None + # viewer settings + self.viewer.eye = (7.0, 0.0, 2.5) + self.viewer.lookat = (0.0, 0.0, 2.5) + @configclass class CartpoleResNet18CameraEnvCfg(CartpoleRGBCameraEnvCfg): + """Configuration for the cartpole environment with ResNet18 features as observations.""" + observations: ResNet18ObservationCfg = ResNet18ObservationCfg() @configclass class CartpoleTheiaTinyCameraEnvCfg(CartpoleRGBCameraEnvCfg): - """ - Due to TheiaTiny's size in GPU memory, we reduce the number of environments by default. - This helps reduce the possibility of crashing on more modest hardware. - The following configuration uses ~12gb VRAM at peak. - """ + """Configuration for the cartpole environment with Theia-Tiny features as observations.""" - scene: CartpoleSceneCfg = CartpoleRGBCameraSceneCfg(num_envs=128, env_spacing=20) observations: TheiaTinyObservationCfg = TheiaTinyObservationCfg() diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/cartpole/cartpole_env_cfg.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/cartpole/cartpole_env_cfg.py index 84d88cba10..ca8784d8db 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/cartpole/cartpole_env_cfg.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/cartpole/cartpole_env_cfg.py @@ -48,11 +48,6 @@ class CartpoleSceneCfg(InteractiveSceneCfg): prim_path="/World/DomeLight", spawn=sim_utils.DomeLightCfg(color=(0.9, 0.9, 0.9), intensity=500.0), ) - distant_light = AssetBaseCfg( - prim_path="/World/DistantLight", - spawn=sim_utils.DistantLightCfg(color=(0.9, 0.9, 0.9), intensity=2500.0), - init_state=AssetBaseCfg.InitialStateCfg(rot=(0.738, 0.477, 0.477, 0.0)), - ) ## From f7e23806003218fed08fd01fd65ce03ad9993212 Mon Sep 17 00:00:00 2001 From: David Hoeller Date: Thu, 31 Oct 2024 14:39:57 +0100 Subject: [PATCH 046/111] Fixes the rigid body tests (#1345) # Description Fixes the commented out tests in the rigid body test ## Type of change - Bug fix (non-breaking change which fixes an issue) ## Checklist - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [ ] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [x] I have added tests that prove my fix is effective or that my feature works - [ ] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [x] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --- .../test/assets/test_rigid_object.py | 340 +++++++++--------- tools/per_test_timeouts.py | 1 + 2 files changed, 172 insertions(+), 169 deletions(-) diff --git a/source/extensions/omni.isaac.lab/test/assets/test_rigid_object.py b/source/extensions/omni.isaac.lab/test/assets/test_rigid_object.py index 429264c2c3..15fdc7ff03 100644 --- a/source/extensions/omni.isaac.lab/test/assets/test_rigid_object.py +++ b/source/extensions/omni.isaac.lab/test/assets/test_rigid_object.py @@ -426,175 +426,177 @@ def test_rigid_body_no_friction(self): cube_object.data.root_lin_vel_w, initial_velocity[:, :3], rtol=1e-5, atol=tolerance ) - # def test_rigid_body_with_static_friction(self): - # """Test that static friction applied to rigid object works as expected. - - # This test works by applying a force to the object and checking if the object moves or not based on the - # mu (coefficient of static friction) value set for the object. We set the static friction to be non-zero and - # apply a force to the object. When the force applied is below mu, the object should not move. When the force - # applied is above mu, the object should move. - # """ - # for num_cubes in (1, 2): - # for device in ("cuda:0", "cpu"): - # with self.subTest(num_cubes=num_cubes, device=device): - # with build_simulation_context(device=device, add_ground_plane=True, auto_add_lighting=True) as sim: - # cube_object, _ = generate_cubes_scene(num_cubes=num_cubes, height=0.03125, device=device) - - # # Create ground plane with no friction - # cfg = sim_utils.GroundPlaneCfg( - # physics_material=materials.RigidBodyMaterialCfg( - # static_friction=0.0, - # dynamic_friction=0.0, - # ) - # ) - # cfg.func("/World/GroundPlane", cfg) - - # # Play sim - # sim.reset() - - # # Set static friction to be non-zero - # static_friction_coefficient = 0.5 - # static_friction = torch.Tensor([[static_friction_coefficient]] * num_cubes) - # dynamic_friction = torch.zeros(num_cubes, 1) - # restitution = torch.FloatTensor(num_cubes, 1).uniform_(0.0, 0.2) - - # cube_object_materials = torch.cat([static_friction, dynamic_friction, restitution], dim=-1) - - # indices = torch.tensor(range(num_cubes), dtype=torch.int) - - # # Add friction to cube - # cube_object.root_physx_view.set_material_properties(cube_object_materials, indices) - - # # 2 cases: force applied is below and above mu - # # below mu: block should not move as the force applied is <= mu - # # above mu: block should move as the force applied is > mu - # for force in "below_mu", "above_mu": - # with self.subTest(force=force): - # external_wrench_b = torch.zeros((num_cubes, 1, 6), device=sim.device) - - # if force == "below_mu": - # external_wrench_b[:, 0, 0] = static_friction_coefficient * 0.999 - # else: - # external_wrench_b[:, 0, 0] = static_friction_coefficient * 1.001 - - # cube_object.set_external_force_and_torque( - # external_wrench_b[..., :3], - # external_wrench_b[..., 3:], - # ) - - # # Get root state - # initial_root_state = cube_object.data.root_state_w - - # # Simulate physics - # for _ in range(10): - # # perform rendering - # sim.step() - # # update object - # cube_object.update(sim.cfg.dt) - - # if force == "below_mu": - # # Assert that the block has not moved - # torch.testing.assert_close( - # cube_object.data.root_state_w, initial_root_state, rtol=1e-5, atol=1e-5 - # ) - # else: - # torch.testing.assert_close( - # cube_object.data.root_state_w, initial_root_state, rtol=1e-5, atol=1e-5 - # ) - - # def test_rigid_body_with_restitution(self): - # """Test that restitution when applied to rigid object works as expected. - - # This test works by dropping a block from a height and checking if the block bounces or not based on the - # restitution value set for the object. We set the restitution to be non-zero and drop the block from a height. - # When the restitution is 0, the block should not bounce. When the restitution is 1, the block should bounce - # with the same energy. When the restitution is between 0 and 1, the block should bounce with less energy. - - # """ - # for num_cubes in (1, 2): - # for device in ("cuda:0", "cpu"): - # with self.subTest(num_cubes=num_cubes, device=device): - # with build_simulation_context(device=device, add_ground_plane=True, auto_add_lighting=True) as sim: - # cube_object, _ = generate_cubes_scene(num_cubes=num_cubes, height=1.0, device=device) - - # # Create ground plane such that has a restitution of 1.0 (perfectly elastic collision) - # cfg = sim_utils.GroundPlaneCfg( - # physics_material=materials.RigidBodyMaterialCfg( - # restitution=1.0, - # ) - # ) - # cfg.func("/World/GroundPlane", cfg) - - # indices = torch.tensor(range(num_cubes), dtype=torch.int) - - # # Play sim - # sim.reset() - - # # 3 cases: inelastic, partially elastic, elastic - # # inelastic: resitution = 0, block should not bounce - # # partially elastic: 0 <= restitution <= 1, block should bounce with less energy - # # elastic: restitution = 1, block should bounce with same energy - # for expected_collision_type in "inelastic", "partially_elastic", "elastic": - # root_state = torch.zeros(1, 13, device=sim.device) - # root_state[0, 3] = 1.0 # To make orientation a quaternion - # root_state[0, 2] = 0.1 # Set an initial drop height - # root_state[0, 9] = -1.0 # Set an initial downward velocity - - # cube_object.write_root_state_to_sim(root_state=root_state) - - # prev_z_velocity = 0.0 - # curr_z_velocity = 0.0 - - # with self.subTest(expected_collision_type=expected_collision_type): - # # cube_object.reset() - # # Set static friction to be non-zero - # if expected_collision_type == "inelastic": - # restitution_coefficient = 0.0 - # elif expected_collision_type == "partially_elastic": - # restitution_coefficient = 0.5 - # else: - # restitution_coefficient = 1.0 - - # restitution = 0.5 - # static_friction = torch.zeros(num_cubes, 1) - # dynamic_friction = torch.zeros(num_cubes, 1) - # restitution = torch.Tensor([[restitution_coefficient]] * num_cubes) - - # cube_object_materials = torch.cat( - # [static_friction, dynamic_friction, restitution], dim=-1 - # ) - - # # Add friction to cube - # cube_object.root_physx_view.set_material_properties(cube_object_materials, indices) - - # curr_z_velocity = cube_object.data.root_lin_vel_w[:, 2] - - # while torch.all(curr_z_velocity <= 0.0): - # # Simulate physics - # curr_z_velocity = cube_object.data.root_lin_vel_w[:, 2] - - # # perform rendering - # sim.step() - - # # update object - # cube_object.update(sim.cfg.dt) - # if torch.all(curr_z_velocity <= 0.0): - # # Still in the air - # prev_z_velocity = curr_z_velocity - - # # We have made contact with the ground and can verify expected collision type - # # based on how velocity has changed after the collision - # if expected_collision_type == "inelastic": - # # Assert that the block has lost most energy by checking that the z velocity is < 1/2 previous - # # velocity. This is because the floor's resitution means it will bounce back an object that itself - # # has restitution set to 0.0 - # self.assertTrue(torch.all(torch.le(curr_z_velocity / 2, abs(prev_z_velocity)))) - # elif expected_collision_type == "partially_elastic": - # # Assert that the block has lost some energy by checking that the z velocity is less - # self.assertTrue(torch.all(torch.le(abs(curr_z_velocity), abs(prev_z_velocity)))) - # elif expected_collision_type == "elastic": - # # Assert that the block has not lost any energy by checking that the z velocity is the same - # torch.testing.assert_close(abs(curr_z_velocity), abs(prev_z_velocity)) + def test_rigid_body_with_static_friction(self): + """Test that static friction applied to rigid object works as expected. + + This test works by applying a force to the object and checking if the object moves or not based on the + mu (coefficient of static friction) value set for the object. We set the static friction to be non-zero and + apply a force to the object. When the force applied is below mu, the object should not move. When the force + applied is above mu, the object should move. + """ + for num_cubes in (1, 2): + for device in ("cuda", "cpu"): + with self.subTest(num_cubes=num_cubes, device=device): + with build_simulation_context( + device=device, dt=0.01, add_ground_plane=False, auto_add_lighting=True + ) as sim: + cube_object, _ = generate_cubes_scene(num_cubes=num_cubes, height=0.03125, device=device) + + # Create ground plane + static_friction_coefficient = 0.5 + cfg = sim_utils.GroundPlaneCfg( + physics_material=materials.RigidBodyMaterialCfg( + static_friction=static_friction_coefficient, + dynamic_friction=static_friction_coefficient, # This shouldn't be required but is due to a bug in PhysX + ) + ) + cfg.func("/World/GroundPlane", cfg) + + # Play sim + sim.reset() + + # Set static friction to be non-zero + # Dynamic friction also needs to be zero due to a bug in PhysX + static_friction = torch.Tensor([[static_friction_coefficient]] * num_cubes) + dynamic_friction = torch.Tensor([[static_friction_coefficient]] * num_cubes) + restitution = torch.zeros(num_cubes, 1) + + cube_object_materials = torch.cat([static_friction, dynamic_friction, restitution], dim=-1) + + indices = torch.tensor(range(num_cubes), dtype=torch.int) + + # Add friction to cube + cube_object.root_physx_view.set_material_properties(cube_object_materials, indices) + + # let everything settle + for _ in range(100): + sim.step() + cube_object.update(sim.cfg.dt) + cube_object.write_root_velocity_to_sim(torch.zeros((num_cubes, 6), device=sim.device)) + cube_mass = cube_object.root_physx_view.get_masses() + gravity_magnitude = abs(sim.cfg.gravity[2]) + # 2 cases: force applied is below and above mu + # below mu: block should not move as the force applied is <= mu + # above mu: block should move as the force applied is > mu + for force in "below_mu", "above_mu": + with self.subTest(force=force): + # set initial velocity to zero + cube_object.write_root_velocity_to_sim(torch.zeros((num_cubes, 6), device=sim.device)) + + external_wrench_b = torch.zeros((num_cubes, 1, 6), device=sim.device) + if force == "below_mu": + external_wrench_b[..., 0] = ( + static_friction_coefficient * cube_mass * gravity_magnitude * 0.99 + ) + else: + external_wrench_b[..., 0] = ( + static_friction_coefficient * cube_mass * gravity_magnitude * 1.01 + ) + + cube_object.set_external_force_and_torque( + external_wrench_b[..., :3], + external_wrench_b[..., 3:], + ) + + # Get root state + initial_root_pos = cube_object.data.root_pos_w.clone() + # Simulate physics + for _ in range(200): + # apply the wrench + cube_object.write_data_to_sim() + sim.step() + # update object + cube_object.update(sim.cfg.dt) + if force == "below_mu": + # Assert that the block has not moved + torch.testing.assert_close( + cube_object.data.root_pos_w, initial_root_pos, rtol=1e-3, atol=1e-3 + ) + if force == "above_mu": + self.assertTrue( + (cube_object.data.root_state_w[..., 0] - initial_root_pos[..., 0] > 0.02).all() + ) + + def test_rigid_body_with_restitution(self): + """Test that restitution when applied to rigid object works as expected. + + This test works by dropping a block from a height and checking if the block bounces or not based on the + restitution value set for the object. We set the restitution to be non-zero and drop the block from a height. + When the restitution is 0, the block should not bounce. When the restitution is between 0 and 1, the block + should bounce with less energy. + """ + for num_cubes in (1, 2): + for device in ("cuda:0", "cpu"): + for expected_collision_type in "partially_elastic", "inelastic": + with self.subTest( + expected_collision_type=expected_collision_type, num_cubes=num_cubes, device=device + ): + with build_simulation_context( + device=device, add_ground_plane=False, auto_add_lighting=True + ) as sim: + cube_object, _ = generate_cubes_scene(num_cubes=num_cubes, height=1.0, device=device) + + # Set static friction to be non-zero + if expected_collision_type == "inelastic": + restitution_coefficient = 0.0 + elif expected_collision_type == "partially_elastic": + restitution_coefficient = 0.5 + + # Create ground plane such that has a restitution of 1.0 (perfectly elastic collision) + cfg = sim_utils.GroundPlaneCfg( + physics_material=materials.RigidBodyMaterialCfg( + restitution=restitution_coefficient, + ) + ) + cfg.func("/World/GroundPlane", cfg) + + indices = torch.tensor(range(num_cubes), dtype=torch.int) + + # Play sim + sim.reset() + + root_state = torch.zeros(num_cubes, 13, device=sim.device) + root_state[:, 3] = 1.0 # To make orientation a quaternion + for i in range(num_cubes): + root_state[i, 1] = 1.0 * i + root_state[:, 2] = 1.0 # Set an initial drop height + root_state[:, 9] = -1.0 # Set an initial downward velocity + + cube_object.write_root_state_to_sim(root_state=root_state) + + static_friction = torch.zeros(num_cubes, 1) + dynamic_friction = torch.zeros(num_cubes, 1) + restitution = torch.Tensor([[restitution_coefficient]] * num_cubes) + + cube_object_materials = torch.cat([static_friction, dynamic_friction, restitution], dim=-1) + + # Add restitution to cube + cube_object.root_physx_view.set_material_properties(cube_object_materials, indices) + + curr_z_velocity = cube_object.data.root_lin_vel_w[:, 2].clone() + + for _ in range(100): + sim.step() + + # update object + cube_object.update(sim.cfg.dt) + curr_z_velocity = cube_object.data.root_lin_vel_w[:, 2].clone() + + if expected_collision_type == "inelastic": + # assert that the block has not bounced by checking that the z velocity is less than or equal to 0 + self.assertTrue((curr_z_velocity <= 0.0).all()) + + if torch.all(curr_z_velocity <= 0.0): + # Still in the air + prev_z_velocity = curr_z_velocity + else: + # collision has happened, exit the for loop + break + + if expected_collision_type == "partially_elastic": + # Assert that the block has lost some energy by checking that the z velocity is less + self.assertTrue(torch.all(torch.le(abs(curr_z_velocity), abs(prev_z_velocity)))) + self.assertTrue((curr_z_velocity > 0.0).all()) def test_rigid_body_set_mass(self): """Test getting and setting mass of rigid object.""" diff --git a/tools/per_test_timeouts.py b/tools/per_test_timeouts.py index e98595372f..4310c632c7 100644 --- a/tools/per_test_timeouts.py +++ b/tools/per_test_timeouts.py @@ -9,6 +9,7 @@ """ PER_TEST_TIMEOUTS = { "test_articulation.py": 200, + "test_deformable_object.py": 200, "test_environments.py": 1200, # This test runs through all the environments for 100 steps each "test_environment_determinism.py": 200, # This test runs through many the environments for 100 steps each "test_env_rendering_logic.py": 300, From 952f648415682fe4d7fb22d3a24ce752184e5f38 Mon Sep 17 00:00:00 2001 From: Michael Gussert Date: Thu, 31 Oct 2024 09:28:58 -0700 Subject: [PATCH 047/111] Fixes typos in comments and docs (#1216) ## Checklist - [X] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [X] I have made corresponding changes to the documentation - [X] My changes generate no new warnings - [X] I have added tests that prove my fix is effective or that my feature works - [X] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [X] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --- docs/source/migration/migrating_from_isaacgymenvs.rst | 4 ++-- docs/source/migration/migrating_from_omniisaacgymenvs.rst | 4 ++-- .../isaac/lab_tasks/direct/cartpole/cartpole_camera_env.py | 2 +- .../omni/isaac/lab_tasks/direct/cartpole/cartpole_env.py | 2 +- .../direct/inhand_manipulation/inhand_manipulation_env.py | 2 +- .../omni/isaac/lab_tasks/direct/locomotion/locomotion_env.py | 2 +- .../lab_tasks/direct/shadow_hand/shadow_hand_vision_env.py | 2 +- .../standalone/tutorials/01_assets/run_deformable_object.py | 2 +- 8 files changed, 10 insertions(+), 10 deletions(-) diff --git a/docs/source/migration/migrating_from_isaacgymenvs.rst b/docs/source/migration/migrating_from_isaacgymenvs.rst index 2073854d32..2632321917 100644 --- a/docs/source/migration/migrating_from_isaacgymenvs.rst +++ b/docs/source/migration/migrating_from_isaacgymenvs.rst @@ -196,7 +196,7 @@ adding any other optional objects into the scene, such as lights. | self.sim = super().create_sim(self.device_id, self.graphics_device_id, | # clone, filter, and replicate | | self.physics_engine, self.sim_params) | self.scene.clone_environments(copy_from_source=False) | | self._create_ground_plane() | self.scene.filter_collisions(global_prim_paths=[]) | -| self._create_envs(self.num_envs, self.cfg["env"]['envSpacing'], | # add articultion to scene | +| self._create_envs(self.num_envs, self.cfg["env"]['envSpacing'], | # add articulation to scene | | int(np.sqrt(self.num_envs))) | self.scene.articulations["cartpole"] = self.cartpole | | | # add lights | | | light_cfg = sim_utils.DomeLightCfg(intensity=2000.0) | @@ -660,7 +660,7 @@ the need to set simulation parameters for actors in the task implementation. | self._create_ground_plane() | copy_from_source=False) | | self._create_envs(self.num_envs, | self.scene.filter_collisions( | | self.cfg["env"]['envSpacing'], | global_prim_paths=[]) | -| int(np.sqrt(self.num_envs))) | # add articultion to scene | +| int(np.sqrt(self.num_envs))) | # add articulation to scene | | | self.scene.articulations["cartpole"] = self.cartpole | | def _create_ground_plane(self): | # add lights | | plane_params = gymapi.PlaneParams() | light_cfg = sim_utils.DomeLightCfg( | diff --git a/docs/source/migration/migrating_from_omniisaacgymenvs.rst b/docs/source/migration/migrating_from_omniisaacgymenvs.rst index cbda1e8d45..7945ccb0b1 100644 --- a/docs/source/migration/migrating_from_omniisaacgymenvs.rst +++ b/docs/source/migration/migrating_from_omniisaacgymenvs.rst @@ -219,7 +219,7 @@ will automatically be created for the actor. This avoids the need to separately | self._cartpoles = ArticulationView( | # clone, filter, and replicate | | prim_paths_expr="/World/envs/.*/Cartpole", | self.scene.clone_environments(copy_from_source=False) | | name="cartpole_view", reset_xform_properties=False | self.scene.filter_collisions(global_prim_paths=[]) | -| ) | # add articultion to scene | +| ) | # add articulation to scene | | scene.add(self._cartpoles) | self.scene.articulations["cartpole"] = self.cartpole | | | # add lights | | | light_cfg = sim_utils.DomeLightCfg(intensity=2000.0) | @@ -638,7 +638,7 @@ Adding actors to the scene has been replaced by ``self.scene.articulations["cart | reset_xform_properties=False | copy_from_source=False) | | ) | self.scene.filter_collisions( | | scene.add(self._cartpoles) | global_prim_paths=[]) | -| return | # add articultion to scene | +| return | # add articulation to scene | | | self.scene.articulations["cartpole"] = self.cartpole | | def get_cartpole(self): | | | cartpole = Cartpole( | # add lights | diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/cartpole/cartpole_camera_env.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/cartpole/cartpole_camera_env.py index dc7db07030..e5881db086 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/cartpole/cartpole_camera_env.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/cartpole/cartpole_camera_env.py @@ -125,7 +125,7 @@ def _setup_scene(self): self.scene.clone_environments(copy_from_source=False) self.scene.filter_collisions(global_prim_paths=[]) - # add articultion and sensors to scene + # add articulation and sensors to scene self.scene.articulations["cartpole"] = self._cartpole self.scene.sensors["tiled_camera"] = self._tiled_camera # add lights diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/cartpole/cartpole_env.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/cartpole/cartpole_env.py index 534fb26443..1525941672 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/cartpole/cartpole_env.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/cartpole/cartpole_env.py @@ -74,7 +74,7 @@ def _setup_scene(self): # clone, filter, and replicate self.scene.clone_environments(copy_from_source=False) self.scene.filter_collisions(global_prim_paths=[]) - # add articultion to scene + # add articulation to scene self.scene.articulations["cartpole"] = self.cartpole # add lights light_cfg = sim_utils.DomeLightCfg(intensity=2000.0, color=(0.75, 0.75, 0.75)) diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/inhand_manipulation/inhand_manipulation_env.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/inhand_manipulation/inhand_manipulation_env.py index 52f4dc6e3c..7ab34f4763 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/inhand_manipulation/inhand_manipulation_env.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/inhand_manipulation/inhand_manipulation_env.py @@ -84,7 +84,7 @@ def _setup_scene(self): spawn_ground_plane(prim_path="/World/ground", cfg=GroundPlaneCfg()) # clone and replicate (no need to filter for this environment) self.scene.clone_environments(copy_from_source=False) - # add articultion to scene - we must register to scene to randomize with EventManager + # add articulation to scene - we must register to scene to randomize with EventManager self.scene.articulations["robot"] = self.hand self.scene.rigid_objects["object"] = self.object # add lights diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/locomotion/locomotion_env.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/locomotion/locomotion_env.py index c5c41a3c48..ffa572ac41 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/locomotion/locomotion_env.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/locomotion/locomotion_env.py @@ -54,7 +54,7 @@ def _setup_scene(self): # clone, filter, and replicate self.scene.clone_environments(copy_from_source=False) self.scene.filter_collisions(global_prim_paths=[self.cfg.terrain.prim_path]) - # add articultion to scene + # add articulation to scene self.scene.articulations["robot"] = self.robot # add lights light_cfg = sim_utils.DomeLightCfg(intensity=2000.0, color=(0.75, 0.75, 0.75)) diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/shadow_hand/shadow_hand_vision_env.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/shadow_hand/shadow_hand_vision_env.py index 492074d8a9..8677c16eba 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/shadow_hand/shadow_hand_vision_env.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/shadow_hand/shadow_hand_vision_env.py @@ -88,7 +88,7 @@ def _setup_scene(self): sem.GetSemanticDataAttr().Set("cube") # clone and replicate (no need to filter for this environment) self.scene.clone_environments(copy_from_source=False) - # add articultion to scene - we must register to scene to randomize with EventManager + # add articulation to scene - we must register to scene to randomize with EventManager self.scene.articulations["robot"] = self.hand self.scene.rigid_objects["object"] = self.object self.scene.sensors["tiled_camera"] = self._tiled_camera diff --git a/source/standalone/tutorials/01_assets/run_deformable_object.py b/source/standalone/tutorials/01_assets/run_deformable_object.py index eccbfab06e..8a6177d1d4 100644 --- a/source/standalone/tutorials/01_assets/run_deformable_object.py +++ b/source/standalone/tutorials/01_assets/run_deformable_object.py @@ -109,7 +109,7 @@ def run_simulator(sim: sim_utils.SimulationContext, entities: dict[str, Deformab # write nodal state to simulation cube_object.write_nodal_state_to_sim(nodal_state) - # write kinematic target to nodal state and free all vertices + # Write the nodal state to the kinematic target and free all vertices nodal_kinematic_target[..., :3] = nodal_state[..., :3] nodal_kinematic_target[..., 3] = 1.0 cube_object.write_nodal_kinematic_target_to_sim(nodal_kinematic_target) From c0d01d7edcb058d5f02e8bd8d3dffeead71cebd7 Mon Sep 17 00:00:00 2001 From: robotsfan Date: Fri, 1 Nov 2024 01:41:21 +0800 Subject: [PATCH 048/111] Ensures mesh name is compatible with USD convention in mesh converter (#1302) # Description Fixes #1287 **Issue details**: When using the convert_mesh.py script to convert .obj to .usd, if the obj file in this scene starts with a number(0c334eaabb844eaaad049cbbb2e0a4f2.obj), while the USD API prohibits names that start with a number [Link](https://openusd.org/release/api/group__group__tf___string.html#gaa129b294af3f68d01477d430b70d40c8). This issue is described in more detail here: [Link](https://forums.developer.nvidia.com/t/cant-create-prims-if-name-starts-with-number/249617). Also deleted useless debugging output code. ## Type of change - Bug fix (non-breaking change which fixes an issue) ## Checklist - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [ ] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [x] I have added tests that prove my fix is effective or that my feature works - [ ] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [x] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --- .../omni/isaac/lab/sim/converters/mesh_converter.py | 12 +++++++++++- source/standalone/tools/convert_mesh.py | 4 ---- 2 files changed, 11 insertions(+), 5 deletions(-) diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/converters/mesh_converter.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/converters/mesh_converter.py index 8a42138644..3ed91a1256 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/converters/mesh_converter.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/converters/mesh_converter.py @@ -10,7 +10,7 @@ import omni.kit.commands import omni.usd from omni.isaac.core.utils.extensions import enable_extension -from pxr import Usd, UsdGeom, UsdPhysics, UsdUtils +from pxr import Tf, Usd, UsdGeom, UsdPhysics, UsdUtils from omni.isaac.lab.sim.converters.asset_converter_base import AssetConverterBase from omni.isaac.lab.sim.converters.mesh_converter_cfg import MeshConverterCfg @@ -81,6 +81,16 @@ def _convert_asset(self, cfg: MeshConverterCfg): mesh_file_basename, mesh_file_format = os.path.basename(cfg.asset_path).split(".") mesh_file_format = mesh_file_format.lower() + # Check if mesh_file_basename is a valid USD identifier + if not Tf.IsValidIdentifier(mesh_file_basename): + # Correct the name to a valid identifier and update the basename + mesh_file_basename_original = mesh_file_basename + mesh_file_basename = Tf.MakeValidIdentifier(mesh_file_basename) + omni.log.warn( + f"Input file name '{mesh_file_basename_original}' is an invalid identifier for the mesh prim path." + f" Renaming it to '{mesh_file_basename}' for the conversion." + ) + # Convert USD asyncio.get_event_loop().run_until_complete( self._convert_mesh_to_usd( diff --git a/source/standalone/tools/convert_mesh.py b/source/standalone/tools/convert_mesh.py index 5cebf53d7f..5a88061067 100644 --- a/source/standalone/tools/convert_mesh.py +++ b/source/standalone/tools/convert_mesh.py @@ -106,10 +106,6 @@ def main(): if not os.path.isabs(dest_path): dest_path = os.path.abspath(dest_path) - print(dest_path) - print(os.path.dirname(dest_path)) - print(os.path.basename(dest_path)) - # Mass properties if args_cli.mass is not None: mass_props = schemas_cfg.MassPropertiesCfg(mass=args_cli.mass) From c37c50e17d30c8b0633eeaf9ff0b9d7389e04616 Mon Sep 17 00:00:00 2001 From: Yujian Zhang <272181284@qq.com> Date: Fri, 1 Nov 2024 21:07:23 +0800 Subject: [PATCH 049/111] Adds sanity check for the term type inside the command manager (#1315) # Description - The purpose of this change is to enhance the robustness of the code by adding a sanity check to ensure that the command term is of a valid type before it is processed (Just like ActionTerm). This validation step is crucial for preventing unexpected errors and maintaining system stability, especially when dealing with dynamically configured command terms that may vary based on external inputs or configurations. By validating the type of the command term, we can provide early feedback to developers and users, helping to catch misconfigurations or type mismatches during the initial stages. This change aims to improve the overall reliability and maintainability of the codebase. - It also fixes iteration over group_cfg_items inside the observation manager. ## Type of change - Bug fix (non-breaking change which fixes an issue) ## Checklist - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [x] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [ ] I have added tests that prove my fix is effective or that my feature works - [x] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [x] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --------- Signed-off-by: Mayank Mittal <12863862+Mayankm96@users.noreply.github.com> Co-authored-by: Mayank Mittal <12863862+Mayankm96@users.noreply.github.com> --- CONTRIBUTORS.md | 1 + source/extensions/omni.isaac.lab/config/extension.toml | 3 +-- source/extensions/omni.isaac.lab/docs/CHANGELOG.rst | 9 +++++++++ .../omni/isaac/lab/managers/command_manager.py | 3 +++ .../omni/isaac/lab/managers/observation_manager.py | 2 +- 5 files changed, 15 insertions(+), 3 deletions(-) diff --git a/CONTRIBUTORS.md b/CONTRIBUTORS.md index e59d3de8d4..4b49086672 100644 --- a/CONTRIBUTORS.md +++ b/CONTRIBUTORS.md @@ -72,6 +72,7 @@ Guidelines for modifications: * Wei Yang * Xavier Nal * Yang Jin +* Yujian Zhang * Zhengyu Zhang * Ziqi Fan * Qian Wan diff --git a/source/extensions/omni.isaac.lab/config/extension.toml b/source/extensions/omni.isaac.lab/config/extension.toml index 4a6faf6114..a9cf0aebda 100644 --- a/source/extensions/omni.isaac.lab/config/extension.toml +++ b/source/extensions/omni.isaac.lab/config/extension.toml @@ -1,8 +1,7 @@ [package] # Note: Semantic Versioning is used: https://semver.org/ - -version = "0.27.7" +version = "0.27.8" # Description title = "Isaac Lab framework for Robot Learning" diff --git a/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst b/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst index ecc0471794..431ad8677f 100644 --- a/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst +++ b/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst @@ -1,6 +1,15 @@ Changelog --------- +0.27.8 (2024-11-01) +~~~~~~~~~~~~~~~~~~~ + +Fixed +^^^^^ + +* Added sanity check if the term is a valid type inside the command manager. +* Corrected the iteration over ``group_cfg_items`` inside the observation manager. + 0.27.7 (2024-10-28) ~~~~~~~~~~~~~~~~~~~ diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/command_manager.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/command_manager.py index 2b4451f7e4..50a717b6d4 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/command_manager.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/command_manager.py @@ -394,5 +394,8 @@ def _prepare_terms(self): ) # create the action term term = term_cfg.class_type(term_cfg, self._env) + # sanity check if term is valid type + if not isinstance(term, CommandTerm): + raise TypeError(f"Returned object for the term '{term_name}' is not of type CommandType.") # add class to dict self._terms[term_name] = term diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/observation_manager.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/observation_manager.py index 1e0391b3a0..b270b2d456 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/observation_manager.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/observation_manager.py @@ -317,7 +317,7 @@ def _prepare_terms(self): else: group_cfg_items = group_cfg.__dict__.items() # iterate over all the terms in each group - for term_name, term_cfg in group_cfg.__dict__.items(): + for term_name, term_cfg in group_cfg_items: # skip non-obs settings if term_name in ["enable_corruption", "concatenate_terms"]: continue From 05f5d1eb94bb3dd5b2310f2d2d994c4e6526a497 Mon Sep 17 00:00:00 2001 From: Mayank Mittal <12863862+Mayankm96@users.noreply.github.com> Date: Fri, 1 Nov 2024 14:10:01 +0100 Subject: [PATCH 050/111] Adds `ArticulationActions` type to the core framework (#1292) Earlier, we were depending on Isaac Sim's for the articulation action type. The type-hinting for the attributes in there used numpy and list. However, the Isaac Lab framework uses torch tensors everywhere so this led to pylance complaining about the types. The MR makes a drop in replacement with the correct types for our usecases. - New feature (non-breaking change which adds functionality) - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [x] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [ ] I have added tests that prove my fix is effective or that my feature works - [x] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [x] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --- docs/source/api/lab/omni.isaac.lab.utils.rst | 8 ++++ .../omni.isaac.lab/config/extension.toml | 2 +- .../omni.isaac.lab/docs/CHANGELOG.rst | 13 ++++++- .../omni/isaac/lab/actuators/actuator_base.py | 3 +- .../omni/isaac/lab/actuators/actuator_net.py | 3 +- .../omni/isaac/lab/actuators/actuator_pd.py | 20 ++++++++-- .../lab/assets/articulation/articulation.py | 2 +- .../omni/isaac/lab/utils/__init__.py | 1 + .../omni/isaac/lab/utils/types.py | 39 +++++++++++++++++++ 9 files changed, 81 insertions(+), 10 deletions(-) create mode 100644 source/extensions/omni.isaac.lab/omni/isaac/lab/utils/types.py diff --git a/docs/source/api/lab/omni.isaac.lab.utils.rst b/docs/source/api/lab/omni.isaac.lab.utils.rst index 2143ecfc28..c14ae19b6c 100644 --- a/docs/source/api/lab/omni.isaac.lab.utils.rst +++ b/docs/source/api/lab/omni.isaac.lab.utils.rst @@ -18,6 +18,7 @@ noise string timer + types warp .. Rubric:: Functions @@ -123,6 +124,13 @@ Timer operations :members: :show-inheritance: +Type operations +~~~~~~~~~~~~~~~ + +.. automodule:: omni.isaac.lab.utils.types + :members: + :show-inheritance: + Warp operations ~~~~~~~~~~~~~~~ diff --git a/source/extensions/omni.isaac.lab/config/extension.toml b/source/extensions/omni.isaac.lab/config/extension.toml index a9cf0aebda..0b5f4bdd5c 100644 --- a/source/extensions/omni.isaac.lab/config/extension.toml +++ b/source/extensions/omni.isaac.lab/config/extension.toml @@ -1,7 +1,7 @@ [package] # Note: Semantic Versioning is used: https://semver.org/ -version = "0.27.8" +version = "0.27.9" # Description title = "Isaac Lab framework for Robot Learning" diff --git a/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst b/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst index 431ad8677f..0627320876 100644 --- a/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst +++ b/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst @@ -1,6 +1,17 @@ Changelog --------- +0.27.9 (2024-11-01) +~~~~~~~~~~~~~~~~~~~ + +Added +^^^^^ + +* Added the :class:`omni.isaac.lab.utils.types.ArticulationActions` class to store the joint actions + for an articulation. Earlier, the class from Isaac Sim was being used. However, it used a different + type for the joint actions which was not compatible with the Isaac Lab framework. + + 0.27.8 (2024-11-01) ~~~~~~~~~~~~~~~~~~~ @@ -91,7 +102,7 @@ Added :attr:`omni.isaac.lab.envs.ManagerBasedRLEnvCfg.commands` as None. Before, this had to be done using the class :class:`omni.isaac.lab.command_generators.NullCommandGenerator`. * Moved the ``meshes`` attribute in the :class:`omni.isaac.lab.sensors.RayCaster` class from class variable to instance variable. - This prevents the meshes to overwrite each other. + This prevents the meshes to overwrite each other. 0.26.0 (2024-10-16) diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/actuators/actuator_base.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/actuators/actuator_base.py index 67926fce31..dc1d3788bd 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/actuators/actuator_base.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/actuators/actuator_base.py @@ -10,9 +10,8 @@ from collections.abc import Sequence from typing import TYPE_CHECKING -from omni.isaac.core.utils.types import ArticulationActions - import omni.isaac.lab.utils.string as string_utils +from omni.isaac.lab.utils.types import ArticulationActions if TYPE_CHECKING: from .actuator_cfg import ActuatorBaseCfg diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/actuators/actuator_net.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/actuators/actuator_net.py index 5cf034679d..c0d440533a 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/actuators/actuator_net.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/actuators/actuator_net.py @@ -18,9 +18,8 @@ from collections.abc import Sequence from typing import TYPE_CHECKING -from omni.isaac.core.utils.types import ArticulationActions - from omni.isaac.lab.utils.assets import read_file +from omni.isaac.lab.utils.types import ArticulationActions from .actuator_pd import DCMotor diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/actuators/actuator_pd.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/actuators/actuator_pd.py index 165567536f..563b29ba47 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/actuators/actuator_pd.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/actuators/actuator_pd.py @@ -9,9 +9,8 @@ from collections.abc import Sequence from typing import TYPE_CHECKING -from omni.isaac.core.utils.types import ArticulationActions - from omni.isaac.lab.utils import DelayBuffer, LinearInterpolation +from omni.isaac.lab.utils.types import ArticulationActions from .actuator_base import ActuatorBase @@ -63,7 +62,22 @@ def reset(self, *args, **kwargs): def compute( self, control_action: ArticulationActions, joint_pos: torch.Tensor, joint_vel: torch.Tensor ) -> ArticulationActions: - """Compute the aproximmate torques for the actuated joint (physX does not compute this explicitly).""" + """Process the actuator group actions and compute the articulation actions. + + In case of implicit actuator, the control action is directly returned as the computed action. + This function is a no-op and does not perform any computation on the input control action. + However, it computes the approximate torques for the actuated joint since PhysX does not compute + this quantity explicitly. + + Args: + control_action: The joint action instance comprising of the desired joint positions, joint velocities + and (feed-forward) joint efforts. + joint_pos: The current joint positions of the joints in the group. Shape is (num_envs, num_joints). + joint_vel: The current joint velocities of the joints in the group. Shape is (num_envs, num_joints). + + Returns: + The computed desired joint positions, joint velocities and joint efforts. + """ # store approximate torques for reward computation error_pos = control_action.joint_positions - joint_pos error_vel = control_action.joint_velocities - joint_vel diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/articulation/articulation.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/articulation/articulation.py index a604254caa..7011cafbc1 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/articulation/articulation.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/articulation/articulation.py @@ -16,13 +16,13 @@ import omni.isaac.core.utils.stage as stage_utils import omni.log import omni.physics.tensors.impl.api as physx -from omni.isaac.core.utils.types import ArticulationActions from pxr import PhysxSchema, UsdPhysics import omni.isaac.lab.sim as sim_utils import omni.isaac.lab.utils.math as math_utils import omni.isaac.lab.utils.string as string_utils from omni.isaac.lab.actuators import ActuatorBase, ActuatorBaseCfg, ImplicitActuator +from omni.isaac.lab.utils.types import ArticulationActions from ..asset_base import AssetBase from .articulation_data import ArticulationData diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/utils/__init__.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/utils/__init__.py index 23fb50d4c2..1cfa3507fd 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/utils/__init__.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/utils/__init__.py @@ -13,3 +13,4 @@ from .modifiers import * from .string import * from .timer import Timer +from .types import * diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/utils/types.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/utils/types.py new file mode 100644 index 0000000000..3f2066a192 --- /dev/null +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/utils/types.py @@ -0,0 +1,39 @@ +# Copyright (c) 2022-2024, The Isaac Lab Project Developers. +# All rights reserved. +# +# SPDX-License-Identifier: BSD-3-Clause + +"""Sub-module for different data types.""" + +from __future__ import annotations + +import torch +from collections.abc import Sequence +from dataclasses import dataclass + + +@dataclass +class ArticulationActions: + """Data container to store articulation's joints actions. + + This class is used to store the actions of the joints of an articulation. + It is used to store the joint positions, velocities, efforts, and indices. + + If the actions are not provided, the values are set to None. + """ + + joint_positions: torch.Tensor | None = None + """The joint positions of the articulation. Defaults to None.""" + + joint_velocities: torch.Tensor | None = None + """The joint velocities of the articulation. Defaults to None.""" + + joint_efforts: torch.Tensor | None = None + """The joint efforts of the articulation. Defaults to None.""" + + joint_indices: torch.Tensor | Sequence[int] | slice | None = None + """The joint indices of the articulation. Defaults to None. + + If the joint indices are a slice, this indicates that the indices are continuous and correspond + to all the joints of the articulation. We use a slice to make the indexing more efficient. + """ From b3b45484a18c4955e1f18b80cd3c3b799486c527 Mon Sep 17 00:00:00 2001 From: Toni-SM Date: Fri, 1 Nov 2024 09:18:34 -0400 Subject: [PATCH 051/111] Caches PhysX view's joint paths when processing fixed articulation tendons (#1347) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit # Description Cache PhysX view's DOF paths before looping when processing fixed articulation tendons to improve loading time. For the Shadow Hand task, calling `self.root_physx_view.dof_paths` when iterating over all joints to find tendons attached (in `Articulation._process_fixed_tendons` method) is an "expensive" operation. Timing can be reduced from 2.2 seconds to 300 milliseconds (13th Gen Intel® Core™ i9-13950HX × 32, RTX 5000) by calling `self.root_physx_view.dof_paths` once ## Screenshots Without any change ![Screenshot from 2024-10-28 13-30-07](https://github.com/user-attachments/assets/0bd61f3d-3013-49fb-8540-c08236b974cf) After cache PhysX view's DOF paths before looping (`self.root_physx_view.dof_paths` called only once) ![Screenshot from 2024-10-28 13-26-02](https://github.com/user-attachments/assets/6c2af86e-bd21-4b65-9c13-9610e6648e8d) ## Checklist - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [ ] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [ ] I have added tests that prove my fix is effective or that my feature works - [x] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [x] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --- source/extensions/omni.isaac.lab/config/extension.toml | 2 +- source/extensions/omni.isaac.lab/docs/CHANGELOG.rst | 10 ++++++++++ .../omni/isaac/lab/assets/articulation/articulation.py | 3 ++- 3 files changed, 13 insertions(+), 2 deletions(-) diff --git a/source/extensions/omni.isaac.lab/config/extension.toml b/source/extensions/omni.isaac.lab/config/extension.toml index 0b5f4bdd5c..28a5564049 100644 --- a/source/extensions/omni.isaac.lab/config/extension.toml +++ b/source/extensions/omni.isaac.lab/config/extension.toml @@ -1,7 +1,7 @@ [package] # Note: Semantic Versioning is used: https://semver.org/ -version = "0.27.9" +version = "0.27.10" # Description title = "Isaac Lab framework for Robot Learning" diff --git a/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst b/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst index 0627320876..991b6268d7 100644 --- a/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst +++ b/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst @@ -1,6 +1,16 @@ Changelog --------- +0.27.10 (2024-11-01) +~~~~~~~~~~~~~~~~~~~~ + +Changed +^^^^^^^ + +* Cached the PhysX view's joint paths before looping over them when processing fixed joint tendons + inside the :class:`Articulation` class. This helps improve the processing time for the tendons. + + 0.27.9 (2024-11-01) ~~~~~~~~~~~~~~~~~~~ diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/articulation/articulation.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/articulation/articulation.py index 7011cafbc1..1dfc348bc2 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/articulation/articulation.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/articulation/articulation.py @@ -1190,10 +1190,11 @@ def _process_fixed_tendons(self): # parse fixed tendons properties if they exist if self.num_fixed_tendons > 0: stage = stage_utils.get_current_stage() + joint_paths = self.root_physx_view.dof_paths[0] # iterate over all joints to find tendons attached to them for j in range(self.num_joints): - usd_joint_path = self.root_physx_view.dof_paths[0][j] + usd_joint_path = joint_paths[j] # check whether joint has tendons - tendon name follows the joint name it is attached to joint = UsdPhysics.Joint.Get(stage, usd_joint_path) if joint.GetPrim().HasAPI(PhysxSchema.PhysxTendonAxisRootAPI): From 281f9b0b2b59e411d3cb5075fa0394f5d32dc40a Mon Sep 17 00:00:00 2001 From: MoreTorque <104254025+MoreTore@users.noreply.github.com> Date: Fri, 1 Nov 2024 10:38:55 -0500 Subject: [PATCH 052/111] Adds event term to randomize gains of explicit actuators (#1005) # Description resolves: https://github.com/isaac-sim/IsaacLab/issues/1000 resolves: https://github.com/isaac-sim/IsaacLab/issues/1011 depends: https://github.com/isaac-sim/IsaacLab/issues/1006 ## Type of change - New feature (non-breaking change which adds functionality) - This change may require a documentation update ## Checklist - [x] have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [x] My changes generate no new warnings - [x] I have added my name to the `CONTRIBUTORS.md` or my name already exists there - [x] I have made corresponding changes to the documentation - [ ] I have added tests that prove my fix is effective or that my feature works - [ ] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file --- CONTRIBUTORS.md | 4 +- .../omni/isaac/lab/actuators/actuator_base.py | 10 ++- .../lab/assets/articulation/articulation.py | 33 +++---- .../omni/isaac/lab/envs/mdp/events.py | 88 ++++++++++--------- 4 files changed, 70 insertions(+), 65 deletions(-) diff --git a/CONTRIBUTORS.md b/CONTRIBUTORS.md index 4b49086672..c9075bc49b 100644 --- a/CONTRIBUTORS.md +++ b/CONTRIBUTORS.md @@ -63,10 +63,12 @@ Guidelines for modifications: * Muhong Guo * Nuralem Abizov * Özhan Özen +* Qian Wan * Qinxi Yu * René Zurbrügg * Ritvik Singh * Rosario Scalise +* Ryley McCarroll * Shafeef Omar * Vladimir Fokow * Wei Yang @@ -75,8 +77,6 @@ Guidelines for modifications: * Yujian Zhang * Zhengyu Zhang * Ziqi Fan -* Qian Wan -* Wei Yang ## Acknowledgements diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/actuators/actuator_base.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/actuators/actuator_base.py index dc1d3788bd..fba943bc15 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/actuators/actuator_base.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/actuators/actuator_base.py @@ -206,6 +206,7 @@ def _parse_joint_parameter( TypeError: If the parameter value is not of the expected type. TypeError: If the default value is not of the expected type. ValueError: If the parameter value is None and no default value is provided. + ValueError: If the default value tensor is the wrong shape. """ # create parameter buffer param = torch.zeros(self._num_envs, self.num_joints, device=self._device) @@ -230,7 +231,14 @@ def _parse_joint_parameter( param[:] = float(default_value) elif isinstance(default_value, torch.Tensor): # if tensor, then use the same tensor for all joints - param[:] = default_value.float() + if default_value.shape == (self._num_envs, self.num_joints): + param = default_value.float() + else: + raise ValueError( + "Invalid default value tensor shape.\n" + f"Got: {default_value.shape}\n" + f"Expected: {(self._num_envs, self.num_joints)}" + ) else: raise TypeError( f"Invalid type for default value: {type(default_value)} for " diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/articulation/articulation.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/articulation/articulation.py index 1dfc348bc2..d744f3387f 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/articulation/articulation.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/articulation/articulation.py @@ -1105,12 +1105,10 @@ def _process_actuators_cfg(self): self._has_implicit_actuators = False # cache the values coming from the usd - usd_stiffness = self.root_physx_view.get_dof_stiffnesses().clone() - usd_damping = self.root_physx_view.get_dof_dampings().clone() - usd_armature = self.root_physx_view.get_dof_armatures().clone() - usd_friction = self.root_physx_view.get_dof_friction_coefficients().clone() - usd_effort_limit = self.root_physx_view.get_dof_max_forces().clone() - usd_velocity_limit = self.root_physx_view.get_dof_max_velocities().clone() + self._data.default_joint_stiffness = self.root_physx_view.get_dof_stiffnesses().to(self.device).clone() + self._data.default_joint_damping = self.root_physx_view.get_dof_dampings().to(self.device).clone() + self._data.default_joint_armature = self.root_physx_view.get_dof_armatures().to(self.device).clone() + self._data.default_joint_friction = self.root_physx_view.get_dof_friction_coefficients().to(self.device).clone() # iterate over all actuator configurations for actuator_name, actuator_cfg in self.cfg.actuators.items(): @@ -1134,12 +1132,12 @@ def _process_actuators_cfg(self): ), num_envs=self.num_instances, device=self.device, - stiffness=usd_stiffness[:, joint_ids], - damping=usd_damping[:, joint_ids], - armature=usd_armature[:, joint_ids], - friction=usd_friction[:, joint_ids], - effort_limit=usd_effort_limit[:, joint_ids], - velocity_limit=usd_velocity_limit[:, joint_ids], + stiffness=self._data.default_joint_stiffness[:, joint_ids], + damping=self._data.default_joint_damping[:, joint_ids], + armature=self._data.default_joint_armature[:, joint_ids], + friction=self._data.default_joint_friction[:, joint_ids], + effort_limit=self.root_physx_view.get_dof_max_forces().to(self.device).clone()[:, joint_ids], + velocity_limit=self.root_physx_view.get_dof_max_velocities().to(self.device).clone()[:, joint_ids], ) # log information on actuator groups omni.log.info( @@ -1165,14 +1163,9 @@ def _process_actuators_cfg(self): self.write_joint_effort_limit_to_sim(1.0e9, joint_ids=actuator.joint_indices) self.write_joint_armature_to_sim(actuator.armature, joint_ids=actuator.joint_indices) self.write_joint_friction_to_sim(actuator.friction, joint_ids=actuator.joint_indices) - - # set the default joint parameters based on the changes from the actuators - self._data.default_joint_stiffness = self.root_physx_view.get_dof_stiffnesses().to(device=self.device).clone() - self._data.default_joint_damping = self.root_physx_view.get_dof_dampings().to(device=self.device).clone() - self._data.default_joint_armature = self.root_physx_view.get_dof_armatures().to(device=self.device).clone() - self._data.default_joint_friction = ( - self.root_physx_view.get_dof_friction_coefficients().to(device=self.device).clone() - ) + # Store the actual default stiffness and damping values for explicit actuators (not written the sim) + self._data.default_joint_stiffness[:, actuator.joint_indices] = actuator.stiffness + self._data.default_joint_damping[:, actuator.joint_indices] = actuator.damping # perform some sanity checks to ensure actuators are prepared correctly total_act_joints = sum(actuator.num_joints for actuator in self.actuators.values()) diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/events.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/events.py index 3eaeb650f9..bd7532a14a 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/events.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/events.py @@ -300,54 +300,57 @@ def randomize_actuator_gains( .. tip:: For implicit actuators, this function uses CPU tensors to assign the actuator gains into the simulation. In such cases, it is recommended to use this function only during the initialization of the environment. - - Raises: - NotImplementedError: If the joint indices are in explicit motor mode. This operation is currently - not supported for explicit actuator models. """ - # extract the used quantities (to enable type-hinting) + # Extract the used quantities (to enable type-hinting) asset: Articulation = env.scene[asset_cfg.name] - # resolve environment ids + # Resolve environment ids if env_ids is None: env_ids = torch.arange(env.scene.num_envs, device=asset.device) - # resolve joint indices - if asset_cfg.joint_ids == slice(None): - joint_ids_list = range(asset.num_joints) - joint_ids = slice(None) # for optimization purposes - else: - joint_ids_list = asset_cfg.joint_ids - joint_ids = torch.tensor(asset_cfg.joint_ids, dtype=torch.int, device=asset.device) - - # check if none of the joint indices are in explicit motor mode - for joint_index in joint_ids_list: - for act_name, actuator in asset.actuators.items(): - # if joint indices are a slice (i.e., all joints are captured) or the joint index is in the actuator - if actuator.joint_indices == slice(None) or joint_index in actuator.joint_indices: - if not isinstance(actuator, ImplicitActuator): - raise NotImplementedError( - "Event term 'randomize_actuator_stiffness_and_damping' is performed on asset" - f" '{asset_cfg.name}' on the joint '{asset.joint_names[joint_index]}' ('{joint_index}') which" - f" uses an explicit actuator model '{act_name}<{actuator.__class__.__name__}>'. This operation" - " is currently not supported for explicit actuator models." - ) + def randomize(data: torch.Tensor, params: tuple[float, float]) -> torch.Tensor: + return _randomize_prop_by_op( + data, params, dim_0_ids=None, dim_1_ids=actuator_indices, operation=operation, distribution=distribution + ) - # sample joint properties from the given ranges and set into the physics simulation - # -- stiffness - if stiffness_distribution_params is not None: - stiffness = asset.data.default_joint_stiffness.to(asset.device).clone() - stiffness = _randomize_prop_by_op( - stiffness, stiffness_distribution_params, env_ids, joint_ids, operation=operation, distribution=distribution - )[env_ids][:, joint_ids] - asset.write_joint_stiffness_to_sim(stiffness, joint_ids=joint_ids, env_ids=env_ids) - # -- damping - if damping_distribution_params is not None: - damping = asset.data.default_joint_damping.to(asset.device).clone() - damping = _randomize_prop_by_op( - damping, damping_distribution_params, env_ids, joint_ids, operation=operation, distribution=distribution - )[env_ids][:, joint_ids] - asset.write_joint_damping_to_sim(damping, joint_ids=joint_ids, env_ids=env_ids) + # Loop through actuators and randomize gains + for actuator in asset.actuators.values(): + if isinstance(asset_cfg.joint_ids, slice): + # we take all the joints of the actuator + actuator_indices = slice(None) + if isinstance(actuator.joint_indices, slice): + global_indices = slice(None) + else: + global_indices = torch.tensor(actuator.joint_indices, device=asset.device) + elif isinstance(actuator.joint_indices, slice): + # we take the joints defined in the asset config + global_indices = actuator_indices = torch.tensor(asset_cfg.joint_ids, device=asset.device) + else: + # we take the intersection of the actuator joints and the asset config joints + actuator_joint_indices = torch.tensor(actuator.joint_indices, device=asset.device) + asset_joint_ids = torch.tensor(asset_cfg.joint_ids, device=asset.device) + # the indices of the joints in the actuator that have to be randomized + actuator_indices = torch.nonzero(torch.isin(actuator_joint_indices, asset_joint_ids)).view(-1) + if len(actuator_indices) == 0: + continue + # maps actuator indices that have to be randomized to global joint indices + global_indices = actuator_joint_indices[actuator_indices] + # Randomize stiffness + if stiffness_distribution_params is not None: + stiffness = actuator.stiffness[env_ids].clone() + stiffness[:, actuator_indices] = asset.data.default_joint_stiffness[env_ids][:, global_indices].clone() + randomize(stiffness, stiffness_distribution_params) + actuator.stiffness[env_ids] = stiffness + if isinstance(actuator, ImplicitActuator): + asset.write_joint_stiffness_to_sim(stiffness, joint_ids=actuator.joint_indices, env_ids=env_ids) + # Randomize damping + if damping_distribution_params is not None: + damping = actuator.damping[env_ids].clone() + damping[:, actuator_indices] = asset.data.default_joint_damping[env_ids][:, global_indices].clone() + randomize(damping, damping_distribution_params) + actuator.damping[env_ids] = damping + if isinstance(actuator, ImplicitActuator): + asset.write_joint_damping_to_sim(damping, joint_ids=actuator.joint_indices, env_ids=env_ids) def randomize_joint_parameters( @@ -967,7 +970,8 @@ def _randomize_prop_by_op( dim_0_ids = slice(None) else: n_dim_0 = len(dim_0_ids) - dim_0_ids = dim_0_ids[:, None] + if not isinstance(dim_1_ids, slice): + dim_0_ids = dim_0_ids[:, None] # -- dim 1 if isinstance(dim_1_ids, slice): n_dim_1 = data.shape[1] From f7350c72b3e7ac310eda00cbc325b8f80f31e66a Mon Sep 17 00:00:00 2001 From: Pascal Roth <57946385+pascal-roth@users.noreply.github.com> Date: Fri, 1 Nov 2024 18:29:55 +0100 Subject: [PATCH 053/111] Expands observation term scaling to support list of floats (#1269) # Description Added support to define tuple of floats to scale observation terms by expanding the `ObservationManagerCfg.scale` attribute. ## Type of change - New feature (non-breaking change which adds functionality) ## Checklist - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [ ] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [ ] I have added tests that prove my fix is effective or that my feature works - [x] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [x] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --- .../omni.isaac.lab/config/extension.toml | 2 +- .../omni.isaac.lab/docs/CHANGELOG.rst | 10 ++++++++++ .../isaac/lab/managers/manager_term_cfg.py | 8 ++++++-- .../isaac/lab/managers/observation_manager.py | 19 ++++++++++++++++++- .../test/managers/test_observation_manager.py | 13 ++++++++++--- 5 files changed, 45 insertions(+), 7 deletions(-) diff --git a/source/extensions/omni.isaac.lab/config/extension.toml b/source/extensions/omni.isaac.lab/config/extension.toml index 28a5564049..6f43e77bf2 100644 --- a/source/extensions/omni.isaac.lab/config/extension.toml +++ b/source/extensions/omni.isaac.lab/config/extension.toml @@ -1,7 +1,7 @@ [package] # Note: Semantic Versioning is used: https://semver.org/ -version = "0.27.10" +version = "0.27.11" # Description title = "Isaac Lab framework for Robot Learning" diff --git a/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst b/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst index 991b6268d7..b67d43e9ed 100644 --- a/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst +++ b/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst @@ -1,6 +1,16 @@ Changelog --------- +0.27.11 (2024-10-31) +~~~~~~~~~~~~~~~~~~~~ + +Added +^^^^^ + +* Added support to define tuple of floats to scale observation terms by expanding the + :attr:`omni.isaac.lab.managers.manager_term_cfg.ObservationManagerCfg.scale` attribute. + + 0.27.10 (2024-11-01) ~~~~~~~~~~~~~~~~~~~~ diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/manager_term_cfg.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/manager_term_cfg.py index 9a2250e48b..1a510159e2 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/manager_term_cfg.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/manager_term_cfg.py @@ -152,9 +152,13 @@ class ObservationTermCfg(ManagerTermBaseCfg): """The clipping range for the observation after adding noise. Defaults to None, in which case no clipping is applied.""" - scale: float | None = None + scale: tuple[float, ...] | float | None = None """The scale to apply to the observation after clipping. Defaults to None, - in which case no scaling is applied (same as setting scale to :obj:`1`).""" + in which case no scaling is applied (same as setting scale to :obj:`1`). + + We leverage PyTorch broadcasting to scale the observation tensor with the provided value. If a tuple is provided, + please make sure the length of the tuple matches the dimensions of the tensor outputted from the term. + """ @configclass diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/observation_manager.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/observation_manager.py index b270b2d456..6bc9b0374b 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/observation_manager.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/observation_manager.py @@ -259,7 +259,7 @@ def compute_group(self, group_name: str) -> torch.Tensor | dict[str, torch.Tenso obs = term_cfg.noise.func(obs, term_cfg.noise) if term_cfg.clip: obs = obs.clip_(min=term_cfg.clip[0], max=term_cfg.clip[1]) - if term_cfg.scale: + if term_cfg.scale is not None: obs = obs.mul_(term_cfg.scale) # add value to list group_obs[name] = obs @@ -343,6 +343,23 @@ def _prepare_terms(self): obs_dims = tuple(term_cfg.func(self._env, **term_cfg.params).shape) self._group_obs_term_dim[group_name].append(obs_dims[1:]) + # if scale is set, check if single float or tuple + if term_cfg.scale is not None: + if not isinstance(term_cfg.scale, (float, int, tuple)): + raise TypeError( + f"Scale for observation term '{term_name}' in group '{group_name}'" + f" is not of type float, int or tuple. Received: '{type(term_cfg.scale)}'." + ) + if isinstance(term_cfg.scale, tuple) and len(term_cfg.scale) != obs_dims[1]: + raise ValueError( + f"Scale for observation term '{term_name}' in group '{group_name}'" + f" does not match the dimensions of the observation. Expected: {obs_dims[1]}" + f" but received: {len(term_cfg.scale)}." + ) + + # cast the scale into torch tensor + term_cfg.scale = torch.tensor(term_cfg.scale, dtype=torch.float, device=self._env.device) + # prepare modifiers for each observation if term_cfg.modifiers is not None: # initialize list of modifiers for term diff --git a/source/extensions/omni.isaac.lab/test/managers/test_observation_manager.py b/source/extensions/omni.isaac.lab/test/managers/test_observation_manager.py index 9b73e2d44a..c624fb2bd1 100644 --- a/source/extensions/omni.isaac.lab/test/managers/test_observation_manager.py +++ b/source/extensions/omni.isaac.lab/test/managers/test_observation_manager.py @@ -244,6 +244,8 @@ class SampleImageGroupCfg(ObservationGroupCfg): def test_compute(self): """Test the observation computation.""" + pos_scale_tuple = (2.0, 3.0, 1.0) + @configclass class MyObservationManagerCfg: """Test config class for observation manager.""" @@ -254,14 +256,14 @@ class PolicyCfg(ObservationGroupCfg): term_1 = ObservationTermCfg(func=grilled_chicken, scale=10) term_2 = ObservationTermCfg(func=grilled_chicken_with_curry, scale=0.0, params={"hot": False}) - term_3 = ObservationTermCfg(func=pos_w_data, scale=2.0) + term_3 = ObservationTermCfg(func=pos_w_data, scale=pos_scale_tuple) term_4 = ObservationTermCfg(func=lin_vel_w_data, scale=1.5) @configclass class CriticCfg(ObservationGroupCfg): - term_1 = ObservationTermCfg(func=pos_w_data, scale=2.0) + term_1 = ObservationTermCfg(func=pos_w_data, scale=pos_scale_tuple) term_2 = ObservationTermCfg(func=lin_vel_w_data, scale=1.5) - term_3 = ObservationTermCfg(func=pos_w_data, scale=2.0) + term_3 = ObservationTermCfg(func=pos_w_data, scale=pos_scale_tuple) term_4 = ObservationTermCfg(func=lin_vel_w_data, scale=1.5) @configclass @@ -289,6 +291,11 @@ class ImageCfg(ObservationGroupCfg): self.assertEqual((self.env.num_envs, 11), obs_policy.shape) self.assertEqual((self.env.num_envs, 12), obs_critic.shape) self.assertEqual((self.env.num_envs, 128, 256, 4), obs_image.shape) + # check that the scales are applied correctly + torch.testing.assert_close( + self.env.data.pos_w * torch.tensor(pos_scale_tuple, device=self.env.device), obs_critic[:, :3] + ) + torch.testing.assert_close(self.env.data.lin_vel_w * 1.5, obs_critic[:, 3:6]) # make sure that the data are the same for same terms # -- within group torch.testing.assert_close(obs_critic[:, 0:3], obs_critic[:, 6:9]) From 799e0f98b13d27d21d4e7191db0a5e40f0890b7b Mon Sep 17 00:00:00 2001 From: Mayank Mittal <12863862+Mayankm96@users.noreply.github.com> Date: Mon, 4 Nov 2024 10:56:06 +0100 Subject: [PATCH 054/111] Fixes location of images for task workflows (#1349) This MR fixes the regression in #1337. The images were located in the wrong directory. Please be careful. P.S.: The images are very low in resolution, and they don't support the dark theme. It would be great to include this as part of this MR to avoid this issue. - Bug fix (non-breaking change which fixes an issue) - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [x] I have made corresponding changes to the documentation - [ ] My changes generate no new warnings - [ ] I have added tests that prove my fix is effective or that my feature works - [x] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [x] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --- CONTRIBUTORS.md | 5 ++-- .../task-workflows/direct-based-dark.svg | 3 ++ .../task-workflows/direct-based-light.svg | 3 ++ .../task-workflows/manager-based-dark.svg | 3 ++ .../task-workflows/manager-based-light.svg | 3 ++ .../Direct-basedTaskWorkflow.jpg | Bin 60552 -> 0 bytes .../Manager-basedTaskWorkflow.jpg | Bin 119227 -> 0 bytes .../overview/core-concepts/task_workflows.rst | 28 +++++++++++++----- 8 files changed, 35 insertions(+), 10 deletions(-) create mode 100644 docs/source/_static/task-workflows/direct-based-dark.svg create mode 100644 docs/source/_static/task-workflows/direct-based-light.svg create mode 100644 docs/source/_static/task-workflows/manager-based-dark.svg create mode 100644 docs/source/_static/task-workflows/manager-based-light.svg delete mode 100644 docs/source/overview/core-concepts/Direct-basedTaskWorkflow.jpg delete mode 100644 docs/source/overview/core-concepts/Manager-basedTaskWorkflow.jpg diff --git a/CONTRIBUTORS.md b/CONTRIBUTORS.md index c9075bc49b..d7b4042e53 100644 --- a/CONTRIBUTORS.md +++ b/CONTRIBUTORS.md @@ -6,7 +6,7 @@ To see the full list of contributors, please check the revision history in the s Guidelines for modifications: -* Please keep the lists sorted alphabetically. +* Please keep the **lists sorted alphabetically**. * Names should be added to this file as: *individual names* or *organizations*. * E-mail addresses are tracked elsewhere to avoid spam. @@ -19,6 +19,7 @@ Guidelines for modifications: --- +* Antonio Serrano-Muñoz * David Hoeller * Farbod Farshidian * Hunter Hansen @@ -36,7 +37,6 @@ Guidelines for modifications: * Amr Mousa * Andrej Orsula * Anton Bjørndahl Mortensen -* Antonio Serrano-Muñoz * Arjun Bhardwaj * Brayden Zhang * Calvin Yu @@ -62,6 +62,7 @@ Guidelines for modifications: * Michael Gussert * Muhong Guo * Nuralem Abizov +* Oyindamola Omotuyi * Özhan Özen * Qian Wan * Qinxi Yu diff --git a/docs/source/_static/task-workflows/direct-based-dark.svg b/docs/source/_static/task-workflows/direct-based-dark.svg new file mode 100644 index 0000000000..2709dae140 --- /dev/null +++ b/docs/source/_static/task-workflows/direct-based-dark.svg @@ -0,0 +1,3 @@ + + +
Sensors
Observations
Apply Actions
Define Task
Define Step
Environment Scripting
NVIDIA
Isaac Sim
Perform Resets
Rewards
Commands
Learning Agent
Scene Creation
Articulation
Objects
Compute Signals
Actions
Perform
Randomization
diff --git a/docs/source/_static/task-workflows/direct-based-light.svg b/docs/source/_static/task-workflows/direct-based-light.svg new file mode 100644 index 0000000000..b39bffa353 --- /dev/null +++ b/docs/source/_static/task-workflows/direct-based-light.svg @@ -0,0 +1,3 @@ + + +
Sensors
Observations
Apply Actions
Define Task
Define Step
Environment Scripting
NVIDIA
Isaac Sim
Perform Resets
Rewards
Commands
Learning Agent
Scene Creation
Articulation
Objects
Compute Signals
Actions
Perform
Randomization
diff --git a/docs/source/_static/task-workflows/manager-based-dark.svg b/docs/source/_static/task-workflows/manager-based-dark.svg new file mode 100644 index 0000000000..b66ba1bfee --- /dev/null +++ b/docs/source/_static/task-workflows/manager-based-dark.svg @@ -0,0 +1,3 @@ + + +
Action Manager
Task-space
Joint-space
Termination Manager
Reward Manager
Curriculum Manager
Learning
Agent
Custom
Command Manager
Custom
Velocity
Pose
Observation Manager
Proprioception
Custom
Exteroception
NVIDIA
Isaac Sim
Articulation
Objects
Sensors
Interactive Scene
Event Manager
External Disturbances
Domain Randomization
diff --git a/docs/source/_static/task-workflows/manager-based-light.svg b/docs/source/_static/task-workflows/manager-based-light.svg new file mode 100644 index 0000000000..60fe6119d4 --- /dev/null +++ b/docs/source/_static/task-workflows/manager-based-light.svg @@ -0,0 +1,3 @@ + + +
Action Manager
Task-space
Joint-space
Termination Manager
Reward Manager
Curriculum Manager
Learning
Agent
Custom
Command Manager
Custom
Velocity
Pose
Observation Manager
Proprioception
Custom
Exteroception
NVIDIA
Isaac Sim
Articulation
Objects
Sensors
Interactive Scene
Event Manager
External Disturbances
Domain Randomization
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z1qhS=p>_>wI?qO+Tk`rLH3`-s2(=S9ZZ3J@eNHz22Xem`{7-H*LXYJ8%YjZK_`9?s zl{SV@E+qH$vhhcJyBVOfMj!zkNp!d-*Z0oP{(F2vM2RQu)mkM!_g;LD-UL&i5@(C6 z6Kix?l4EN~r}HM@V6PXY@~9tc}UP8Y>43Mr5j2z#zt8 zF%nT=8wZ6jhi{gMcLPUA=X_s%u$VMT(HlAKJyAXu@WAG`Hnz<+B?X;2Vx8bhl{FY^mCD(!mWcT!7%hdu`KvCep%$ z46pQ$R&h|AYJK{ptDSd0?N+bZ&3jCi{v@(*ihtP#Rgnw!7;#_or#g1su>PoH)sPyV zF1#R7>6Urg!pQY~adqK<6>6AOdf7`X*biTloObID-iF`ZWOt+_z9QXqq`7!kpH|~_ z)J;XyVFpZ}@kNYmo8MekxP&dlBp6sU)t?_RN>5sa_oO|CzXPww2lv>NscfstcPQfP z&Aj6!y*CMvIvGT#nsJSJ+7BpT+k7uF3>E)_;9l)j&fHvlJ)`1qDOiAe{%JOyB7yO>IVZ z_z?RmGt$mg^vq8>c@M6Eplqsn1h(`q&d|yBft`!VWJK?0j%l~Mb)zH5io?=Dy;Pfb zjpyk={%F!PqvGm+(0RCjo(i>%LK5U3Cq7<+8*-i45_YB|zjhR#azA${U4=;v)6;iQ zKu{$6*cdz&IB~hFLPP*)qO42fS-LkDn~< zh^kvg`Lodt#{@)4qfyi5YpvlPG2;On>4vRe>TxqCULHiZc0)yl!v3iI-)A=d8V{%W z?$-7}N)A?AeGX0Pw_}J)r Date: Mon, 4 Nov 2024 11:54:34 -0500 Subject: [PATCH 055/111] Replaces TensorDict with native dictionary (#1348) # Description Remove TensorDict usage from Isaac Lab ## Type of change - Breaking change... for those ones using TensorDict specific API such as `camera.data.output.to_dict()` or `camera.data.output.sorted_keys` ## Screenshots Before ![Screenshot from 2024-10-30 12-45-06](https://github.com/user-attachments/assets/2dc0e827-3e12-4ae9-849e-e9f75c718157) After ![Screenshot from 2024-10-30 16-04-35](https://github.com/user-attachments/assets/715b6cb0-9f87-4938-8dbd-5c56203cb90e) ## Checklist - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [ ] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [ ] I have added tests that prove my fix is effective or that my feature works - [x] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [x] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --------- Co-authored-by: Kelly Guo --- .../omni.isaac.lab/config/extension.toml | 2 +- .../omni.isaac.lab/docs/CHANGELOG.rst | 9 +++++ .../omni/isaac/lab/sensors/camera/camera.py | 7 ++-- .../isaac/lab/sensors/camera/camera_data.py | 3 +- .../isaac/lab/sensors/camera/tiled_camera.py | 5 ++- .../sensors/ray_caster/ray_caster_camera.py | 3 +- .../test/sensors/test_camera.py | 6 ++-- .../test/sensors/test_ray_caster_camera.py | 8 ++--- .../test/sensors/test_tiled_camera.py | 34 +++++++++---------- .../04_sensors/run_ray_caster_camera.py | 11 ++---- .../tutorials/04_sensors/run_usd_camera.py | 5 +-- 11 files changed, 47 insertions(+), 46 deletions(-) diff --git a/source/extensions/omni.isaac.lab/config/extension.toml b/source/extensions/omni.isaac.lab/config/extension.toml index 6f43e77bf2..fc52aa2a47 100644 --- a/source/extensions/omni.isaac.lab/config/extension.toml +++ b/source/extensions/omni.isaac.lab/config/extension.toml @@ -1,7 +1,7 @@ [package] # Note: Semantic Versioning is used: https://semver.org/ -version = "0.27.11" +version = "0.27.12" # Description title = "Isaac Lab framework for Robot Learning" diff --git a/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst b/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst index b67d43e9ed..b37e90bd7e 100644 --- a/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst +++ b/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst @@ -1,6 +1,15 @@ Changelog --------- +0.27.12 (2024-01-04) +~~~~~~~~~~~~~~~~~~~ + +Removed +^^^^^^^ + +* Removed TensorDict usage in favor of Python dictionary in sensors + + 0.27.11 (2024-10-31) ~~~~~~~~~~~~~~~~~~~~ diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/camera/camera.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/camera/camera.py index 718fde0546..ed102319e7 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/camera/camera.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/camera/camera.py @@ -9,7 +9,6 @@ import re import torch from collections.abc import Sequence -from tensordict import TensorDict from typing import TYPE_CHECKING, Any, Literal import carb @@ -156,7 +155,7 @@ def __str__(self) -> str: # message for class return ( f"Camera @ '{self.cfg.prim_path}': \n" - f"\tdata types : {self.data.output.sorted_keys} \n" + f"\tdata types : {list(self.data.output.keys())} \n" f"\tsemantic filter : {self.cfg.semantic_filter}\n" f"\tcolorize semantic segm. : {self.cfg.colorize_semantic_segmentation}\n" f"\tcolorize instance segm. : {self.cfg.colorize_instance_segmentation}\n" @@ -497,7 +496,7 @@ def _update_buffers_impl(self, env_ids: Sequence[int]): self._update_poses(env_ids) # -- read the data from annotator registry # check if buffer is called for the first time. If so then, allocate the memory - if len(self._data.output.sorted_keys) == 0: + if len(self._data.output) == 0: # this is the first time buffer is called # it allocates memory for all the sensors self._create_annotator_data() @@ -552,7 +551,7 @@ def _create_buffers(self): # lazy allocation of data dictionary # since the size of the output data is not known in advance, we leave it as None # the memory will be allocated when the buffer() function is called for the first time. - self._data.output = TensorDict({}, batch_size=self._view.count, device=self.device) + self._data.output = {} self._data.info = [{name: None for name in self.cfg.data_types} for _ in range(self._view.count)] def _update_intrinsic_matrices(self, env_ids: Sequence[int]): diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/camera/camera_data.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/camera/camera_data.py index 2ffb2c7bf8..540fdb7dcf 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/camera/camera_data.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/camera/camera_data.py @@ -5,7 +5,6 @@ import torch from dataclasses import dataclass -from tensordict import TensorDict from typing import Any from omni.isaac.lab.utils.math import convert_camera_frame_orientation_convention @@ -47,7 +46,7 @@ class CameraData: Shape is (N, 3, 3) where N is the number of sensors. """ - output: TensorDict = None + output: dict[str, torch.Tensor] = None """The retrieved sensor data with sensor types as key. The format of the data is available in the `Replicator Documentation`_. For semantic-based data, diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/camera/tiled_camera.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/camera/tiled_camera.py index 1e465a4867..68ed4b38e8 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/camera/tiled_camera.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/camera/tiled_camera.py @@ -9,7 +9,6 @@ import numpy as np import torch from collections.abc import Sequence -from tensordict import TensorDict from typing import TYPE_CHECKING, Any import carb @@ -106,7 +105,7 @@ def __str__(self) -> str: # message for class return ( f"Tiled Camera @ '{self.cfg.prim_path}': \n" - f"\tdata types : {self.data.output.sorted_keys} \n" + f"\tdata types : {list(self.data.output.keys())} \n" f"\tsemantic filter : {self.cfg.semantic_filter}\n" f"\tcolorize semantic segm. : {self.cfg.colorize_semantic_segmentation}\n" f"\tcolorize instance segm. : {self.cfg.colorize_instance_segmentation}\n" @@ -372,7 +371,7 @@ def _create_buffers(self): (self._view.count, self.cfg.height, self.cfg.width, 1), device=self.device, dtype=torch.int32 ).contiguous() - self._data.output = TensorDict(data_dict, batch_size=self._view.count, device=self.device) + self._data.output = data_dict self._data.info = dict() def _tiled_image_shape(self) -> tuple[int, int]: diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/ray_caster/ray_caster_camera.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/ray_caster/ray_caster_camera.py index 91689b03ee..e458fc7849 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/ray_caster/ray_caster_camera.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/sensors/ray_caster/ray_caster_camera.py @@ -7,7 +7,6 @@ import torch from collections.abc import Sequence -from tensordict import TensorDict from typing import TYPE_CHECKING, ClassVar, Literal import omni.isaac.core.utils.stage as stage_utils @@ -347,7 +346,7 @@ def _create_buffers(self): self._data.image_shape = self.image_shape # -- output data # create the buffers to store the annotator data. - self._data.output = TensorDict({}, batch_size=self._view.count, device=self.device) + self._data.output = {} self._data.info = [{name: None for name in self.cfg.data_types}] * self._view.count for name in self.cfg.data_types: if name in ["distance_to_image_plane", "distance_to_camera"]: diff --git a/source/extensions/omni.isaac.lab/test/sensors/test_camera.py b/source/extensions/omni.isaac.lab/test/sensors/test_camera.py index bc8f8722df..388bd6c8c3 100644 --- a/source/extensions/omni.isaac.lab/test/sensors/test_camera.py +++ b/source/extensions/omni.isaac.lab/test/sensors/test_camera.py @@ -121,7 +121,7 @@ def test_camera_init(self): # update camera camera.update(self.dt) # check image data - for im_data in camera.data.output.to_dict().values(): + for im_data in camera.data.output.values(): self.assertEqual(im_data.shape, (1, self.camera_cfg.height, self.camera_cfg.width, 1)) def test_camera_init_offset(self): @@ -228,7 +228,7 @@ def test_multi_camera_init(self): cam_2.update(self.dt) # check image data for cam in [cam_1, cam_2]: - for im_data in cam.data.output.to_dict().values(): + for im_data in cam.data.output.values(): self.assertEqual(im_data.shape, (1, self.camera_cfg.height, self.camera_cfg.width, 1)) def test_multi_camera_with_different_resolution(self): @@ -705,7 +705,7 @@ def test_throughput(self): with Timer(f"Time taken for writing data with shape {camera.image_shape} "): # Pack data back into replicator format to save them using its writer rep_output = {"annotators": {}} - camera_data = convert_dict_to_backend(camera.data.output[0].to_dict(), backend="numpy") + camera_data = convert_dict_to_backend({k: v[0] for k, v in camera.data.output.items()}, backend="numpy") for key, data, info in zip(camera_data.keys(), camera_data.values(), camera.data.info[0].values()): if info is not None: rep_output["annotators"][key] = {"render_product": {"data": data, **info}} diff --git a/source/extensions/omni.isaac.lab/test/sensors/test_ray_caster_camera.py b/source/extensions/omni.isaac.lab/test/sensors/test_ray_caster_camera.py index ec932429ba..c6c6b4447a 100644 --- a/source/extensions/omni.isaac.lab/test/sensors/test_ray_caster_camera.py +++ b/source/extensions/omni.isaac.lab/test/sensors/test_ray_caster_camera.py @@ -129,7 +129,7 @@ def test_camera_init(self): # update camera camera.update(self.dt) # check image data - for im_data in camera.data.output.to_dict().values(): + for im_data in camera.data.output.values(): self.assertEqual( im_data.shape, (1, self.camera_cfg.pattern_cfg.height, self.camera_cfg.pattern_cfg.width, 1) ) @@ -147,7 +147,7 @@ def test_camera_resolution(self): self.sim.step() camera.update(self.dt) # access image data and compare shapes - for im_data in camera.data.output.to_dict().values(): + for im_data in camera.data.output.values(): self.assertTrue( im_data.shape == (1, self.camera_cfg.pattern_cfg.height, self.camera_cfg.pattern_cfg.width, 1) ) @@ -289,7 +289,7 @@ def test_multi_camera_init(self): cam_2.update(self.dt) # check image data for cam in [cam_1, cam_2]: - for im_data in cam.data.output.to_dict().values(): + for im_data in cam.data.output.values(): self.assertEqual( im_data.shape, (1, self.camera_cfg.pattern_cfg.height, self.camera_cfg.pattern_cfg.width, 1) ) @@ -392,7 +392,7 @@ def test_throughput(self): with Timer(f"Time taken for writing data with shape {camera.image_shape} "): # Pack data back into replicator format to save them using its writer rep_output = {"annotators": {}} - camera_data = convert_dict_to_backend(camera.data.output[0].to_dict(), backend="numpy") + camera_data = convert_dict_to_backend({k: v[0] for k, v in camera.data.output.items()}, backend="numpy") for key, data, info in zip(camera_data.keys(), camera_data.values(), camera.data.info[0].values()): if info is not None: rep_output["annotators"][key] = {"render_product": {"data": data, **info}} diff --git a/source/extensions/omni.isaac.lab/test/sensors/test_tiled_camera.py b/source/extensions/omni.isaac.lab/test/sensors/test_tiled_camera.py index 28446a52ef..617619d1b8 100644 --- a/source/extensions/omni.isaac.lab/test/sensors/test_tiled_camera.py +++ b/source/extensions/omni.isaac.lab/test/sensors/test_tiled_camera.py @@ -111,7 +111,7 @@ def test_single_camera_init(self): # update camera camera.update(self.dt) # check image data - for im_type, im_data in camera.data.output.to_dict().items(): + for im_type, im_data in camera.data.output.items(): if im_type == "rgb": self.assertEqual(im_data.shape, (1, self.camera_cfg.height, self.camera_cfg.width, 3)) self.assertGreater((im_data / 255.0).mean().item(), 0.0) @@ -162,7 +162,7 @@ def test_multi_camera_init(self): # update camera camera.update(self.dt) # check image data - for im_type, im_data in camera.data.output.to_dict().items(): + for im_type, im_data in camera.data.output.items(): if im_type == "rgb": self.assertEqual(im_data.shape, (num_cameras, self.camera_cfg.height, self.camera_cfg.width, 3)) for i in range(4): @@ -347,7 +347,7 @@ def test_rgba_only_camera(self): # update camera camera.update(self.dt) # check image data - for _, im_data in camera.data.output.to_dict().items(): + for _, im_data in camera.data.output.items(): self.assertEqual(im_data.shape, (num_cameras, self.camera_cfg.height, self.camera_cfg.width, 4)) for i in range(4): self.assertGreater((im_data[i] / 255.0).mean().item(), 0.0) @@ -399,7 +399,7 @@ def test_distance_to_camera_only_camera(self): # update camera camera.update(self.dt) # check image data - for _, im_data in camera.data.output.to_dict().items(): + for _, im_data in camera.data.output.items(): self.assertEqual(im_data.shape, (num_cameras, self.camera_cfg.height, self.camera_cfg.width, 1)) for i in range(4): self.assertGreater((im_data[i]).mean().item(), 0.0) @@ -451,7 +451,7 @@ def test_distance_to_image_plane_only_camera(self): # update camera camera.update(self.dt) # check image data - for _, im_data in camera.data.output.to_dict().items(): + for _, im_data in camera.data.output.items(): self.assertEqual(im_data.shape, (num_cameras, self.camera_cfg.height, self.camera_cfg.width, 1)) for i in range(4): self.assertGreater((im_data[i]).mean().item(), 0.0) @@ -503,7 +503,7 @@ def test_normals_only_camera(self): # update camera camera.update(self.dt) # check image data - for _, im_data in camera.data.output.to_dict().items(): + for _, im_data in camera.data.output.items(): self.assertEqual(im_data.shape, (num_cameras, self.camera_cfg.height, self.camera_cfg.width, 3)) for i in range(4): self.assertGreater((im_data[i]).mean().item(), 0.0) @@ -555,7 +555,7 @@ def test_motion_vectors_only_camera(self): # update camera camera.update(self.dt) # check image data - for _, im_data in camera.data.output.to_dict().items(): + for _, im_data in camera.data.output.items(): self.assertEqual(im_data.shape, (num_cameras, self.camera_cfg.height, self.camera_cfg.width, 2)) for i in range(4): self.assertGreater((im_data[i]).mean().item(), 0.0) @@ -607,7 +607,7 @@ def test_semantic_segmentation_colorize_only_camera(self): # update camera camera.update(self.dt) # check image data - for _, im_data in camera.data.output.to_dict().items(): + for _, im_data in camera.data.output.items(): self.assertEqual(im_data.shape, (num_cameras, self.camera_cfg.height, self.camera_cfg.width, 4)) for i in range(4): self.assertGreater((im_data[i] / 255.0).mean().item(), 0.0) @@ -660,7 +660,7 @@ def test_instance_segmentation_fast_colorize_only_camera(self): # update camera camera.update(self.dt) # check image data - for _, im_data in camera.data.output.to_dict().items(): + for _, im_data in camera.data.output.items(): self.assertEqual(im_data.shape, (num_cameras, self.camera_cfg.height, self.camera_cfg.width, 4)) for i in range(num_cameras): self.assertGreater((im_data[i] / 255.0).mean().item(), 0.0) @@ -713,7 +713,7 @@ def test_instance_id_segmentation_fast_colorize_only_camera(self): # update camera camera.update(self.dt) # check image data - for _, im_data in camera.data.output.to_dict().items(): + for _, im_data in camera.data.output.items(): self.assertEqual(im_data.shape, (num_cameras, self.camera_cfg.height, self.camera_cfg.width, 4)) for i in range(num_cameras): self.assertGreater((im_data[i] / 255.0).mean().item(), 0.0) @@ -767,7 +767,7 @@ def test_semantic_segmentation_non_colorize_only_camera(self): # update camera camera.update(self.dt) # check image data - for _, im_data in camera.data.output.to_dict().items(): + for _, im_data in camera.data.output.items(): self.assertEqual(im_data.shape, (num_cameras, self.camera_cfg.height, self.camera_cfg.width, 1)) for i in range(num_cameras): self.assertGreater(im_data[i].to(dtype=float).mean().item(), 0.0) @@ -822,7 +822,7 @@ def test_instance_segmentation_fast_non_colorize_only_camera(self): # update camera camera.update(self.dt) # check image data - for _, im_data in camera.data.output.to_dict().items(): + for _, im_data in camera.data.output.items(): self.assertEqual(im_data.shape, (num_cameras, self.camera_cfg.height, self.camera_cfg.width, 1)) for i in range(num_cameras): self.assertGreater(im_data[i].to(dtype=float).mean().item(), 0.0) @@ -876,7 +876,7 @@ def test_instance_id_segmentation_fast_non_colorize_only_camera(self): # update camera camera.update(self.dt) # check image data - for _, im_data in camera.data.output.to_dict().items(): + for _, im_data in camera.data.output.items(): self.assertEqual(im_data.shape, (num_cameras, self.camera_cfg.height, self.camera_cfg.width, 1)) for i in range(num_cameras): self.assertGreater(im_data[i].to(dtype=float).mean().item(), 0.0) @@ -941,7 +941,7 @@ def test_all_annotators_camera(self): # update camera camera.update(self.dt) # check image data - for data_type, im_data in camera.data.output.to_dict().items(): + for data_type, im_data in camera.data.output.items(): if data_type in ["rgb", "normals"]: self.assertEqual(im_data.shape, (num_cameras, self.camera_cfg.height, self.camera_cfg.width, 3)) elif data_type in [ @@ -1039,7 +1039,7 @@ def test_all_annotators_low_resolution_camera(self): # update camera camera.update(self.dt) # check image data - for data_type, im_data in camera.data.output.to_dict().items(): + for data_type, im_data in camera.data.output.items(): if data_type in ["rgb", "normals"]: self.assertEqual(im_data.shape, (num_cameras, camera_cfg.height, camera_cfg.width, 3)) elif data_type in [ @@ -1135,7 +1135,7 @@ def test_all_annotators_non_perfect_square_number_camera(self): # update camera camera.update(self.dt) # check image data - for data_type, im_data in camera.data.output.to_dict().items(): + for data_type, im_data in camera.data.output.items(): if data_type in ["rgb", "normals"]: self.assertEqual(im_data.shape, (num_cameras, self.camera_cfg.height, self.camera_cfg.width, 3)) elif data_type in [ @@ -1201,7 +1201,7 @@ def test_throughput(self): with Timer(f"Time taken for updating camera with shape {camera.image_shape}"): camera.update(self.dt) # Check image data - for im_type, im_data in camera.data.output.to_dict().items(): + for im_type, im_data in camera.data.output.items(): if im_type == "rgb": self.assertEqual(im_data.shape, (1, camera_cfg.height, camera_cfg.width, 3)) self.assertGreater((im_data / 255.0).mean().item(), 0.0) diff --git a/source/standalone/tutorials/04_sensors/run_ray_caster_camera.py b/source/standalone/tutorials/04_sensors/run_ray_caster_camera.py index a813bd74ea..22958ec3a3 100644 --- a/source/standalone/tutorials/04_sensors/run_ray_caster_camera.py +++ b/source/standalone/tutorials/04_sensors/run_ray_caster_camera.py @@ -129,14 +129,9 @@ def run_simulator(sim: sim_utils.SimulationContext, scene_entities: dict): # Extract camera data camera_index = 0 # note: BasicWriter only supports saving data in numpy format, so we need to convert the data to numpy. - if sim.backend == "torch": - # tensordict allows easy indexing of tensors in the dictionary - single_cam_data = convert_dict_to_backend(camera.data.output[camera_index], backend="numpy") - else: - # for numpy, we need to manually index the data - single_cam_data = dict() - for key, value in camera.data.output.items(): - single_cam_data[key] = value[camera_index] + single_cam_data = convert_dict_to_backend( + {k: v[camera_index] for k, v in camera.data.output.items()}, backend="numpy" + ) # Extract the other information single_cam_info = camera.data.info[camera_index] diff --git a/source/standalone/tutorials/04_sensors/run_usd_camera.py b/source/standalone/tutorials/04_sensors/run_usd_camera.py index 129a76f566..22d0871441 100644 --- a/source/standalone/tutorials/04_sensors/run_usd_camera.py +++ b/source/standalone/tutorials/04_sensors/run_usd_camera.py @@ -228,8 +228,9 @@ def run_simulator(sim: sim_utils.SimulationContext, scene_entities: dict): if args_cli.save: # Save images from camera at camera_index # note: BasicWriter only supports saving data in numpy format, so we need to convert the data to numpy. - # tensordict allows easy indexing of tensors in the dictionary - single_cam_data = convert_dict_to_backend(camera.data.output[camera_index], backend="numpy") + single_cam_data = convert_dict_to_backend( + {k: v[camera_index] for k, v in camera.data.output.items()}, backend="numpy" + ) # Extract the other information single_cam_info = camera.data.info[camera_index] From 6bf87f3798a288278a87fdbded03285f163cd2e1 Mon Sep 17 00:00:00 2001 From: Toni-SM Date: Mon, 4 Nov 2024 12:59:39 -0500 Subject: [PATCH 056/111] Improve omni.isaac.lab_tasks loading time (#1353) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit # Description Improve omni.isaac.lab_tasks loading time (13th Gen Intel® Core™ i9-13950HX × 32) * Before: 3.66 seconds * After: 84 milliseconds ## Screenshots Original (no changes) ![Screenshot from 2024-10-27 09-32-44](https://github.com/user-attachments/assets/2245d1c3-b0c8-47fc-8bc3-dd09c5e5303d) Define task entry points as string when registering ![Screenshot from 2024-10-27 18-12-20](https://github.com/user-attachments/assets/574fbddd-cd77-4b78-83ea-99c21dbcb214) Define task entry points as string when registering + Ignore `mdp` directories during import. ![Screenshot from 2024-10-28 10-20-00](https://github.com/user-attachments/assets/6fe6744c-ad2c-42fc-b6fa-ae1966281cbb) ## Checklist - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [ ] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [ ] I have added tests that prove my fix is effective or that my feature works - [x] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [x] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --------- Co-authored-by: Mayank Mittal Co-authored-by: Kelly Guo Co-authored-by: Kelly Guo --- .../config/extension.toml | 2 +- .../omni.isaac.lab_tasks/docs/CHANGELOG.rst | 12 +++++++++ .../omni/isaac/lab_tasks/__init__.py | 2 +- .../lab_tasks/direct/allegro_hand/__init__.py | 8 +++--- .../isaac/lab_tasks/direct/ant/__init__.py | 7 +++--- .../lab_tasks/direct/anymal_c/__init__.py | 11 ++++---- .../direct/cart_double_pendulum/__init__.py | 7 +++--- .../lab_tasks/direct/cartpole/__init__.py | 16 ++++++------ .../direct/franka_cabinet/__init__.py | 7 +++--- .../lab_tasks/direct/humanoid/__init__.py | 7 +++--- .../lab_tasks/direct/quadcopter/__init__.py | 7 +++--- .../lab_tasks/direct/shadow_hand/__init__.py | 25 ++++++++++--------- .../direct/shadow_hand_over/__init__.py | 8 +++--- .../manager_based/classic/ant/__init__.py | 6 +++-- .../classic/cartpole/__init__.py | 19 ++++++-------- .../classic/humanoid/__init__.py | 6 +++-- .../locomotion/velocity/config/a1/__init__.py | 12 +++++---- .../velocity/config/anymal_b/__init__.py | 12 +++++---- .../velocity/config/anymal_c/__init__.py | 12 +++++---- .../velocity/config/anymal_d/__init__.py | 12 +++++---- .../velocity/config/cassie/__init__.py | 12 +++++---- .../locomotion/velocity/config/g1/__init__.py | 12 +++++---- .../velocity/config/go1/__init__.py | 12 +++++---- .../velocity/config/go2/__init__.py | 12 +++++---- .../locomotion/velocity/config/h1/__init__.py | 12 +++++---- .../velocity/config/spot/__init__.py | 8 +++--- .../cabinet/config/franka/__init__.py | 12 +++++---- .../inhand/config/allegro_hand/__init__.py | 12 +++++---- .../lift/config/franka/__init__.py | 14 ++++++----- .../reach/config/franka/__init__.py | 12 +++++---- .../reach/config/ur_10/__init__.py | 8 +++--- .../navigation/config/anymal_c/__init__.py | 8 +++--- 32 files changed, 192 insertions(+), 140 deletions(-) diff --git a/source/extensions/omni.isaac.lab_tasks/config/extension.toml b/source/extensions/omni.isaac.lab_tasks/config/extension.toml index 544cd97377..c4beba4ecd 100644 --- a/source/extensions/omni.isaac.lab_tasks/config/extension.toml +++ b/source/extensions/omni.isaac.lab_tasks/config/extension.toml @@ -1,7 +1,7 @@ [package] # Note: Semantic Versioning is used: https://semver.org/ -version = "0.10.12" +version = "0.10.13" # Description title = "Isaac Lab Environments" diff --git a/source/extensions/omni.isaac.lab_tasks/docs/CHANGELOG.rst b/source/extensions/omni.isaac.lab_tasks/docs/CHANGELOG.rst index c194591492..c7912dcc6d 100644 --- a/source/extensions/omni.isaac.lab_tasks/docs/CHANGELOG.rst +++ b/source/extensions/omni.isaac.lab_tasks/docs/CHANGELOG.rst @@ -1,6 +1,17 @@ Changelog --------- +0.10.13 (2024-10-30) +~~~~~~~~~~~~~~~~~~~~ + +Changed +^^^^^^^ + +* Defined the Gymnasium task entry points with configuration strings instead of class types. + This avoids unnecessary imports and improves the load types. +* Blacklisted ``mdp`` directories during the recursive module search. + + 0.10.12 (2024-10-28) ~~~~~~~~~~~~~~~~~~~~ @@ -10,6 +21,7 @@ Changed * Changed manager-based vision cartpole environment names from Isaac-Cartpole-RGB-Camera-v0 and Isaac-Cartpole-Depth-Camera-v0 to Isaac-Cartpole-RGB-v0 and Isaac-Cartpole-Depth-v0 + 0.10.11 (2024-10-28) ~~~~~~~~~~~~~~~~~~~~ diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/__init__.py index 5dd39864d3..6f06dbcd02 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/__init__.py @@ -25,6 +25,6 @@ from .utils import import_packages # The blacklist is used to prevent importing configs from sub-packages -_BLACKLIST_PKGS = ["utils"] +_BLACKLIST_PKGS = ["utils", ".mdp"] # Import all configs in this package import_packages(__name__, _BLACKLIST_PKGS) diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/allegro_hand/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/allegro_hand/__init__.py index 0f4ed4544f..b851a255cf 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/allegro_hand/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/allegro_hand/__init__.py @@ -10,18 +10,20 @@ import gymnasium as gym from . import agents -from .allegro_hand_env_cfg import AllegroHandEnvCfg ## # Register Gym environments. ## +task_entry = "omni.isaac.lab_tasks.direct.allegro_hand" +inhand_task_entry = "omni.isaac.lab_tasks.direct.inhand_manipulation" + gym.register( id="Isaac-Repose-Cube-Allegro-Direct-v0", - entry_point="omni.isaac.lab_tasks.direct.inhand_manipulation:InHandManipulationEnv", + entry_point=f"{inhand_task_entry}.inhand_manipulation_env:InHandManipulationEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": AllegroHandEnvCfg, + "env_cfg_entry_point": f"{task_entry}.allegro_hand_env_cfg:AllegroHandEnvCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_cfg.yaml", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:AllegroHandPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_ppo_cfg.yaml", diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/ant/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/ant/__init__.py index 97a3814e6c..9d5deb0546 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/ant/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/ant/__init__.py @@ -10,18 +10,19 @@ import gymnasium as gym from . import agents -from .ant_env import AntEnv, AntEnvCfg ## # Register Gym environments. ## +task_entry = "omni.isaac.lab_tasks.direct.ant" + gym.register( id="Isaac-Ant-Direct-v0", - entry_point="omni.isaac.lab_tasks.direct.ant:AntEnv", + entry_point=f"{task_entry}.ant_env:AntEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": AntEnvCfg, + "env_cfg_entry_point": f"{task_entry}.ant_env:AntEnvCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_cfg.yaml", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:AntPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_ppo_cfg.yaml", diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/anymal_c/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/anymal_c/__init__.py index 1a245b7293..d217a90998 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/anymal_c/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/anymal_c/__init__.py @@ -10,18 +10,19 @@ import gymnasium as gym from . import agents -from .anymal_c_env import AnymalCEnv, AnymalCFlatEnvCfg, AnymalCRoughEnvCfg ## # Register Gym environments. ## +task_entry = "omni.isaac.lab_tasks.direct.anymal_c" + gym.register( id="Isaac-Velocity-Flat-Anymal-C-Direct-v0", - entry_point="omni.isaac.lab_tasks.direct.anymal_c:AnymalCEnv", + entry_point=f"{task_entry}.anymal_c_env:AnymalCEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": AnymalCFlatEnvCfg, + "env_cfg_entry_point": f"{task_entry}.anymal_c_env:AnymalCFlatEnvCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_flat_ppo_cfg.yaml", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:AnymalCFlatPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_flat_ppo_cfg.yaml", @@ -30,10 +31,10 @@ gym.register( id="Isaac-Velocity-Rough-Anymal-C-Direct-v0", - entry_point="omni.isaac.lab_tasks.direct.anymal_c:AnymalCEnv", + entry_point=f"{task_entry}.anymal_c_env:AnymalCEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": AnymalCRoughEnvCfg, + "env_cfg_entry_point": f"{task_entry}.anymal_c_env:AnymalCRoughEnvCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_rough_ppo_cfg.yaml", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:AnymalCRoughPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_rough_ppo_cfg.yaml", diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/cart_double_pendulum/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/cart_double_pendulum/__init__.py index 2b034f4f2e..e09b1658e1 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/cart_double_pendulum/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/cart_double_pendulum/__init__.py @@ -10,18 +10,19 @@ import gymnasium as gym from . import agents -from .cart_double_pendulum_env import CartDoublePendulumEnv, CartDoublePendulumEnvCfg ## # Register Gym environments. ## +task_entry = "omni.isaac.lab_tasks.direct.cart_double_pendulum" + gym.register( id="Isaac-Cart-Double-Pendulum-Direct-v0", - entry_point="omni.isaac.lab_tasks.direct.cart_double_pendulum:CartDoublePendulumEnv", + entry_point=f"{task_entry}.cart_double_pendulum_env:CartDoublePendulumEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": CartDoublePendulumEnvCfg, + "env_cfg_entry_point": f"{task_entry}.cart_double_pendulum_env:CartDoublePendulumEnvCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_cfg.yaml", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_ppo_cfg.yaml", "skrl_ippo_cfg_entry_point": f"{agents.__name__}:skrl_ippo_cfg.yaml", diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/cartpole/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/cartpole/__init__.py index 9f07c14605..64b24850eb 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/cartpole/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/cartpole/__init__.py @@ -10,19 +10,19 @@ import gymnasium as gym from . import agents -from .cartpole_camera_env import CartpoleCameraEnv, CartpoleDepthCameraEnvCfg, CartpoleRGBCameraEnvCfg -from .cartpole_env import CartpoleEnv, CartpoleEnvCfg ## # Register Gym environments. ## +task_entry = "omni.isaac.lab_tasks.direct.cartpole" + gym.register( id="Isaac-Cartpole-Direct-v0", - entry_point="omni.isaac.lab_tasks.direct.cartpole:CartpoleEnv", + entry_point=f"{task_entry}.cartpole_env:CartpoleEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": CartpoleEnvCfg, + "env_cfg_entry_point": f"{task_entry}.cartpole_env:CartpoleEnvCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_cfg.yaml", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:CartpolePPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_ppo_cfg.yaml", @@ -32,10 +32,10 @@ gym.register( id="Isaac-Cartpole-RGB-Camera-Direct-v0", - entry_point="omni.isaac.lab_tasks.direct.cartpole:CartpoleCameraEnv", + entry_point=f"{task_entry}.cartpole_camera_env:CartpoleCameraEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": CartpoleRGBCameraEnvCfg, + "env_cfg_entry_point": f"{task_entry}.cartpole_camera_env:CartpoleRGBCameraEnvCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_camera_ppo_cfg.yaml", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_camera_ppo_cfg.yaml", }, @@ -43,10 +43,10 @@ gym.register( id="Isaac-Cartpole-Depth-Camera-Direct-v0", - entry_point="omni.isaac.lab_tasks.direct.cartpole:CartpoleCameraEnv", + entry_point=f"{task_entry}.cartpole_camera_env:CartpoleCameraEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": CartpoleDepthCameraEnvCfg, + "env_cfg_entry_point": f"{task_entry}.cartpole_camera_env:CartpoleDepthCameraEnvCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_camera_ppo_cfg.yaml", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_camera_ppo_cfg.yaml", }, diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/franka_cabinet/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/franka_cabinet/__init__.py index 5f333dc9cf..14df4e20df 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/franka_cabinet/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/franka_cabinet/__init__.py @@ -9,18 +9,19 @@ import gymnasium as gym from . import agents -from .franka_cabinet_env import FrankaCabinetEnv, FrankaCabinetEnvCfg ## # Register Gym environments. ## +task_entry = "omni.isaac.lab_tasks.direct.franka_cabinet" + gym.register( id="Isaac-Franka-Cabinet-Direct-v0", - entry_point="omni.isaac.lab_tasks.direct.franka_cabinet:FrankaCabinetEnv", + entry_point=f"{task_entry}.franka_cabinet_env:FrankaCabinetEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": FrankaCabinetEnvCfg, + "env_cfg_entry_point": f"{task_entry}.franka_cabinet_env:FrankaCabinetEnvCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_cfg.yaml", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:FrankaCabinetPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_ppo_cfg.yaml", diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/humanoid/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/humanoid/__init__.py index 92e8384926..687c5fcf30 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/humanoid/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/humanoid/__init__.py @@ -10,18 +10,19 @@ import gymnasium as gym from . import agents -from .humanoid_env import HumanoidEnv, HumanoidEnvCfg ## # Register Gym environments. ## +task_entry = "omni.isaac.lab_tasks.direct.humanoid" + gym.register( id="Isaac-Humanoid-Direct-v0", - entry_point="omni.isaac.lab_tasks.direct.humanoid:HumanoidEnv", + entry_point=f"{task_entry}.humanoid_env:HumanoidEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": HumanoidEnvCfg, + "env_cfg_entry_point": f"{task_entry}.humanoid_env:HumanoidEnvCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_cfg.yaml", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:HumanoidPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_ppo_cfg.yaml", diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/quadcopter/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/quadcopter/__init__.py index bc2bc74ce9..523ca0d9f8 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/quadcopter/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/quadcopter/__init__.py @@ -10,18 +10,19 @@ import gymnasium as gym from . import agents -from .quadcopter_env import QuadcopterEnv, QuadcopterEnvCfg ## # Register Gym environments. ## +task_entry = "omni.isaac.lab_tasks.direct.quadcopter" + gym.register( id="Isaac-Quadcopter-Direct-v0", - entry_point="omni.isaac.lab_tasks.direct.quadcopter:QuadcopterEnv", + entry_point=f"{task_entry}.quadcopter_env:QuadcopterEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": QuadcopterEnvCfg, + "env_cfg_entry_point": f"{task_entry}.quadcopter_env:QuadcopterEnvCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_cfg.yaml", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:QuadcopterPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_ppo_cfg.yaml", diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/shadow_hand/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/shadow_hand/__init__.py index 07ac1b10f2..9f48e206a0 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/shadow_hand/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/shadow_hand/__init__.py @@ -10,19 +10,20 @@ import gymnasium as gym from . import agents -from .shadow_hand_env_cfg import ShadowHandEnvCfg, ShadowHandOpenAIEnvCfg -from .shadow_hand_vision_env import ShadowHandVisionEnvCfg, ShadowHandVisionEnvPlayCfg ## # Register Gym environments. ## +task_entry = "omni.isaac.lab_tasks.direct.shadow_hand" +inhand_task_entry = "omni.isaac.lab_tasks.direct.inhand_manipulation" + gym.register( id="Isaac-Repose-Cube-Shadow-Direct-v0", - entry_point="omni.isaac.lab_tasks.direct.inhand_manipulation:InHandManipulationEnv", + entry_point=f"{inhand_task_entry}.inhand_manipulation_env:InHandManipulationEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": ShadowHandEnvCfg, + "env_cfg_entry_point": f"{task_entry}.shadow_hand_env_cfg:ShadowHandEnvCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_cfg.yaml", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:ShadowHandPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_ppo_cfg.yaml", @@ -31,10 +32,10 @@ gym.register( id="Isaac-Repose-Cube-Shadow-OpenAI-FF-Direct-v0", - entry_point="omni.isaac.lab_tasks.direct.inhand_manipulation:InHandManipulationEnv", + entry_point=f"{inhand_task_entry}.inhand_manipulation_env:InHandManipulationEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": ShadowHandOpenAIEnvCfg, + "env_cfg_entry_point": f"{task_entry}.shadow_hand_env_cfg:ShadowHandOpenAIEnvCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_ff_cfg.yaml", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:ShadowHandAsymFFPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_ff_ppo_cfg.yaml", @@ -43,10 +44,10 @@ gym.register( id="Isaac-Repose-Cube-Shadow-OpenAI-LSTM-Direct-v0", - entry_point="omni.isaac.lab_tasks.direct.inhand_manipulation:InHandManipulationEnv", + entry_point=f"{inhand_task_entry}.inhand_manipulation_env:InHandManipulationEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": ShadowHandOpenAIEnvCfg, + "env_cfg_entry_point": f"{task_entry}.shadow_hand_env_cfg:ShadowHandOpenAIEnvCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_lstm_cfg.yaml", }, ) @@ -55,10 +56,10 @@ gym.register( id="Isaac-Repose-Cube-Shadow-Vision-Direct-v0", - entry_point="omni.isaac.lab_tasks.direct.shadow_hand.shadow_hand_vision_env:ShadowHandVisionEnv", + entry_point=f"{task_entry}.shadow_hand_vision_env:ShadowHandVisionEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": ShadowHandVisionEnvCfg, + "env_cfg_entry_point": f"{task_entry}.shadow_hand_vision_env:ShadowHandVisionEnvCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:ShadowHandVisionFFPPORunnerCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_vision_cfg.yaml", }, @@ -66,10 +67,10 @@ gym.register( id="Isaac-Repose-Cube-Shadow-Vision-Direct-Play-v0", - entry_point="omni.isaac.lab_tasks.direct.shadow_hand.shadow_hand_vision_env:ShadowHandVisionEnv", + entry_point=f"{task_entry}.shadow_hand_vision_env:ShadowHandVisionEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": ShadowHandVisionEnvPlayCfg, + "env_cfg_entry_point": f"{task_entry}.shadow_hand_vision_env:ShadowHandVisionEnvPlayCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:ShadowHandVisionFFPPORunnerCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_vision_cfg.yaml", }, diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/shadow_hand_over/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/shadow_hand_over/__init__.py index 0beb0a0d61..e226d6dcf4 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/shadow_hand_over/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/shadow_hand_over/__init__.py @@ -10,19 +10,19 @@ import gymnasium as gym from . import agents -from .shadow_hand_over_env import ShadowHandOverEnv -from .shadow_hand_over_env_cfg import ShadowHandOverEnvCfg ## # Register Gym environments. ## +task_entry = "omni.isaac.lab_tasks.direct.shadow_hand_over" + gym.register( id="Isaac-Shadow-Hand-Over-Direct-v0", - entry_point="omni.isaac.lab_tasks.direct.shadow_hand_over:ShadowHandOverEnv", + entry_point=f"{task_entry}.shadow_hand_over_env:ShadowHandOverEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": ShadowHandOverEnvCfg, + "env_cfg_entry_point": f"{task_entry}.shadow_hand_over_env_cfg:ShadowHandOverEnvCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_cfg.yaml", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_ppo_cfg.yaml", "skrl_ippo_cfg_entry_point": f"{agents.__name__}:skrl_ippo_cfg.yaml", diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/ant/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/ant/__init__.py index ed3c86eab3..d5e96aa9b3 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/ant/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/ant/__init__.py @@ -9,18 +9,20 @@ import gymnasium as gym -from . import agents, ant_env_cfg +from . import agents ## # Register Gym environments. ## +task_entry = "omni.isaac.lab_tasks.manager_based.classic.ant" + gym.register( id="Isaac-Ant-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": ant_env_cfg.AntEnvCfg, + "env_cfg_entry_point": f"{task_entry}.ant_env_cfg:AntEnvCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:AntPPORunnerCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_cfg.yaml", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_ppo_cfg.yaml", diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/cartpole/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/cartpole/__init__.py index 43040be70a..264684ee32 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/cartpole/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/cartpole/__init__.py @@ -10,24 +10,19 @@ import gymnasium as gym from . import agents -from .cartpole_camera_env_cfg import ( - CartpoleDepthCameraEnvCfg, - CartpoleResNet18CameraEnvCfg, - CartpoleRGBCameraEnvCfg, - CartpoleTheiaTinyCameraEnvCfg, -) -from .cartpole_env_cfg import CartpoleEnvCfg ## # Register Gym environments. ## +task_entry = "omni.isaac.lab_tasks.manager_based.classic.cartpole" + gym.register( id="Isaac-Cartpole-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": CartpoleEnvCfg, + "env_cfg_entry_point": f"{task_entry}.cartpole_env_cfg:CartpoleEnvCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_cfg.yaml", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:CartpolePPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_ppo_cfg.yaml", @@ -40,7 +35,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": CartpoleRGBCameraEnvCfg, + "env_cfg_entry_point": f"{task_entry}.cartpole_camera_env_cfg:CartpoleRGBCameraEnvCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_camera_ppo_cfg.yaml", }, ) @@ -50,7 +45,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": CartpoleDepthCameraEnvCfg, + "env_cfg_entry_point": f"{task_entry}.cartpole_camera_env_cfg:CartpoleDepthCameraEnvCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_camera_ppo_cfg.yaml", }, ) @@ -60,7 +55,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": CartpoleResNet18CameraEnvCfg, + "env_cfg_entry_point": f"{task_entry}.cartpole_camera_env_cfg:CartpoleResNet18CameraEnvCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_feature_ppo_cfg.yaml", }, ) @@ -70,7 +65,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": CartpoleTheiaTinyCameraEnvCfg, + "env_cfg_entry_point": f"{task_entry}.cartpole_camera_env_cfg:CartpoleTheiaTinyCameraEnvCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_feature_ppo_cfg.yaml", }, ) diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/humanoid/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/humanoid/__init__.py index c902b83af5..1a2084d791 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/humanoid/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/humanoid/__init__.py @@ -9,18 +9,20 @@ import gymnasium as gym -from . import agents, humanoid_env_cfg +from . import agents ## # Register Gym environments. ## +task_entry = "omni.isaac.lab_tasks.manager_based.classic.humanoid" + gym.register( id="Isaac-Humanoid-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": humanoid_env_cfg.HumanoidEnvCfg, + "env_cfg_entry_point": f"{task_entry}.humanoid_env_cfg:HumanoidEnvCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:HumanoidPPORunnerCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_cfg.yaml", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_ppo_cfg.yaml", diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/a1/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/a1/__init__.py index 80e9c3750f..d3ce2ca1fc 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/a1/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/a1/__init__.py @@ -5,18 +5,20 @@ import gymnasium as gym -from . import agents, flat_env_cfg, rough_env_cfg +from . import agents ## # Register Gym environments. ## +task_entry = "omni.isaac.lab_tasks.manager_based.locomotion.velocity.config.a1" + gym.register( id="Isaac-Velocity-Flat-Unitree-A1-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": flat_env_cfg.UnitreeA1FlatEnvCfg, + "env_cfg_entry_point": f"{task_entry}.flat_env_cfg:UnitreeA1FlatEnvCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:UnitreeA1FlatPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_flat_ppo_cfg.yaml", }, @@ -27,7 +29,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": flat_env_cfg.UnitreeA1FlatEnvCfg_PLAY, + "env_cfg_entry_point": f"{task_entry}.flat_env_cfg:UnitreeA1FlatEnvCfg_PLAY", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:UnitreeA1FlatPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_flat_ppo_cfg.yaml", }, @@ -38,7 +40,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": rough_env_cfg.UnitreeA1RoughEnvCfg, + "env_cfg_entry_point": f"{task_entry}.rough_env_cfg:UnitreeA1RoughEnvCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:UnitreeA1RoughPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_rough_ppo_cfg.yaml", }, @@ -49,7 +51,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": rough_env_cfg.UnitreeA1RoughEnvCfg_PLAY, + "env_cfg_entry_point": f"{task_entry}.rough_env_cfg:UnitreeA1RoughEnvCfg_PLAY", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:UnitreeA1RoughPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_rough_ppo_cfg.yaml", }, diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/anymal_b/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/anymal_b/__init__.py index 65e89a1d9e..52f1cc55c9 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/anymal_b/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/anymal_b/__init__.py @@ -4,18 +4,20 @@ # SPDX-License-Identifier: BSD-3-Clause import gymnasium as gym -from . import agents, flat_env_cfg, rough_env_cfg +from . import agents ## # Register Gym environments. ## +task_entry = "omni.isaac.lab_tasks.manager_based.locomotion.velocity.config.anymal_b" + gym.register( id="Isaac-Velocity-Flat-Anymal-B-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": flat_env_cfg.AnymalBFlatEnvCfg, + "env_cfg_entry_point": f"{task_entry}.flat_env_cfg:AnymalBFlatEnvCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:AnymalBFlatPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_flat_ppo_cfg.yaml", }, @@ -26,7 +28,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": flat_env_cfg.AnymalBFlatEnvCfg_PLAY, + "env_cfg_entry_point": f"{task_entry}.flat_env_cfg:AnymalBFlatEnvCfg_PLAY", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:AnymalBFlatPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_flat_ppo_cfg.yaml", }, @@ -37,7 +39,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": rough_env_cfg.AnymalBRoughEnvCfg, + "env_cfg_entry_point": f"{task_entry}.rough_env_cfg:AnymalBRoughEnvCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:AnymalBRoughPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_rough_ppo_cfg.yaml", }, @@ -48,7 +50,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": rough_env_cfg.AnymalBRoughEnvCfg_PLAY, + "env_cfg_entry_point": f"{task_entry}.rough_env_cfg:AnymalBRoughEnvCfg_PLAY", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:AnymalBRoughPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_rough_ppo_cfg.yaml", }, diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/anymal_c/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/anymal_c/__init__.py index 1d5aa41c87..020bc3854a 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/anymal_c/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/anymal_c/__init__.py @@ -5,18 +5,20 @@ import gymnasium as gym -from . import agents, flat_env_cfg, rough_env_cfg +from . import agents ## # Register Gym environments. ## +task_entry = "omni.isaac.lab_tasks.manager_based.locomotion.velocity.config.anymal_c" + gym.register( id="Isaac-Velocity-Flat-Anymal-C-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": flat_env_cfg.AnymalCFlatEnvCfg, + "env_cfg_entry_point": f"{task_entry}.flat_env_cfg:AnymalCFlatEnvCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:AnymalCFlatPPORunnerCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_flat_ppo_cfg.yaml", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_flat_ppo_cfg.yaml", @@ -28,7 +30,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": flat_env_cfg.AnymalCFlatEnvCfg_PLAY, + "env_cfg_entry_point": f"{task_entry}.flat_env_cfg:AnymalCFlatEnvCfg_PLAY", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_flat_ppo_cfg.yaml", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:AnymalCFlatPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_flat_ppo_cfg.yaml", @@ -40,7 +42,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": rough_env_cfg.AnymalCRoughEnvCfg, + "env_cfg_entry_point": f"{task_entry}.rough_env_cfg:AnymalCRoughEnvCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_rough_ppo_cfg.yaml", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:AnymalCRoughPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_rough_ppo_cfg.yaml", @@ -52,7 +54,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": rough_env_cfg.AnymalCRoughEnvCfg_PLAY, + "env_cfg_entry_point": f"{task_entry}.rough_env_cfg:AnymalCRoughEnvCfg_PLAY", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_rough_ppo_cfg.yaml", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:AnymalCRoughPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_rough_ppo_cfg.yaml", diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/anymal_d/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/anymal_d/__init__.py index 0f6b8a4776..d6054be1a4 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/anymal_d/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/anymal_d/__init__.py @@ -5,18 +5,20 @@ import gymnasium as gym -from . import agents, flat_env_cfg, rough_env_cfg +from . import agents ## # Register Gym environments. ## +task_entry = "omni.isaac.lab_tasks.manager_based.locomotion.velocity.config.anymal_d" + gym.register( id="Isaac-Velocity-Flat-Anymal-D-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": flat_env_cfg.AnymalDFlatEnvCfg, + "env_cfg_entry_point": f"{task_entry}.flat_env_cfg:AnymalDFlatEnvCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:AnymalDFlatPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_flat_ppo_cfg.yaml", }, @@ -27,7 +29,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": flat_env_cfg.AnymalDFlatEnvCfg_PLAY, + "env_cfg_entry_point": f"{task_entry}.flat_env_cfg:AnymalDFlatEnvCfg_PLAY", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:AnymalDFlatPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_flat_ppo_cfg.yaml", }, @@ -38,7 +40,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": rough_env_cfg.AnymalDRoughEnvCfg, + "env_cfg_entry_point": f"{task_entry}.rough_env_cfg:AnymalDRoughEnvCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:AnymalDRoughPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_rough_ppo_cfg.yaml", }, @@ -49,7 +51,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": rough_env_cfg.AnymalDRoughEnvCfg_PLAY, + "env_cfg_entry_point": f"{task_entry}.rough_env_cfg:AnymalDRoughEnvCfg_PLAY", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:AnymalDRoughPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_rough_ppo_cfg.yaml", }, diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/cassie/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/cassie/__init__.py index 495491f617..3b37b34b41 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/cassie/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/cassie/__init__.py @@ -5,18 +5,20 @@ import gymnasium as gym -from . import agents, flat_env_cfg, rough_env_cfg +from . import agents ## # Register Gym environments. ## +task_entry = "omni.isaac.lab_tasks.manager_based.locomotion.velocity.config.cassie" + gym.register( id="Isaac-Velocity-Flat-Cassie-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": flat_env_cfg.CassieFlatEnvCfg, + "env_cfg_entry_point": f"{task_entry}.flat_env_cfg:CassieFlatEnvCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:CassieFlatPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_flat_ppo_cfg.yaml", }, @@ -27,7 +29,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": flat_env_cfg.CassieFlatEnvCfg_PLAY, + "env_cfg_entry_point": f"{task_entry}.flat_env_cfg:CassieFlatEnvCfg_PLAY", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:CassieFlatPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_flat_ppo_cfg.yaml", }, @@ -38,7 +40,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": rough_env_cfg.CassieRoughEnvCfg, + "env_cfg_entry_point": f"{task_entry}.rough_env_cfg:CassieRoughEnvCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:CassieRoughPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_rough_ppo_cfg.yaml", }, @@ -49,7 +51,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": rough_env_cfg.CassieRoughEnvCfg_PLAY, + "env_cfg_entry_point": f"{task_entry}.rough_env_cfg:CassieRoughEnvCfg_PLAY", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:CassieRoughPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_rough_ppo_cfg.yaml", }, diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/g1/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/g1/__init__.py index c84c627099..7c50e5dfb5 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/g1/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/g1/__init__.py @@ -5,19 +5,21 @@ import gymnasium as gym -from . import agents, flat_env_cfg, rough_env_cfg +from . import agents ## # Register Gym environments. ## +task_entry = "omni.isaac.lab_tasks.manager_based.locomotion.velocity.config.g1" + gym.register( id="Isaac-Velocity-Rough-G1-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": rough_env_cfg.G1RoughEnvCfg, + "env_cfg_entry_point": f"{task_entry}.rough_env_cfg:G1RoughEnvCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:G1RoughPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_rough_ppo_cfg.yaml", }, @@ -29,7 +31,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": rough_env_cfg.G1RoughEnvCfg_PLAY, + "env_cfg_entry_point": f"{task_entry}.rough_env_cfg:G1RoughEnvCfg_PLAY", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:G1RoughPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_rough_ppo_cfg.yaml", }, @@ -41,7 +43,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": flat_env_cfg.G1FlatEnvCfg, + "env_cfg_entry_point": f"{task_entry}.flat_env_cfg:G1FlatEnvCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:G1FlatPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_flat_ppo_cfg.yaml", }, @@ -53,7 +55,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": flat_env_cfg.G1FlatEnvCfg_PLAY, + "env_cfg_entry_point": f"{task_entry}.flat_env_cfg:G1FlatEnvCfg_PLAY", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:G1FlatPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_flat_ppo_cfg.yaml", }, diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/go1/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/go1/__init__.py index 260e68cff1..68ca2a6f54 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/go1/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/go1/__init__.py @@ -5,18 +5,20 @@ import gymnasium as gym -from . import agents, flat_env_cfg, rough_env_cfg +from . import agents ## # Register Gym environments. ## +task_entry = "omni.isaac.lab_tasks.manager_based.locomotion.velocity.config.go1" + gym.register( id="Isaac-Velocity-Flat-Unitree-Go1-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": flat_env_cfg.UnitreeGo1FlatEnvCfg, + "env_cfg_entry_point": f"{task_entry}.flat_env_cfg:UnitreeGo1FlatEnvCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:UnitreeGo1FlatPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_flat_ppo_cfg.yaml", }, @@ -27,7 +29,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": flat_env_cfg.UnitreeGo1FlatEnvCfg_PLAY, + "env_cfg_entry_point": f"{task_entry}.flat_env_cfg:UnitreeGo1FlatEnvCfg_PLAY", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:UnitreeGo1FlatPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_flat_ppo_cfg.yaml", }, @@ -38,7 +40,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": rough_env_cfg.UnitreeGo1RoughEnvCfg, + "env_cfg_entry_point": f"{task_entry}.rough_env_cfg:UnitreeGo1RoughEnvCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:UnitreeGo1RoughPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_rough_ppo_cfg.yaml", }, @@ -49,7 +51,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": rough_env_cfg.UnitreeGo1RoughEnvCfg_PLAY, + "env_cfg_entry_point": f"{task_entry}.rough_env_cfg:UnitreeGo1RoughEnvCfg_PLAY", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:UnitreeGo1RoughPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_rough_ppo_cfg.yaml", }, diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/go2/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/go2/__init__.py index 27b3483956..819c5bc0b9 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/go2/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/go2/__init__.py @@ -5,18 +5,20 @@ import gymnasium as gym -from . import agents, flat_env_cfg, rough_env_cfg +from . import agents ## # Register Gym environments. ## +task_entry = "omni.isaac.lab_tasks.manager_based.locomotion.velocity.config.go2" + gym.register( id="Isaac-Velocity-Flat-Unitree-Go2-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": flat_env_cfg.UnitreeGo2FlatEnvCfg, + "env_cfg_entry_point": f"{task_entry}.flat_env_cfg:UnitreeGo2FlatEnvCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:UnitreeGo2FlatPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_flat_ppo_cfg.yaml", }, @@ -27,7 +29,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": flat_env_cfg.UnitreeGo2FlatEnvCfg_PLAY, + "env_cfg_entry_point": f"{task_entry}.flat_env_cfg:UnitreeGo2FlatEnvCfg_PLAY", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:UnitreeGo2FlatPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_flat_ppo_cfg.yaml", }, @@ -38,7 +40,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": rough_env_cfg.UnitreeGo2RoughEnvCfg, + "env_cfg_entry_point": f"{task_entry}.rough_env_cfg:UnitreeGo2RoughEnvCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:UnitreeGo2RoughPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_rough_ppo_cfg.yaml", }, @@ -49,7 +51,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": rough_env_cfg.UnitreeGo2RoughEnvCfg_PLAY, + "env_cfg_entry_point": f"{task_entry}.rough_env_cfg:UnitreeGo2RoughEnvCfg_PLAY", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:UnitreeGo2RoughPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_rough_ppo_cfg.yaml", }, diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/h1/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/h1/__init__.py index 5c405ea4ef..f95053e7bd 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/h1/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/h1/__init__.py @@ -5,19 +5,21 @@ import gymnasium as gym -from . import agents, flat_env_cfg, rough_env_cfg +from . import agents ## # Register Gym environments. ## +task_entry = "omni.isaac.lab_tasks.manager_based.locomotion.velocity.config.h1" + gym.register( id="Isaac-Velocity-Rough-H1-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": rough_env_cfg.H1RoughEnvCfg, + "env_cfg_entry_point": f"{task_entry}.rough_env_cfg:H1RoughEnvCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:H1RoughPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_rough_ppo_cfg.yaml", }, @@ -29,7 +31,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": rough_env_cfg.H1RoughEnvCfg_PLAY, + "env_cfg_entry_point": f"{task_entry}.rough_env_cfg:H1RoughEnvCfg_PLAY", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:H1RoughPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_rough_ppo_cfg.yaml", }, @@ -41,7 +43,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": flat_env_cfg.H1FlatEnvCfg, + "env_cfg_entry_point": f"{task_entry}.flat_env_cfg:H1FlatEnvCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:H1FlatPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_flat_ppo_cfg.yaml", }, @@ -53,7 +55,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": flat_env_cfg.H1FlatEnvCfg_PLAY, + "env_cfg_entry_point": f"{task_entry}.flat_env_cfg:H1FlatEnvCfg_PLAY", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:H1FlatPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_flat_ppo_cfg.yaml", }, diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/spot/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/spot/__init__.py index fda9123ea6..e614dd40bd 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/spot/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/spot/__init__.py @@ -5,18 +5,20 @@ import gymnasium as gym -from . import agents, flat_env_cfg +from . import agents ## # Register Gym environments. ## +task_entry = "omni.isaac.lab_tasks.manager_based.locomotion.velocity.config.spot" + gym.register( id="Isaac-Velocity-Flat-Spot-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": flat_env_cfg.SpotFlatEnvCfg, + "env_cfg_entry_point": f"{task_entry}.flat_env_cfg:SpotFlatEnvCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:SpotFlatPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_flat_ppo_cfg.yaml", }, @@ -27,7 +29,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": flat_env_cfg.SpotFlatEnvCfg_PLAY, + "env_cfg_entry_point": f"{task_entry}.flat_env_cfg:SpotFlatEnvCfg_PLAY", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:SpotFlatPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_flat_ppo_cfg.yaml", }, diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/cabinet/config/franka/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/cabinet/config/franka/__init__.py index 192bcf6d6b..249b2e54be 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/cabinet/config/franka/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/cabinet/config/franka/__init__.py @@ -5,12 +5,14 @@ import gymnasium as gym -from . import agents, ik_abs_env_cfg, ik_rel_env_cfg, joint_pos_env_cfg +from . import agents ## # Register Gym environments. ## +task_entry = "omni.isaac.lab_tasks.manager_based.manipulation.cabinet.config.franka" + ## # Joint Position Control ## @@ -19,7 +21,7 @@ id="Isaac-Open-Drawer-Franka-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", kwargs={ - "env_cfg_entry_point": joint_pos_env_cfg.FrankaCabinetEnvCfg, + "env_cfg_entry_point": f"{task_entry}.joint_pos_env_cfg:FrankaCabinetEnvCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:CabinetPPORunnerCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_cfg.yaml", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_ppo_cfg.yaml", @@ -31,7 +33,7 @@ id="Isaac-Open-Drawer-Franka-Play-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", kwargs={ - "env_cfg_entry_point": joint_pos_env_cfg.FrankaCabinetEnvCfg_PLAY, + "env_cfg_entry_point": f"{task_entry}.joint_pos_env_cfg:FrankaCabinetEnvCfg_PLAY", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:CabinetPPORunnerCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_cfg.yaml", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_ppo_cfg.yaml", @@ -48,7 +50,7 @@ id="Isaac-Open-Drawer-Franka-IK-Abs-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", kwargs={ - "env_cfg_entry_point": ik_abs_env_cfg.FrankaCabinetEnvCfg, + "env_cfg_entry_point": f"{task_entry}.ik_abs_env_cfg:FrankaCabinetEnvCfg", }, disable_env_checker=True, ) @@ -61,7 +63,7 @@ id="Isaac-Open-Drawer-Franka-IK-Rel-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", kwargs={ - "env_cfg_entry_point": ik_rel_env_cfg.FrankaCabinetEnvCfg, + "env_cfg_entry_point": f"{task_entry}.ik_rel_env_cfg:FrankaCabinetEnvCfg", }, disable_env_checker=True, ) diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/inhand/config/allegro_hand/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/inhand/config/allegro_hand/__init__.py index e1d162515d..a2e97ec29b 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/inhand/config/allegro_hand/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/inhand/config/allegro_hand/__init__.py @@ -5,12 +5,14 @@ import gymnasium as gym -from . import agents, allegro_env_cfg +from . import agents ## # Register Gym environments. ## +task_entry = "omni.isaac.lab_tasks.manager_based.manipulation.inhand.config.allegro_hand" + ## # Full kinematic state observations. ## @@ -20,7 +22,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": allegro_env_cfg.AllegroCubeEnvCfg, + "env_cfg_entry_point": f"{task_entry}.allegro_env_cfg:AllegroCubeEnvCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:AllegroCubePPORunnerCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_cfg.yaml", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_ppo_cfg.yaml", @@ -32,7 +34,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": allegro_env_cfg.AllegroCubeEnvCfg_PLAY, + "env_cfg_entry_point": f"{task_entry}.allegro_env_cfg:AllegroCubeEnvCfg_PLAY", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:AllegroCubePPORunnerCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_cfg.yaml", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_ppo_cfg.yaml", @@ -48,7 +50,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": allegro_env_cfg.AllegroCubeNoVelObsEnvCfg, + "env_cfg_entry_point": f"{task_entry}.allegro_env_cfg:AllegroCubeNoVelObsEnvCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:AllegroCubeNoVelObsPPORunnerCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_cfg.yaml", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_ppo_cfg.yaml", @@ -60,7 +62,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": allegro_env_cfg.AllegroCubeNoVelObsEnvCfg_PLAY, + "env_cfg_entry_point": f"{task_entry}.allegro_env_cfg:AllegroCubeNoVelObsEnvCfg_PLAY", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:AllegroCubeNoVelObsPPORunnerCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_cfg.yaml", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_ppo_cfg.yaml", diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/lift/config/franka/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/lift/config/franka/__init__.py index 651d84ed63..533d5fd5e8 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/lift/config/franka/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/lift/config/franka/__init__.py @@ -5,12 +5,14 @@ import gymnasium as gym import os -from . import agents, ik_abs_env_cfg, ik_rel_env_cfg, joint_pos_env_cfg +from . import agents ## # Register Gym environments. ## +task_entry = "omni.isaac.lab_tasks.manager_based.manipulation.lift.config.franka" + ## # Joint Position Control ## @@ -19,7 +21,7 @@ id="Isaac-Lift-Cube-Franka-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", kwargs={ - "env_cfg_entry_point": joint_pos_env_cfg.FrankaCubeLiftEnvCfg, + "env_cfg_entry_point": f"{task_entry}.joint_pos_env_cfg:FrankaCubeLiftEnvCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:LiftCubePPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_ppo_cfg.yaml", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_cfg.yaml", @@ -32,7 +34,7 @@ id="Isaac-Lift-Cube-Franka-Play-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", kwargs={ - "env_cfg_entry_point": joint_pos_env_cfg.FrankaCubeLiftEnvCfg_PLAY, + "env_cfg_entry_point": f"{task_entry}.joint_pos_env_cfg:FrankaCubeLiftEnvCfg_PLAY", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:LiftCubePPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_ppo_cfg.yaml", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_cfg.yaml", @@ -49,7 +51,7 @@ id="Isaac-Lift-Cube-Franka-IK-Abs-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", kwargs={ - "env_cfg_entry_point": ik_abs_env_cfg.FrankaCubeLiftEnvCfg, + "env_cfg_entry_point": f"{task_entry}.ik_abs_env_cfg:FrankaCubeLiftEnvCfg", }, disable_env_checker=True, ) @@ -58,7 +60,7 @@ id="Isaac-Lift-Teddy-Bear-Franka-IK-Abs-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", kwargs={ - "env_cfg_entry_point": ik_abs_env_cfg.FrankaTeddyBearLiftEnvCfg, + "env_cfg_entry_point": f"{task_entry}.ik_abs_env_cfg:FrankaTeddyBearLiftEnvCfg", }, disable_env_checker=True, ) @@ -71,7 +73,7 @@ id="Isaac-Lift-Cube-Franka-IK-Rel-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", kwargs={ - "env_cfg_entry_point": ik_rel_env_cfg.FrankaCubeLiftEnvCfg, + "env_cfg_entry_point": f"{task_entry}.ik_rel_env_cfg:FrankaCubeLiftEnvCfg", "robomimic_bc_cfg_entry_point": os.path.join(agents.__path__[0], "robomimic/bc.json"), }, disable_env_checker=True, diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/reach/config/franka/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/reach/config/franka/__init__.py index 66146302b2..9bfd737a90 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/reach/config/franka/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/reach/config/franka/__init__.py @@ -5,12 +5,14 @@ import gymnasium as gym -from . import agents, ik_abs_env_cfg, ik_rel_env_cfg, joint_pos_env_cfg +from . import agents ## # Register Gym environments. ## +task_entry = "omni.isaac.lab_tasks.manager_based.manipulation.reach.config.franka" + ## # Joint Position Control ## @@ -20,7 +22,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": joint_pos_env_cfg.FrankaReachEnvCfg, + "env_cfg_entry_point": f"{task_entry}.joint_pos_env_cfg:FrankaReachEnvCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_cfg.yaml", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:FrankaReachPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_ppo_cfg.yaml", @@ -32,7 +34,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": joint_pos_env_cfg.FrankaReachEnvCfg_PLAY, + "env_cfg_entry_point": f"{task_entry}.joint_pos_env_cfg:FrankaReachEnvCfg_PLAY", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_cfg.yaml", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:FrankaReachPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_ppo_cfg.yaml", @@ -48,7 +50,7 @@ id="Isaac-Reach-Franka-IK-Abs-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", kwargs={ - "env_cfg_entry_point": ik_abs_env_cfg.FrankaReachEnvCfg, + "env_cfg_entry_point": f"{task_entry}.ik_abs_env_cfg:FrankaReachEnvCfg", }, disable_env_checker=True, ) @@ -61,7 +63,7 @@ id="Isaac-Reach-Franka-IK-Rel-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", kwargs={ - "env_cfg_entry_point": ik_rel_env_cfg.FrankaReachEnvCfg, + "env_cfg_entry_point": f"{task_entry}.ik_rel_env_cfg:FrankaReachEnvCfg", }, disable_env_checker=True, ) diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/reach/config/ur_10/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/reach/config/ur_10/__init__.py index ca788c59d9..1c1fc72621 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/reach/config/ur_10/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/reach/config/ur_10/__init__.py @@ -5,18 +5,20 @@ import gymnasium as gym -from . import agents, joint_pos_env_cfg +from . import agents ## # Register Gym environments. ## +task_entry = "omni.isaac.lab_tasks.manager_based.manipulation.reach.config.ur_10" + gym.register( id="Isaac-Reach-UR10-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": joint_pos_env_cfg.UR10ReachEnvCfg, + "env_cfg_entry_point": f"{task_entry}.joint_pos_env_cfg:UR10ReachEnvCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_cfg.yaml", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:UR10ReachPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_ppo_cfg.yaml", @@ -28,7 +30,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": joint_pos_env_cfg.UR10ReachEnvCfg_PLAY, + "env_cfg_entry_point": f"{task_entry}.joint_pos_env_cfg:UR10ReachEnvCfg_PLAY", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_cfg.yaml", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:UR10ReachPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_ppo_cfg.yaml", diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/navigation/config/anymal_c/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/navigation/config/anymal_c/__init__.py index 74ef1ccace..6911bea515 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/navigation/config/anymal_c/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/navigation/config/anymal_c/__init__.py @@ -5,18 +5,20 @@ import gymnasium as gym -from . import agents, navigation_env_cfg +from . import agents ## # Register Gym environments. ## +task_entry = "omni.isaac.lab_tasks.manager_based.navigation.config.anymal_c" + gym.register( id="Isaac-Navigation-Flat-Anymal-C-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": navigation_env_cfg.NavigationEnvCfg, + "env_cfg_entry_point": f"{task_entry}.navigation_env_cfg:NavigationEnvCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:NavigationEnvPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_flat_ppo_cfg.yaml", }, @@ -27,7 +29,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": navigation_env_cfg.NavigationEnvCfg_PLAY, + "env_cfg_entry_point": f"{task_entry}.navigation_env_cfg:NavigationEnvCfg_PLAY", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:NavigationEnvPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_flat_ppo_cfg.yaml", }, From 10e7beca2fe8878403c24566b214ffe6945605de Mon Sep 17 00:00:00 2001 From: David Hoeller Date: Mon, 4 Nov 2024 19:22:09 +0100 Subject: [PATCH 057/111] Fixes the default value for the fix base attribute in urdf converter config (#1367) # Description Fixes the default value for the fix base attribute in urdf converter config Fixes #1339 ## Type of change - Bug fix (non-breaking change which fixes an issue) ## Checklist - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [ ] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [ ] I have added tests that prove my fix is effective or that my feature works - [ ] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [x] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --------- Co-authored-by: Kelly Guo --- .../omni/isaac/lab/sim/converters/asset_converter_base.py | 2 ++ .../omni/isaac/lab/sim/converters/urdf_converter_cfg.py | 2 +- 2 files changed, 3 insertions(+), 1 deletion(-) diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/converters/asset_converter_base.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/converters/asset_converter_base.py index 34523f5396..8da8ca2f80 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/converters/asset_converter_base.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/converters/asset_converter_base.py @@ -54,6 +54,8 @@ def __init__(self, cfg: AssetConverterBaseCfg): Raises: ValueError: When provided asset file does not exist. """ + # check that the config is valid + cfg.validate() # check if the asset file exists if not check_file_path(cfg.asset_path): raise ValueError(f"The asset path does not exist: {cfg.asset_path}") diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/converters/urdf_converter_cfg.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/converters/urdf_converter_cfg.py index 06e13b3d01..1c7ebb855a 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/converters/urdf_converter_cfg.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/converters/urdf_converter_cfg.py @@ -30,7 +30,7 @@ class UrdfConverterCfg(AssetConverterBaseCfg): """Decompose a convex mesh into smaller pieces for a closer fit. Defaults to False.""" fix_base: bool = MISSING - """Create a fix joint to the root/base link. Defaults to True.""" + """Create a fix joint to the root/base link.""" merge_fixed_joints: bool = False """Consolidate links that are connected by fixed joints. Defaults to False.""" From c3372f10ecd700a72be92efe4fce5134cb1717ee Mon Sep 17 00:00:00 2001 From: Pascal Roth <57946385+pascal-roth@users.noreply.github.com> Date: Mon, 4 Nov 2024 19:39:05 +0100 Subject: [PATCH 058/111] Adds option to scale/translate/rotate meshes in the `mesh_converter` (#1228) # Description Meshes can be generated with Y up-axis and in cm format. Currently, these meshes would not be rotated or scaled when loading in our stage, which is Z up and m scale. This PR allows scaling and rotating meshes during the mesh converter process. ## Type of change - Bug fix (non-breaking change which fixes an issue) ## Checklist - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [ ] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [x] I have added tests that prove my fix is effective or that my feature works - [x] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [x] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --- .../omni.isaac.lab/config/extension.toml | 2 +- .../omni.isaac.lab/docs/CHANGELOG.rst | 11 ++ .../lab/sim/converters/mesh_converter.py | 105 +++++++++--------- .../lab/sim/converters/mesh_converter_cfg.py | 15 ++- .../test/sim/test_mesh_converter.py | 49 +++++++- 5 files changed, 125 insertions(+), 57 deletions(-) diff --git a/source/extensions/omni.isaac.lab/config/extension.toml b/source/extensions/omni.isaac.lab/config/extension.toml index fc52aa2a47..8fb3c29740 100644 --- a/source/extensions/omni.isaac.lab/config/extension.toml +++ b/source/extensions/omni.isaac.lab/config/extension.toml @@ -1,7 +1,7 @@ [package] # Note: Semantic Versioning is used: https://semver.org/ -version = "0.27.12" +version = "0.27.13" # Description title = "Isaac Lab framework for Robot Learning" diff --git a/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst b/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst index b37e90bd7e..5faefa60fc 100644 --- a/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst +++ b/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst @@ -1,6 +1,17 @@ Changelog --------- +0.27.13 (2024-10-30) +~~~~~~~~~~~~~~~~~~~~ + +Added +^^^^^ + +* Added the attributes :attr:`~omni.isaac.lab.sim.converters.MeshConverterCfg.translation`, :attr:`~omni.isaac.lab.sim.converters.MeshConverterCfg.rotation`, + :attr:`~omni.isaac.lab.sim.converters.MeshConverterCfg.scale` to translate, rotate, and scale meshes + when importing them with :class:`~omni.isaac.lab.sim.converters.MeshConverter`. + + 0.27.12 (2024-01-04) ~~~~~~~~~~~~~~~~~~~ diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/converters/mesh_converter.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/converters/mesh_converter.py index 3ed91a1256..ecaaa4098b 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/converters/mesh_converter.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/converters/mesh_converter.py @@ -10,7 +10,7 @@ import omni.kit.commands import omni.usd from omni.isaac.core.utils.extensions import enable_extension -from pxr import Tf, Usd, UsdGeom, UsdPhysics, UsdUtils +from pxr import Gf, Tf, Usd, UsdGeom, UsdPhysics, UsdUtils from omni.isaac.lab.sim.converters.asset_converter_base import AssetConverterBase from omni.isaac.lab.sim.converters.mesh_converter_cfg import MeshConverterCfg @@ -64,12 +64,13 @@ def __init__(self, cfg: MeshConverterCfg): def _convert_asset(self, cfg: MeshConverterCfg): """Generate USD from OBJ, STL or FBX. - It stores the asset in the following format: + The USD file has Y-up axis and is scaled to meters. + The asset hierarchy is arranged as follows: - /file_name (default prim) - |- /geometry <- Made instanceable if requested - |- /Looks - |- /mesh + .. code-block:: none + mesh_file_basename (default prim) + |- /geometry/Looks + |- /geometry/mesh Args: cfg: The configuration for conversion of mesh to USD. @@ -93,15 +94,25 @@ def _convert_asset(self, cfg: MeshConverterCfg): # Convert USD asyncio.get_event_loop().run_until_complete( - self._convert_mesh_to_usd( - in_file=cfg.asset_path, out_file=self.usd_path, prim_path=f"/{mesh_file_basename}" - ) + self._convert_mesh_to_usd(in_file=cfg.asset_path, out_file=self.usd_path) ) + # Create a new stage, set Z up and meters per unit + temp_stage = Usd.Stage.CreateInMemory() + UsdGeom.SetStageUpAxis(temp_stage, UsdGeom.Tokens.z) + UsdGeom.SetStageMetersPerUnit(temp_stage, 1.0) + UsdPhysics.SetStageKilogramsPerUnit(temp_stage, 1.0) + # Add mesh to stage + base_prim = temp_stage.DefinePrim(f"/{mesh_file_basename}", "Xform") + prim = temp_stage.DefinePrim(f"/{mesh_file_basename}/geometry", "Xform") + prim.GetReferences().AddReference(self.usd_path) + temp_stage.SetDefaultPrim(base_prim) + temp_stage.Export(self.usd_path) + # Open converted USD stage - # note: This opens a new stage and does not use the stage created earlier by the user - # create a new stage stage = Usd.Stage.Open(self.usd_path) - # add USD to stage cache + # Need to reload the stage to get the new prim structure, otherwise it can be taken from the cache + stage.Reload() + # Add USD to stage cache stage_id = UsdUtils.StageCache.Get().Insert(stage) # Get the default prim (which is the root prim) -- "/{mesh_file_basename}" xform_prim = stage.GetDefaultPrim() @@ -121,6 +132,32 @@ def _convert_asset(self, cfg: MeshConverterCfg): ) # Delete the old Xform and make the new Xform the default prim stage.SetDefaultPrim(xform_prim) + # Apply default Xform rotation to mesh -> enable to set rotation and scale + omni.kit.commands.execute( + "CreateDefaultXformOnPrimCommand", + prim_path=xform_prim.GetPath(), + **{"stage": stage}, + ) + + # Apply translation, rotation, and scale to the Xform + geom_xform = UsdGeom.Xform(geom_prim) + geom_xform.ClearXformOpOrder() + + # Remove any existing rotation attributes + rotate_attr = geom_prim.GetAttribute("xformOp:rotateXYZ") + if rotate_attr: + geom_prim.RemoveProperty(rotate_attr.GetName()) + + # translation + translate_op = geom_xform.AddTranslateOp(UsdGeom.XformOp.PrecisionDouble) + translate_op.Set(Gf.Vec3d(*cfg.translation)) + # rotation + orient_op = geom_xform.AddOrientOp(UsdGeom.XformOp.PrecisionDouble) + orient_op.Set(Gf.Quatd(*cfg.rotation)) + # scale + scale_op = geom_xform.AddScaleOp(UsdGeom.XformOp.PrecisionDouble) + scale_op.Set(Gf.Vec3d(*cfg.scale)) + # Handle instanceable # Create a new Xform prim that will be the prototype prim if cfg.make_instanceable: @@ -158,28 +195,18 @@ def _convert_asset(self, cfg: MeshConverterCfg): """ @staticmethod - async def _convert_mesh_to_usd( - in_file: str, out_file: str, prim_path: str = "/World", load_materials: bool = True - ) -> bool: + async def _convert_mesh_to_usd(in_file: str, out_file: str, load_materials: bool = True) -> bool: """Convert mesh from supported file types to USD. This function uses the Omniverse Asset Converter extension to convert a mesh file to USD. It is an asynchronous function and should be called using `asyncio.get_event_loop().run_until_complete()`. The converted asset is stored in the USD format in the specified output file. - The USD file has Y-up axis and is scaled to meters. - - The asset hierarchy is arranged as follows: - - .. code-block:: none - prim_path (default prim) - |- /geometry/Looks - |- /geometry/mesh + The USD file has Y-up axis and is scaled to cm. Args: in_file: The file to convert. out_file: The path to store the output file. - prim_path: The prim path of the mesh. load_materials: Set to True to enable attaching materials defined in the input file to the generated USD mesh. Defaults to True. @@ -187,11 +214,9 @@ async def _convert_mesh_to_usd( True if the conversion succeeds. """ enable_extension("omni.kit.asset_converter") - enable_extension("omni.usd.metrics.assembler") import omni.kit.asset_converter import omni.usd - from omni.metrics.assembler.core import get_metrics_assembler_interface # Create converter context converter_context = omni.kit.asset_converter.AssetConverterContext() @@ -212,29 +237,9 @@ async def _convert_mesh_to_usd( # Create converter task instance = omni.kit.asset_converter.get_instance() - out_file_non_metric = out_file.replace(".usd", "_non_metric.usd") - task = instance.create_converter_task(in_file, out_file_non_metric, None, converter_context) + task = instance.create_converter_task(in_file, out_file, None, converter_context) # Start conversion task and wait for it to finish - success = True - while True: - success = await task.wait_until_finished() - if not success: - await asyncio.sleep(0.1) - else: - break - - temp_stage = Usd.Stage.CreateInMemory() - UsdGeom.SetStageUpAxis(temp_stage, UsdGeom.Tokens.z) - UsdGeom.SetStageMetersPerUnit(temp_stage, 1.0) - UsdPhysics.SetStageKilogramsPerUnit(temp_stage, 1.0) - - base_prim = temp_stage.DefinePrim(prim_path, "Xform") - prim = temp_stage.DefinePrim(f"{prim_path}/geometry", "Xform") - prim.GetReferences().AddReference(out_file_non_metric) - cache = UsdUtils.StageCache.Get() - cache.Insert(temp_stage) - stage_id = cache.GetId(temp_stage).ToLongInt() - get_metrics_assembler_interface().resolve_stage(stage_id) - temp_stage.SetDefaultPrim(base_prim) - temp_stage.Export(out_file) + success = await task.wait_until_finished() + if not success: + raise RuntimeError(f"Failed to convert {in_file} to USD. Error: {task.get_error_message()}") return success diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/converters/mesh_converter_cfg.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/converters/mesh_converter_cfg.py index 2466048447..92d5a611e2 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/converters/mesh_converter_cfg.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/sim/converters/mesh_converter_cfg.py @@ -12,21 +12,21 @@ class MeshConverterCfg(AssetConverterBaseCfg): """The configuration class for MeshConverter.""" - mass_props: schemas_cfg.MassPropertiesCfg = None + mass_props: schemas_cfg.MassPropertiesCfg | None = None """Mass properties to apply to the USD. Defaults to None. Note: If None, then no mass properties will be added. """ - rigid_props: schemas_cfg.RigidBodyPropertiesCfg = None + rigid_props: schemas_cfg.RigidBodyPropertiesCfg | None = None """Rigid body properties to apply to the USD. Defaults to None. Note: If None, then no rigid body properties will be added. """ - collision_props: schemas_cfg.CollisionPropertiesCfg = None + collision_props: schemas_cfg.CollisionPropertiesCfg | None = None """Collision properties to apply to the USD. Defaults to None. Note: @@ -42,3 +42,12 @@ class MeshConverterCfg(AssetConverterBaseCfg): "none" causes no collision mesh to be added. """ + + translation: tuple[float, float, float] = (0.0, 0.0, 0.0) + """The translation of the mesh to the origin. Defaults to (0.0, 0.0, 0.0).""" + + rotation: tuple[float, float, float, float] = (1.0, 0.0, 0.0, 0.0) + """The rotation of the mesh in quaternion format (w, x, y, z). Defaults to (1.0, 0.0, 0.0, 0.0).""" + + scale: tuple[float, float, float] = (1.0, 1.0, 1.0) + """The scale of the mesh. Defaults to (1.0, 1.0, 1.0).""" diff --git a/source/extensions/omni.isaac.lab/test/sim/test_mesh_converter.py b/source/extensions/omni.isaac.lab/test/sim/test_mesh_converter.py index 4d67db879c..a77e0ad8f0 100644 --- a/source/extensions/omni.isaac.lab/test/sim/test_mesh_converter.py +++ b/source/extensions/omni.isaac.lab/test/sim/test_mesh_converter.py @@ -12,7 +12,9 @@ """Rest everything follows.""" +import math import os +import random import tempfile import unittest @@ -27,6 +29,16 @@ from omni.isaac.lab.utils.assets import ISAACLAB_NUCLEUS_DIR, retrieve_file_path +def random_quaternion(): + # Generate four random numbers for the quaternion + u1, u2, u3 = random.random(), random.random(), random.random() + w = math.sqrt(1 - u1) * math.sin(2 * math.pi * u2) + x = math.sqrt(1 - u1) * math.cos(2 * math.pi * u2) + y = math.sqrt(u1) * math.sin(2 * math.pi * u3) + z = math.sqrt(u1) * math.cos(2 * math.pi * u3) + return (w, x, y, z) + + class TestMeshConverter(unittest.TestCase): """Test fixture for the MeshConverter class.""" @@ -105,7 +117,12 @@ def test_config_change(self): def test_convert_obj(self): """Convert an OBJ file""" - mesh_config = MeshConverterCfg(asset_path=self.assets["obj"]) + mesh_config = MeshConverterCfg( + asset_path=self.assets["obj"], + scale=(random.uniform(0.1, 2.0), random.uniform(0.1, 2.0), random.uniform(0.1, 2.0)), + translation=(random.uniform(-10.0, 10.0), random.uniform(-10.0, 10.0), random.uniform(-10.0, 10.0)), + rotation=random_quaternion(), + ) mesh_converter = MeshConverter(mesh_config) # check that mesh conversion is successful @@ -113,7 +130,12 @@ def test_convert_obj(self): def test_convert_stl(self): """Convert an STL file""" - mesh_config = MeshConverterCfg(asset_path=self.assets["stl"]) + mesh_config = MeshConverterCfg( + asset_path=self.assets["stl"], + scale=(random.uniform(0.1, 2.0), random.uniform(0.1, 2.0), random.uniform(0.1, 2.0)), + translation=(random.uniform(-10.0, 10.0), random.uniform(-10.0, 10.0), random.uniform(-10.0, 10.0)), + rotation=random_quaternion(), + ) mesh_converter = MeshConverter(mesh_config) # check that mesh conversion is successful @@ -121,12 +143,24 @@ def test_convert_stl(self): def test_convert_fbx(self): """Convert an FBX file""" - mesh_config = MeshConverterCfg(asset_path=self.assets["fbx"]) + mesh_config = MeshConverterCfg( + asset_path=self.assets["fbx"], + scale=(random.uniform(0.1, 2.0), random.uniform(0.1, 2.0), random.uniform(0.1, 2.0)), + translation=(random.uniform(-10.0, 10.0), random.uniform(-10.0, 10.0), random.uniform(-10.0, 10.0)), + rotation=random_quaternion(), + ) mesh_converter = MeshConverter(mesh_config) # check that mesh conversion is successful self._check_mesh_conversion(mesh_converter) + def test_convert_default_xform_transforms(self): + """Convert an OBJ file and check that default xform transforms are applied correctly""" + mesh_config = MeshConverterCfg(asset_path=self.assets["obj"]) + mesh_converter = MeshConverter(mesh_config) + # check that mesh conversion is successful + self._check_mesh_conversion(mesh_converter) + def test_collider_no_approximation(self): """Convert an OBJ file using no approximation""" collision_props = schemas_cfg.CollisionPropertiesCfg(collision_enabled=True) @@ -229,6 +263,15 @@ def _check_mesh_conversion(self, mesh_converter: MeshConverter): units = UsdGeom.GetStageMetersPerUnit(stage) self.assertEqual(units, 1.0) + # Check mesh settings + pos = tuple(prim_utils.get_prim_at_path("/World/Object/geometry").GetAttribute("xformOp:translate").Get()) + self.assertEqual(pos, mesh_converter.cfg.translation) + quat = prim_utils.get_prim_at_path("/World/Object/geometry").GetAttribute("xformOp:orient").Get() + quat = (quat.GetReal(), quat.GetImaginary()[0], quat.GetImaginary()[1], quat.GetImaginary()[2]) + self.assertEqual(quat, mesh_converter.cfg.rotation) + scale = tuple(prim_utils.get_prim_at_path("/World/Object/geometry").GetAttribute("xformOp:scale").Get()) + self.assertEqual(scale, mesh_converter.cfg.scale) + def _check_mesh_collider_settings(self, mesh_converter: MeshConverter): # Check prim can be properly spawned prim_path = "/World/Object" From d05c7bbcba04652e98fe408bde8a18513071aa8b Mon Sep 17 00:00:00 2001 From: Mayank Mittal <12863862+Mayankm96@users.noreply.github.com> Date: Tue, 5 Nov 2024 07:37:04 +0100 Subject: [PATCH 059/111] Replaces hardcoded module paths with `__name__` dunder (#1357) # Description A minor change to automate where the config directory is located. ## Motivation If user wants to copy these files to their own project, they shouldn't have to change the paths in the registry. --- .../lab_tasks/direct/allegro_hand/__init__.py | 3 +- .../isaac/lab_tasks/direct/ant/__init__.py | 6 +- .../lab_tasks/direct/anymal_c/__init__.py | 10 +- .../lab_tasks/direct/anymal_c/anymal_c_env.py | 146 +---------------- .../direct/anymal_c/anymal_c_env_cfg.py | 149 ++++++++++++++++++ .../direct/cart_double_pendulum/__init__.py | 6 +- .../lab_tasks/direct/cartpole/__init__.py | 14 +- .../direct/franka_cabinet/__init__.py | 6 +- .../lab_tasks/direct/humanoid/__init__.py | 6 +- .../direct/inhand_manipulation/__init__.py | 2 - .../inhand_manipulation_env.py | 4 +- .../lab_tasks/direct/quadcopter/__init__.py | 6 +- .../lab_tasks/direct/shadow_hand/__init__.py | 15 +- .../direct/shadow_hand_over/__init__.py | 6 +- .../manager_based/classic/ant/__init__.py | 4 +- .../classic/cartpole/__init__.py | 12 +- .../classic/humanoid/__init__.py | 4 +- .../locomotion/velocity/config/a1/__init__.py | 10 +- .../velocity/config/anymal_b/__init__.py | 10 +- .../velocity/config/anymal_c/__init__.py | 10 +- .../velocity/config/anymal_d/__init__.py | 10 +- .../velocity/config/cassie/__init__.py | 10 +- .../locomotion/velocity/config/g1/__init__.py | 11 +- .../velocity/config/go1/__init__.py | 10 +- .../velocity/config/go2/__init__.py | 10 +- .../locomotion/velocity/config/h1/__init__.py | 11 +- .../velocity/config/spot/__init__.py | 6 +- .../cabinet/config/franka/__init__.py | 10 +- .../inhand/config/allegro_hand/__init__.py | 10 +- .../lift/config/franka/__init__.py | 12 +- .../reach/config/franka/__init__.py | 10 +- .../reach/config/ur_10/__init__.py | 6 +- .../navigation/config/anymal_c/__init__.py | 6 +- 33 files changed, 251 insertions(+), 300 deletions(-) create mode 100644 source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/anymal_c/anymal_c_env_cfg.py diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/allegro_hand/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/allegro_hand/__init__.py index b851a255cf..b0734779f5 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/allegro_hand/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/allegro_hand/__init__.py @@ -15,7 +15,6 @@ # Register Gym environments. ## -task_entry = "omni.isaac.lab_tasks.direct.allegro_hand" inhand_task_entry = "omni.isaac.lab_tasks.direct.inhand_manipulation" gym.register( @@ -23,7 +22,7 @@ entry_point=f"{inhand_task_entry}.inhand_manipulation_env:InHandManipulationEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.allegro_hand_env_cfg:AllegroHandEnvCfg", + "env_cfg_entry_point": f"{__name__}.allegro_hand_env_cfg:AllegroHandEnvCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_cfg.yaml", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:AllegroHandPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_ppo_cfg.yaml", diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/ant/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/ant/__init__.py index 9d5deb0546..940702a105 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/ant/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/ant/__init__.py @@ -15,14 +15,12 @@ # Register Gym environments. ## -task_entry = "omni.isaac.lab_tasks.direct.ant" - gym.register( id="Isaac-Ant-Direct-v0", - entry_point=f"{task_entry}.ant_env:AntEnv", + entry_point=f"{__name__}.ant_env:AntEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.ant_env:AntEnvCfg", + "env_cfg_entry_point": f"{__name__}.ant_env:AntEnvCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_cfg.yaml", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:AntPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_ppo_cfg.yaml", diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/anymal_c/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/anymal_c/__init__.py index d217a90998..8160e044d9 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/anymal_c/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/anymal_c/__init__.py @@ -15,14 +15,12 @@ # Register Gym environments. ## -task_entry = "omni.isaac.lab_tasks.direct.anymal_c" - gym.register( id="Isaac-Velocity-Flat-Anymal-C-Direct-v0", - entry_point=f"{task_entry}.anymal_c_env:AnymalCEnv", + entry_point=f"{__name__}.anymal_c_env:AnymalCEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.anymal_c_env:AnymalCFlatEnvCfg", + "env_cfg_entry_point": f"{__name__}.anymal_c_env_cfg:AnymalCFlatEnvCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_flat_ppo_cfg.yaml", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:AnymalCFlatPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_flat_ppo_cfg.yaml", @@ -31,10 +29,10 @@ gym.register( id="Isaac-Velocity-Rough-Anymal-C-Direct-v0", - entry_point=f"{task_entry}.anymal_c_env:AnymalCEnv", + entry_point=f"{__name__}.anymal_c_env:AnymalCEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.anymal_c_env:AnymalCRoughEnvCfg", + "env_cfg_entry_point": f"{__name__}.anymal_c_env_cfg:AnymalCRoughEnvCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_rough_ppo_cfg.yaml", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:AnymalCRoughPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_rough_ppo_cfg.yaml", diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/anymal_c/anymal_c_env.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/anymal_c/anymal_c_env.py index ca1f61c54a..1b2ee577c7 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/anymal_c/anymal_c_env.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/anymal_c/anymal_c_env.py @@ -8,150 +8,12 @@ import gymnasium as gym import torch -import omni.isaac.lab.envs.mdp as mdp import omni.isaac.lab.sim as sim_utils -from omni.isaac.lab.assets import Articulation, ArticulationCfg -from omni.isaac.lab.envs import DirectRLEnv, DirectRLEnvCfg -from omni.isaac.lab.managers import EventTermCfg as EventTerm -from omni.isaac.lab.managers import SceneEntityCfg -from omni.isaac.lab.scene import InteractiveSceneCfg -from omni.isaac.lab.sensors import ContactSensor, ContactSensorCfg, RayCaster, RayCasterCfg, patterns -from omni.isaac.lab.sim import SimulationCfg -from omni.isaac.lab.terrains import TerrainImporterCfg -from omni.isaac.lab.utils import configclass +from omni.isaac.lab.assets import Articulation +from omni.isaac.lab.envs import DirectRLEnv +from omni.isaac.lab.sensors import ContactSensor, RayCaster -## -# Pre-defined configs -## -from omni.isaac.lab_assets.anymal import ANYMAL_C_CFG # isort: skip -from omni.isaac.lab.terrains.config.rough import ROUGH_TERRAINS_CFG # isort: skip - - -@configclass -class EventCfg: - """Configuration for randomization.""" - - physics_material = EventTerm( - func=mdp.randomize_rigid_body_material, - mode="startup", - params={ - "asset_cfg": SceneEntityCfg("robot", body_names=".*"), - "static_friction_range": (0.8, 0.8), - "dynamic_friction_range": (0.6, 0.6), - "restitution_range": (0.0, 0.0), - "num_buckets": 64, - }, - ) - - add_base_mass = EventTerm( - func=mdp.randomize_rigid_body_mass, - mode="startup", - params={ - "asset_cfg": SceneEntityCfg("robot", body_names="base"), - "mass_distribution_params": (-5.0, 5.0), - "operation": "add", - }, - ) - - -@configclass -class AnymalCFlatEnvCfg(DirectRLEnvCfg): - # env - episode_length_s = 20.0 - decimation = 4 - action_scale = 0.5 - action_space = 12 - observation_space = 48 - state_space = 0 - - # simulation - sim: SimulationCfg = SimulationCfg( - dt=1 / 200, - render_interval=decimation, - disable_contact_processing=True, - physics_material=sim_utils.RigidBodyMaterialCfg( - friction_combine_mode="multiply", - restitution_combine_mode="multiply", - static_friction=1.0, - dynamic_friction=1.0, - restitution=0.0, - ), - ) - terrain = TerrainImporterCfg( - prim_path="/World/ground", - terrain_type="plane", - collision_group=-1, - physics_material=sim_utils.RigidBodyMaterialCfg( - friction_combine_mode="multiply", - restitution_combine_mode="multiply", - static_friction=1.0, - dynamic_friction=1.0, - restitution=0.0, - ), - debug_vis=False, - ) - - # scene - scene: InteractiveSceneCfg = InteractiveSceneCfg(num_envs=4096, env_spacing=4.0, replicate_physics=True) - - # events - events: EventCfg = EventCfg() - - # robot - robot: ArticulationCfg = ANYMAL_C_CFG.replace(prim_path="/World/envs/env_.*/Robot") - contact_sensor: ContactSensorCfg = ContactSensorCfg( - prim_path="/World/envs/env_.*/Robot/.*", history_length=3, update_period=0.005, track_air_time=True - ) - - # reward scales - lin_vel_reward_scale = 1.0 - yaw_rate_reward_scale = 0.5 - z_vel_reward_scale = -2.0 - ang_vel_reward_scale = -0.05 - joint_torque_reward_scale = -2.5e-5 - joint_accel_reward_scale = -2.5e-7 - action_rate_reward_scale = -0.01 - feet_air_time_reward_scale = 0.5 - undersired_contact_reward_scale = -1.0 - flat_orientation_reward_scale = -5.0 - - -@configclass -class AnymalCRoughEnvCfg(AnymalCFlatEnvCfg): - # env - observation_space = 235 - - terrain = TerrainImporterCfg( - prim_path="/World/ground", - terrain_type="generator", - terrain_generator=ROUGH_TERRAINS_CFG, - max_init_terrain_level=9, - collision_group=-1, - physics_material=sim_utils.RigidBodyMaterialCfg( - friction_combine_mode="multiply", - restitution_combine_mode="multiply", - static_friction=1.0, - dynamic_friction=1.0, - ), - visual_material=sim_utils.MdlFileCfg( - mdl_path="{NVIDIA_NUCLEUS_DIR}/Materials/Base/Architecture/Shingles_01.mdl", - project_uvw=True, - ), - debug_vis=False, - ) - - # we add a height scanner for perceptive locomotion - height_scanner = RayCasterCfg( - prim_path="/World/envs/env_.*/Robot/base", - offset=RayCasterCfg.OffsetCfg(pos=(0.0, 0.0, 20.0)), - attach_yaw_only=True, - pattern_cfg=patterns.GridPatternCfg(resolution=0.1, size=[1.6, 1.0]), - debug_vis=False, - mesh_prim_paths=["/World/ground"], - ) - - # reward scales (override from flat config) - flat_orientation_reward_scale = 0.0 +from .anymal_c_env_cfg import AnymalCFlatEnvCfg, AnymalCRoughEnvCfg class AnymalCEnv(DirectRLEnv): diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/anymal_c/anymal_c_env_cfg.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/anymal_c/anymal_c_env_cfg.py new file mode 100644 index 0000000000..d5276f1404 --- /dev/null +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/anymal_c/anymal_c_env_cfg.py @@ -0,0 +1,149 @@ +# Copyright (c) 2022-2024, The Isaac Lab Project Developers. +# All rights reserved. +# +# SPDX-License-Identifier: BSD-3-Clause + +import omni.isaac.lab.envs.mdp as mdp +import omni.isaac.lab.sim as sim_utils +from omni.isaac.lab.assets import ArticulationCfg +from omni.isaac.lab.envs import DirectRLEnvCfg +from omni.isaac.lab.managers import EventTermCfg as EventTerm +from omni.isaac.lab.managers import SceneEntityCfg +from omni.isaac.lab.scene import InteractiveSceneCfg +from omni.isaac.lab.sensors import ContactSensorCfg, RayCasterCfg, patterns +from omni.isaac.lab.sim import SimulationCfg +from omni.isaac.lab.terrains import TerrainImporterCfg +from omni.isaac.lab.utils import configclass + +## +# Pre-defined configs +## +from omni.isaac.lab_assets.anymal import ANYMAL_C_CFG # isort: skip +from omni.isaac.lab.terrains.config.rough import ROUGH_TERRAINS_CFG # isort: skip + + +@configclass +class EventCfg: + """Configuration for randomization.""" + + physics_material = EventTerm( + func=mdp.randomize_rigid_body_material, + mode="startup", + params={ + "asset_cfg": SceneEntityCfg("robot", body_names=".*"), + "static_friction_range": (0.8, 0.8), + "dynamic_friction_range": (0.6, 0.6), + "restitution_range": (0.0, 0.0), + "num_buckets": 64, + }, + ) + + add_base_mass = EventTerm( + func=mdp.randomize_rigid_body_mass, + mode="startup", + params={ + "asset_cfg": SceneEntityCfg("robot", body_names="base"), + "mass_distribution_params": (-5.0, 5.0), + "operation": "add", + }, + ) + + +@configclass +class AnymalCFlatEnvCfg(DirectRLEnvCfg): + # env + episode_length_s = 20.0 + decimation = 4 + action_scale = 0.5 + action_space = 12 + observation_space = 48 + state_space = 0 + + # simulation + sim: SimulationCfg = SimulationCfg( + dt=1 / 200, + render_interval=decimation, + disable_contact_processing=True, + physics_material=sim_utils.RigidBodyMaterialCfg( + friction_combine_mode="multiply", + restitution_combine_mode="multiply", + static_friction=1.0, + dynamic_friction=1.0, + restitution=0.0, + ), + ) + terrain = TerrainImporterCfg( + prim_path="/World/ground", + terrain_type="plane", + collision_group=-1, + physics_material=sim_utils.RigidBodyMaterialCfg( + friction_combine_mode="multiply", + restitution_combine_mode="multiply", + static_friction=1.0, + dynamic_friction=1.0, + restitution=0.0, + ), + debug_vis=False, + ) + + # scene + scene: InteractiveSceneCfg = InteractiveSceneCfg(num_envs=4096, env_spacing=4.0, replicate_physics=True) + + # events + events: EventCfg = EventCfg() + + # robot + robot: ArticulationCfg = ANYMAL_C_CFG.replace(prim_path="/World/envs/env_.*/Robot") + contact_sensor: ContactSensorCfg = ContactSensorCfg( + prim_path="/World/envs/env_.*/Robot/.*", history_length=3, update_period=0.005, track_air_time=True + ) + + # reward scales + lin_vel_reward_scale = 1.0 + yaw_rate_reward_scale = 0.5 + z_vel_reward_scale = -2.0 + ang_vel_reward_scale = -0.05 + joint_torque_reward_scale = -2.5e-5 + joint_accel_reward_scale = -2.5e-7 + action_rate_reward_scale = -0.01 + feet_air_time_reward_scale = 0.5 + undersired_contact_reward_scale = -1.0 + flat_orientation_reward_scale = -5.0 + + +@configclass +class AnymalCRoughEnvCfg(AnymalCFlatEnvCfg): + # env + observation_space = 235 + + terrain = TerrainImporterCfg( + prim_path="/World/ground", + terrain_type="generator", + terrain_generator=ROUGH_TERRAINS_CFG, + max_init_terrain_level=9, + collision_group=-1, + physics_material=sim_utils.RigidBodyMaterialCfg( + friction_combine_mode="multiply", + restitution_combine_mode="multiply", + static_friction=1.0, + dynamic_friction=1.0, + ), + visual_material=sim_utils.MdlFileCfg( + mdl_path="{NVIDIA_NUCLEUS_DIR}/Materials/Base/Architecture/Shingles_01.mdl", + project_uvw=True, + ), + debug_vis=False, + ) + + # we add a height scanner for perceptive locomotion + height_scanner = RayCasterCfg( + prim_path="/World/envs/env_.*/Robot/base", + offset=RayCasterCfg.OffsetCfg(pos=(0.0, 0.0, 20.0)), + attach_yaw_only=True, + pattern_cfg=patterns.GridPatternCfg(resolution=0.1, size=[1.6, 1.0]), + debug_vis=False, + mesh_prim_paths=["/World/ground"], + ) + + # reward scales (override from flat config) + flat_orientation_reward_scale = 0.0 diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/cart_double_pendulum/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/cart_double_pendulum/__init__.py index e09b1658e1..90d70311d1 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/cart_double_pendulum/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/cart_double_pendulum/__init__.py @@ -15,14 +15,12 @@ # Register Gym environments. ## -task_entry = "omni.isaac.lab_tasks.direct.cart_double_pendulum" - gym.register( id="Isaac-Cart-Double-Pendulum-Direct-v0", - entry_point=f"{task_entry}.cart_double_pendulum_env:CartDoublePendulumEnv", + entry_point=f"{__name__}.cart_double_pendulum_env:CartDoublePendulumEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.cart_double_pendulum_env:CartDoublePendulumEnvCfg", + "env_cfg_entry_point": f"{__name__}.cart_double_pendulum_env:CartDoublePendulumEnvCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_cfg.yaml", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_ppo_cfg.yaml", "skrl_ippo_cfg_entry_point": f"{agents.__name__}:skrl_ippo_cfg.yaml", diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/cartpole/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/cartpole/__init__.py index 64b24850eb..035cf7a7a9 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/cartpole/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/cartpole/__init__.py @@ -15,14 +15,12 @@ # Register Gym environments. ## -task_entry = "omni.isaac.lab_tasks.direct.cartpole" - gym.register( id="Isaac-Cartpole-Direct-v0", - entry_point=f"{task_entry}.cartpole_env:CartpoleEnv", + entry_point=f"{__name__}.cartpole_env:CartpoleEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.cartpole_env:CartpoleEnvCfg", + "env_cfg_entry_point": f"{__name__}.cartpole_env:CartpoleEnvCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_cfg.yaml", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:CartpolePPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_ppo_cfg.yaml", @@ -32,10 +30,10 @@ gym.register( id="Isaac-Cartpole-RGB-Camera-Direct-v0", - entry_point=f"{task_entry}.cartpole_camera_env:CartpoleCameraEnv", + entry_point=f"{__name__}.cartpole_camera_env:CartpoleCameraEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.cartpole_camera_env:CartpoleRGBCameraEnvCfg", + "env_cfg_entry_point": f"{__name__}.cartpole_camera_env:CartpoleRGBCameraEnvCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_camera_ppo_cfg.yaml", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_camera_ppo_cfg.yaml", }, @@ -43,10 +41,10 @@ gym.register( id="Isaac-Cartpole-Depth-Camera-Direct-v0", - entry_point=f"{task_entry}.cartpole_camera_env:CartpoleCameraEnv", + entry_point=f"{__name__}.cartpole_camera_env:CartpoleCameraEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.cartpole_camera_env:CartpoleDepthCameraEnvCfg", + "env_cfg_entry_point": f"{__name__}.cartpole_camera_env:CartpoleDepthCameraEnvCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_camera_ppo_cfg.yaml", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_camera_ppo_cfg.yaml", }, diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/franka_cabinet/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/franka_cabinet/__init__.py index 14df4e20df..f91915d3ed 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/franka_cabinet/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/franka_cabinet/__init__.py @@ -14,14 +14,12 @@ # Register Gym environments. ## -task_entry = "omni.isaac.lab_tasks.direct.franka_cabinet" - gym.register( id="Isaac-Franka-Cabinet-Direct-v0", - entry_point=f"{task_entry}.franka_cabinet_env:FrankaCabinetEnv", + entry_point=f"{__name__}.franka_cabinet_env:FrankaCabinetEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.franka_cabinet_env:FrankaCabinetEnvCfg", + "env_cfg_entry_point": f"{__name__}.franka_cabinet_env:FrankaCabinetEnvCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_cfg.yaml", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:FrankaCabinetPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_ppo_cfg.yaml", diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/humanoid/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/humanoid/__init__.py index 687c5fcf30..9bd3dfec17 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/humanoid/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/humanoid/__init__.py @@ -15,14 +15,12 @@ # Register Gym environments. ## -task_entry = "omni.isaac.lab_tasks.direct.humanoid" - gym.register( id="Isaac-Humanoid-Direct-v0", - entry_point=f"{task_entry}.humanoid_env:HumanoidEnv", + entry_point=f"{__name__}.humanoid_env:HumanoidEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.humanoid_env:HumanoidEnvCfg", + "env_cfg_entry_point": f"{__name__}.humanoid_env:HumanoidEnvCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_cfg.yaml", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:HumanoidPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_ppo_cfg.yaml", diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/inhand_manipulation/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/inhand_manipulation/__init__.py index cdce057355..c3ee657052 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/inhand_manipulation/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/inhand_manipulation/__init__.py @@ -2,5 +2,3 @@ # All rights reserved. # # SPDX-License-Identifier: BSD-3-Clause - -from .inhand_manipulation_env import InHandManipulationEnv diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/inhand_manipulation/inhand_manipulation_env.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/inhand_manipulation/inhand_manipulation_env.py index 7ab34f4763..dd671d2ab9 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/inhand_manipulation/inhand_manipulation_env.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/inhand_manipulation/inhand_manipulation_env.py @@ -19,8 +19,8 @@ from omni.isaac.lab.utils.math import quat_conjugate, quat_from_angle_axis, quat_mul, sample_uniform, saturate if TYPE_CHECKING: - from omni.isaac.lab_tasks.direct.allegro_hand import AllegroHandEnvCfg - from omni.isaac.lab_tasks.direct.shadow_hand import ShadowHandEnvCfg + from omni.isaac.lab_tasks.direct.allegro_hand.allegro_hand_env_cfg import AllegroHandEnvCfg + from omni.isaac.lab_tasks.direct.shadow_hand.shadow_hand_env_cfg import ShadowHandEnvCfg class InHandManipulationEnv(DirectRLEnv): diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/quadcopter/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/quadcopter/__init__.py index 523ca0d9f8..2605b599f0 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/quadcopter/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/quadcopter/__init__.py @@ -15,14 +15,12 @@ # Register Gym environments. ## -task_entry = "omni.isaac.lab_tasks.direct.quadcopter" - gym.register( id="Isaac-Quadcopter-Direct-v0", - entry_point=f"{task_entry}.quadcopter_env:QuadcopterEnv", + entry_point=f"{__name__}.quadcopter_env:QuadcopterEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.quadcopter_env:QuadcopterEnvCfg", + "env_cfg_entry_point": f"{__name__}.quadcopter_env:QuadcopterEnvCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_cfg.yaml", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:QuadcopterPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_ppo_cfg.yaml", diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/shadow_hand/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/shadow_hand/__init__.py index 9f48e206a0..73cdc43270 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/shadow_hand/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/shadow_hand/__init__.py @@ -15,7 +15,6 @@ # Register Gym environments. ## -task_entry = "omni.isaac.lab_tasks.direct.shadow_hand" inhand_task_entry = "omni.isaac.lab_tasks.direct.inhand_manipulation" gym.register( @@ -23,7 +22,7 @@ entry_point=f"{inhand_task_entry}.inhand_manipulation_env:InHandManipulationEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.shadow_hand_env_cfg:ShadowHandEnvCfg", + "env_cfg_entry_point": f"{__name__}.shadow_hand_env_cfg:ShadowHandEnvCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_cfg.yaml", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:ShadowHandPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_ppo_cfg.yaml", @@ -35,7 +34,7 @@ entry_point=f"{inhand_task_entry}.inhand_manipulation_env:InHandManipulationEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.shadow_hand_env_cfg:ShadowHandOpenAIEnvCfg", + "env_cfg_entry_point": f"{__name__}.shadow_hand_env_cfg:ShadowHandOpenAIEnvCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_ff_cfg.yaml", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:ShadowHandAsymFFPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_ff_ppo_cfg.yaml", @@ -47,7 +46,7 @@ entry_point=f"{inhand_task_entry}.inhand_manipulation_env:InHandManipulationEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.shadow_hand_env_cfg:ShadowHandOpenAIEnvCfg", + "env_cfg_entry_point": f"{__name__}.shadow_hand_env_cfg:ShadowHandOpenAIEnvCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_lstm_cfg.yaml", }, ) @@ -56,10 +55,10 @@ gym.register( id="Isaac-Repose-Cube-Shadow-Vision-Direct-v0", - entry_point=f"{task_entry}.shadow_hand_vision_env:ShadowHandVisionEnv", + entry_point=f"{__name__}.shadow_hand_vision_env:ShadowHandVisionEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.shadow_hand_vision_env:ShadowHandVisionEnvCfg", + "env_cfg_entry_point": f"{__name__}.shadow_hand_vision_env:ShadowHandVisionEnvCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:ShadowHandVisionFFPPORunnerCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_vision_cfg.yaml", }, @@ -67,10 +66,10 @@ gym.register( id="Isaac-Repose-Cube-Shadow-Vision-Direct-Play-v0", - entry_point=f"{task_entry}.shadow_hand_vision_env:ShadowHandVisionEnv", + entry_point=f"{__name__}.shadow_hand_vision_env:ShadowHandVisionEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.shadow_hand_vision_env:ShadowHandVisionEnvPlayCfg", + "env_cfg_entry_point": f"{__name__}.shadow_hand_vision_env:ShadowHandVisionEnvPlayCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:ShadowHandVisionFFPPORunnerCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_vision_cfg.yaml", }, diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/shadow_hand_over/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/shadow_hand_over/__init__.py index e226d6dcf4..8eef9dd395 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/shadow_hand_over/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/direct/shadow_hand_over/__init__.py @@ -15,14 +15,12 @@ # Register Gym environments. ## -task_entry = "omni.isaac.lab_tasks.direct.shadow_hand_over" - gym.register( id="Isaac-Shadow-Hand-Over-Direct-v0", - entry_point=f"{task_entry}.shadow_hand_over_env:ShadowHandOverEnv", + entry_point=f"{__name__}.shadow_hand_over_env:ShadowHandOverEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.shadow_hand_over_env_cfg:ShadowHandOverEnvCfg", + "env_cfg_entry_point": f"{__name__}.shadow_hand_over_env_cfg:ShadowHandOverEnvCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_cfg.yaml", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_ppo_cfg.yaml", "skrl_ippo_cfg_entry_point": f"{agents.__name__}:skrl_ippo_cfg.yaml", diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/ant/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/ant/__init__.py index d5e96aa9b3..a128cf5116 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/ant/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/ant/__init__.py @@ -15,14 +15,12 @@ # Register Gym environments. ## -task_entry = "omni.isaac.lab_tasks.manager_based.classic.ant" - gym.register( id="Isaac-Ant-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.ant_env_cfg:AntEnvCfg", + "env_cfg_entry_point": f"{__name__}.ant_env_cfg:AntEnvCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:AntPPORunnerCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_cfg.yaml", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_ppo_cfg.yaml", diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/cartpole/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/cartpole/__init__.py index 264684ee32..3b0107ecb7 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/cartpole/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/cartpole/__init__.py @@ -15,14 +15,12 @@ # Register Gym environments. ## -task_entry = "omni.isaac.lab_tasks.manager_based.classic.cartpole" - gym.register( id="Isaac-Cartpole-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.cartpole_env_cfg:CartpoleEnvCfg", + "env_cfg_entry_point": f"{__name__}.cartpole_env_cfg:CartpoleEnvCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_cfg.yaml", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:CartpolePPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_ppo_cfg.yaml", @@ -35,7 +33,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.cartpole_camera_env_cfg:CartpoleRGBCameraEnvCfg", + "env_cfg_entry_point": f"{__name__}.cartpole_camera_env_cfg:CartpoleRGBCameraEnvCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_camera_ppo_cfg.yaml", }, ) @@ -45,7 +43,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.cartpole_camera_env_cfg:CartpoleDepthCameraEnvCfg", + "env_cfg_entry_point": f"{__name__}.cartpole_camera_env_cfg:CartpoleDepthCameraEnvCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_camera_ppo_cfg.yaml", }, ) @@ -55,7 +53,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.cartpole_camera_env_cfg:CartpoleResNet18CameraEnvCfg", + "env_cfg_entry_point": f"{__name__}.cartpole_camera_env_cfg:CartpoleResNet18CameraEnvCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_feature_ppo_cfg.yaml", }, ) @@ -65,7 +63,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.cartpole_camera_env_cfg:CartpoleTheiaTinyCameraEnvCfg", + "env_cfg_entry_point": f"{__name__}.cartpole_camera_env_cfg:CartpoleTheiaTinyCameraEnvCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_feature_ppo_cfg.yaml", }, ) diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/humanoid/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/humanoid/__init__.py index 1a2084d791..497901f711 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/humanoid/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/classic/humanoid/__init__.py @@ -15,14 +15,12 @@ # Register Gym environments. ## -task_entry = "omni.isaac.lab_tasks.manager_based.classic.humanoid" - gym.register( id="Isaac-Humanoid-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.humanoid_env_cfg:HumanoidEnvCfg", + "env_cfg_entry_point": f"{__name__}.humanoid_env_cfg:HumanoidEnvCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:HumanoidPPORunnerCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_cfg.yaml", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_ppo_cfg.yaml", diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/a1/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/a1/__init__.py index d3ce2ca1fc..fd628c91f5 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/a1/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/a1/__init__.py @@ -11,14 +11,12 @@ # Register Gym environments. ## -task_entry = "omni.isaac.lab_tasks.manager_based.locomotion.velocity.config.a1" - gym.register( id="Isaac-Velocity-Flat-Unitree-A1-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.flat_env_cfg:UnitreeA1FlatEnvCfg", + "env_cfg_entry_point": f"{__name__}.flat_env_cfg:UnitreeA1FlatEnvCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:UnitreeA1FlatPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_flat_ppo_cfg.yaml", }, @@ -29,7 +27,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.flat_env_cfg:UnitreeA1FlatEnvCfg_PLAY", + "env_cfg_entry_point": f"{__name__}.flat_env_cfg:UnitreeA1FlatEnvCfg_PLAY", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:UnitreeA1FlatPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_flat_ppo_cfg.yaml", }, @@ -40,7 +38,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.rough_env_cfg:UnitreeA1RoughEnvCfg", + "env_cfg_entry_point": f"{__name__}.rough_env_cfg:UnitreeA1RoughEnvCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:UnitreeA1RoughPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_rough_ppo_cfg.yaml", }, @@ -51,7 +49,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.rough_env_cfg:UnitreeA1RoughEnvCfg_PLAY", + "env_cfg_entry_point": f"{__name__}.rough_env_cfg:UnitreeA1RoughEnvCfg_PLAY", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:UnitreeA1RoughPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_rough_ppo_cfg.yaml", }, diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/anymal_b/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/anymal_b/__init__.py index 52f1cc55c9..3796c67d81 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/anymal_b/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/anymal_b/__init__.py @@ -10,14 +10,12 @@ # Register Gym environments. ## -task_entry = "omni.isaac.lab_tasks.manager_based.locomotion.velocity.config.anymal_b" - gym.register( id="Isaac-Velocity-Flat-Anymal-B-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.flat_env_cfg:AnymalBFlatEnvCfg", + "env_cfg_entry_point": f"{__name__}.flat_env_cfg:AnymalBFlatEnvCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:AnymalBFlatPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_flat_ppo_cfg.yaml", }, @@ -28,7 +26,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.flat_env_cfg:AnymalBFlatEnvCfg_PLAY", + "env_cfg_entry_point": f"{__name__}.flat_env_cfg:AnymalBFlatEnvCfg_PLAY", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:AnymalBFlatPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_flat_ppo_cfg.yaml", }, @@ -39,7 +37,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.rough_env_cfg:AnymalBRoughEnvCfg", + "env_cfg_entry_point": f"{__name__}.rough_env_cfg:AnymalBRoughEnvCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:AnymalBRoughPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_rough_ppo_cfg.yaml", }, @@ -50,7 +48,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.rough_env_cfg:AnymalBRoughEnvCfg_PLAY", + "env_cfg_entry_point": f"{__name__}.rough_env_cfg:AnymalBRoughEnvCfg_PLAY", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:AnymalBRoughPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_rough_ppo_cfg.yaml", }, diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/anymal_c/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/anymal_c/__init__.py index 020bc3854a..770b52337e 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/anymal_c/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/anymal_c/__init__.py @@ -11,14 +11,12 @@ # Register Gym environments. ## -task_entry = "omni.isaac.lab_tasks.manager_based.locomotion.velocity.config.anymal_c" - gym.register( id="Isaac-Velocity-Flat-Anymal-C-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.flat_env_cfg:AnymalCFlatEnvCfg", + "env_cfg_entry_point": f"{__name__}.flat_env_cfg:AnymalCFlatEnvCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:AnymalCFlatPPORunnerCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_flat_ppo_cfg.yaml", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_flat_ppo_cfg.yaml", @@ -30,7 +28,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.flat_env_cfg:AnymalCFlatEnvCfg_PLAY", + "env_cfg_entry_point": f"{__name__}.flat_env_cfg:AnymalCFlatEnvCfg_PLAY", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_flat_ppo_cfg.yaml", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:AnymalCFlatPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_flat_ppo_cfg.yaml", @@ -42,7 +40,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.rough_env_cfg:AnymalCRoughEnvCfg", + "env_cfg_entry_point": f"{__name__}.rough_env_cfg:AnymalCRoughEnvCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_rough_ppo_cfg.yaml", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:AnymalCRoughPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_rough_ppo_cfg.yaml", @@ -54,7 +52,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.rough_env_cfg:AnymalCRoughEnvCfg_PLAY", + "env_cfg_entry_point": f"{__name__}.rough_env_cfg:AnymalCRoughEnvCfg_PLAY", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_rough_ppo_cfg.yaml", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:AnymalCRoughPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_rough_ppo_cfg.yaml", diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/anymal_d/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/anymal_d/__init__.py index d6054be1a4..eea14799e9 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/anymal_d/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/anymal_d/__init__.py @@ -11,14 +11,12 @@ # Register Gym environments. ## -task_entry = "omni.isaac.lab_tasks.manager_based.locomotion.velocity.config.anymal_d" - gym.register( id="Isaac-Velocity-Flat-Anymal-D-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.flat_env_cfg:AnymalDFlatEnvCfg", + "env_cfg_entry_point": f"{__name__}.flat_env_cfg:AnymalDFlatEnvCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:AnymalDFlatPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_flat_ppo_cfg.yaml", }, @@ -29,7 +27,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.flat_env_cfg:AnymalDFlatEnvCfg_PLAY", + "env_cfg_entry_point": f"{__name__}.flat_env_cfg:AnymalDFlatEnvCfg_PLAY", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:AnymalDFlatPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_flat_ppo_cfg.yaml", }, @@ -40,7 +38,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.rough_env_cfg:AnymalDRoughEnvCfg", + "env_cfg_entry_point": f"{__name__}.rough_env_cfg:AnymalDRoughEnvCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:AnymalDRoughPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_rough_ppo_cfg.yaml", }, @@ -51,7 +49,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.rough_env_cfg:AnymalDRoughEnvCfg_PLAY", + "env_cfg_entry_point": f"{__name__}.rough_env_cfg:AnymalDRoughEnvCfg_PLAY", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:AnymalDRoughPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_rough_ppo_cfg.yaml", }, diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/cassie/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/cassie/__init__.py index 3b37b34b41..69658caf46 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/cassie/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/cassie/__init__.py @@ -11,14 +11,12 @@ # Register Gym environments. ## -task_entry = "omni.isaac.lab_tasks.manager_based.locomotion.velocity.config.cassie" - gym.register( id="Isaac-Velocity-Flat-Cassie-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.flat_env_cfg:CassieFlatEnvCfg", + "env_cfg_entry_point": f"{__name__}.flat_env_cfg:CassieFlatEnvCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:CassieFlatPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_flat_ppo_cfg.yaml", }, @@ -29,7 +27,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.flat_env_cfg:CassieFlatEnvCfg_PLAY", + "env_cfg_entry_point": f"{__name__}.flat_env_cfg:CassieFlatEnvCfg_PLAY", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:CassieFlatPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_flat_ppo_cfg.yaml", }, @@ -40,7 +38,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.rough_env_cfg:CassieRoughEnvCfg", + "env_cfg_entry_point": f"{__name__}.rough_env_cfg:CassieRoughEnvCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:CassieRoughPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_rough_ppo_cfg.yaml", }, @@ -51,7 +49,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.rough_env_cfg:CassieRoughEnvCfg_PLAY", + "env_cfg_entry_point": f"{__name__}.rough_env_cfg:CassieRoughEnvCfg_PLAY", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:CassieRoughPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_rough_ppo_cfg.yaml", }, diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/g1/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/g1/__init__.py index 7c50e5dfb5..316252f77d 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/g1/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/g1/__init__.py @@ -11,15 +11,12 @@ # Register Gym environments. ## -task_entry = "omni.isaac.lab_tasks.manager_based.locomotion.velocity.config.g1" - - gym.register( id="Isaac-Velocity-Rough-G1-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.rough_env_cfg:G1RoughEnvCfg", + "env_cfg_entry_point": f"{__name__}.rough_env_cfg:G1RoughEnvCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:G1RoughPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_rough_ppo_cfg.yaml", }, @@ -31,7 +28,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.rough_env_cfg:G1RoughEnvCfg_PLAY", + "env_cfg_entry_point": f"{__name__}.rough_env_cfg:G1RoughEnvCfg_PLAY", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:G1RoughPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_rough_ppo_cfg.yaml", }, @@ -43,7 +40,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.flat_env_cfg:G1FlatEnvCfg", + "env_cfg_entry_point": f"{__name__}.flat_env_cfg:G1FlatEnvCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:G1FlatPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_flat_ppo_cfg.yaml", }, @@ -55,7 +52,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.flat_env_cfg:G1FlatEnvCfg_PLAY", + "env_cfg_entry_point": f"{__name__}.flat_env_cfg:G1FlatEnvCfg_PLAY", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:G1FlatPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_flat_ppo_cfg.yaml", }, diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/go1/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/go1/__init__.py index 68ca2a6f54..b30722bc7f 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/go1/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/go1/__init__.py @@ -11,14 +11,12 @@ # Register Gym environments. ## -task_entry = "omni.isaac.lab_tasks.manager_based.locomotion.velocity.config.go1" - gym.register( id="Isaac-Velocity-Flat-Unitree-Go1-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.flat_env_cfg:UnitreeGo1FlatEnvCfg", + "env_cfg_entry_point": f"{__name__}.flat_env_cfg:UnitreeGo1FlatEnvCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:UnitreeGo1FlatPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_flat_ppo_cfg.yaml", }, @@ -29,7 +27,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.flat_env_cfg:UnitreeGo1FlatEnvCfg_PLAY", + "env_cfg_entry_point": f"{__name__}.flat_env_cfg:UnitreeGo1FlatEnvCfg_PLAY", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:UnitreeGo1FlatPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_flat_ppo_cfg.yaml", }, @@ -40,7 +38,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.rough_env_cfg:UnitreeGo1RoughEnvCfg", + "env_cfg_entry_point": f"{__name__}.rough_env_cfg:UnitreeGo1RoughEnvCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:UnitreeGo1RoughPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_rough_ppo_cfg.yaml", }, @@ -51,7 +49,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.rough_env_cfg:UnitreeGo1RoughEnvCfg_PLAY", + "env_cfg_entry_point": f"{__name__}.rough_env_cfg:UnitreeGo1RoughEnvCfg_PLAY", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:UnitreeGo1RoughPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_rough_ppo_cfg.yaml", }, diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/go2/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/go2/__init__.py index 819c5bc0b9..85071ad547 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/go2/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/go2/__init__.py @@ -11,14 +11,12 @@ # Register Gym environments. ## -task_entry = "omni.isaac.lab_tasks.manager_based.locomotion.velocity.config.go2" - gym.register( id="Isaac-Velocity-Flat-Unitree-Go2-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.flat_env_cfg:UnitreeGo2FlatEnvCfg", + "env_cfg_entry_point": f"{__name__}.flat_env_cfg:UnitreeGo2FlatEnvCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:UnitreeGo2FlatPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_flat_ppo_cfg.yaml", }, @@ -29,7 +27,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.flat_env_cfg:UnitreeGo2FlatEnvCfg_PLAY", + "env_cfg_entry_point": f"{__name__}.flat_env_cfg:UnitreeGo2FlatEnvCfg_PLAY", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:UnitreeGo2FlatPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_flat_ppo_cfg.yaml", }, @@ -40,7 +38,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.rough_env_cfg:UnitreeGo2RoughEnvCfg", + "env_cfg_entry_point": f"{__name__}.rough_env_cfg:UnitreeGo2RoughEnvCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:UnitreeGo2RoughPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_rough_ppo_cfg.yaml", }, @@ -51,7 +49,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.rough_env_cfg:UnitreeGo2RoughEnvCfg_PLAY", + "env_cfg_entry_point": f"{__name__}.rough_env_cfg:UnitreeGo2RoughEnvCfg_PLAY", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:UnitreeGo2RoughPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_rough_ppo_cfg.yaml", }, diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/h1/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/h1/__init__.py index f95053e7bd..b03937ae60 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/h1/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/h1/__init__.py @@ -11,15 +11,12 @@ # Register Gym environments. ## -task_entry = "omni.isaac.lab_tasks.manager_based.locomotion.velocity.config.h1" - - gym.register( id="Isaac-Velocity-Rough-H1-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.rough_env_cfg:H1RoughEnvCfg", + "env_cfg_entry_point": f"{__name__}.rough_env_cfg:H1RoughEnvCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:H1RoughPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_rough_ppo_cfg.yaml", }, @@ -31,7 +28,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.rough_env_cfg:H1RoughEnvCfg_PLAY", + "env_cfg_entry_point": f"{__name__}.rough_env_cfg:H1RoughEnvCfg_PLAY", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:H1RoughPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_rough_ppo_cfg.yaml", }, @@ -43,7 +40,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.flat_env_cfg:H1FlatEnvCfg", + "env_cfg_entry_point": f"{__name__}.flat_env_cfg:H1FlatEnvCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:H1FlatPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_flat_ppo_cfg.yaml", }, @@ -55,7 +52,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.flat_env_cfg:H1FlatEnvCfg_PLAY", + "env_cfg_entry_point": f"{__name__}.flat_env_cfg:H1FlatEnvCfg_PLAY", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:H1FlatPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_flat_ppo_cfg.yaml", }, diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/spot/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/spot/__init__.py index e614dd40bd..a2a852dd68 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/spot/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/locomotion/velocity/config/spot/__init__.py @@ -11,14 +11,12 @@ # Register Gym environments. ## -task_entry = "omni.isaac.lab_tasks.manager_based.locomotion.velocity.config.spot" - gym.register( id="Isaac-Velocity-Flat-Spot-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.flat_env_cfg:SpotFlatEnvCfg", + "env_cfg_entry_point": f"{__name__}.flat_env_cfg:SpotFlatEnvCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:SpotFlatPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_flat_ppo_cfg.yaml", }, @@ -29,7 +27,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.flat_env_cfg:SpotFlatEnvCfg_PLAY", + "env_cfg_entry_point": f"{__name__}.flat_env_cfg:SpotFlatEnvCfg_PLAY", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:SpotFlatPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_flat_ppo_cfg.yaml", }, diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/cabinet/config/franka/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/cabinet/config/franka/__init__.py index 249b2e54be..ec861b8cd5 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/cabinet/config/franka/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/cabinet/config/franka/__init__.py @@ -11,8 +11,6 @@ # Register Gym environments. ## -task_entry = "omni.isaac.lab_tasks.manager_based.manipulation.cabinet.config.franka" - ## # Joint Position Control ## @@ -21,7 +19,7 @@ id="Isaac-Open-Drawer-Franka-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", kwargs={ - "env_cfg_entry_point": f"{task_entry}.joint_pos_env_cfg:FrankaCabinetEnvCfg", + "env_cfg_entry_point": f"{__name__}.joint_pos_env_cfg:FrankaCabinetEnvCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:CabinetPPORunnerCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_cfg.yaml", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_ppo_cfg.yaml", @@ -33,7 +31,7 @@ id="Isaac-Open-Drawer-Franka-Play-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", kwargs={ - "env_cfg_entry_point": f"{task_entry}.joint_pos_env_cfg:FrankaCabinetEnvCfg_PLAY", + "env_cfg_entry_point": f"{__name__}.joint_pos_env_cfg:FrankaCabinetEnvCfg_PLAY", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:CabinetPPORunnerCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_cfg.yaml", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_ppo_cfg.yaml", @@ -50,7 +48,7 @@ id="Isaac-Open-Drawer-Franka-IK-Abs-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", kwargs={ - "env_cfg_entry_point": f"{task_entry}.ik_abs_env_cfg:FrankaCabinetEnvCfg", + "env_cfg_entry_point": f"{__name__}.ik_abs_env_cfg:FrankaCabinetEnvCfg", }, disable_env_checker=True, ) @@ -63,7 +61,7 @@ id="Isaac-Open-Drawer-Franka-IK-Rel-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", kwargs={ - "env_cfg_entry_point": f"{task_entry}.ik_rel_env_cfg:FrankaCabinetEnvCfg", + "env_cfg_entry_point": f"{__name__}.ik_rel_env_cfg:FrankaCabinetEnvCfg", }, disable_env_checker=True, ) diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/inhand/config/allegro_hand/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/inhand/config/allegro_hand/__init__.py index a2e97ec29b..031a267384 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/inhand/config/allegro_hand/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/inhand/config/allegro_hand/__init__.py @@ -11,8 +11,6 @@ # Register Gym environments. ## -task_entry = "omni.isaac.lab_tasks.manager_based.manipulation.inhand.config.allegro_hand" - ## # Full kinematic state observations. ## @@ -22,7 +20,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.allegro_env_cfg:AllegroCubeEnvCfg", + "env_cfg_entry_point": f"{__name__}.allegro_env_cfg:AllegroCubeEnvCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:AllegroCubePPORunnerCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_cfg.yaml", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_ppo_cfg.yaml", @@ -34,7 +32,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.allegro_env_cfg:AllegroCubeEnvCfg_PLAY", + "env_cfg_entry_point": f"{__name__}.allegro_env_cfg:AllegroCubeEnvCfg_PLAY", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:AllegroCubePPORunnerCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_cfg.yaml", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_ppo_cfg.yaml", @@ -50,7 +48,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.allegro_env_cfg:AllegroCubeNoVelObsEnvCfg", + "env_cfg_entry_point": f"{__name__}.allegro_env_cfg:AllegroCubeNoVelObsEnvCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:AllegroCubeNoVelObsPPORunnerCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_cfg.yaml", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_ppo_cfg.yaml", @@ -62,7 +60,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.allegro_env_cfg:AllegroCubeNoVelObsEnvCfg_PLAY", + "env_cfg_entry_point": f"{__name__}.allegro_env_cfg:AllegroCubeNoVelObsEnvCfg_PLAY", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:AllegroCubeNoVelObsPPORunnerCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_cfg.yaml", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_ppo_cfg.yaml", diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/lift/config/franka/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/lift/config/franka/__init__.py index 533d5fd5e8..644ac056e9 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/lift/config/franka/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/lift/config/franka/__init__.py @@ -11,8 +11,6 @@ # Register Gym environments. ## -task_entry = "omni.isaac.lab_tasks.manager_based.manipulation.lift.config.franka" - ## # Joint Position Control ## @@ -21,7 +19,7 @@ id="Isaac-Lift-Cube-Franka-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", kwargs={ - "env_cfg_entry_point": f"{task_entry}.joint_pos_env_cfg:FrankaCubeLiftEnvCfg", + "env_cfg_entry_point": f"{__name__}.joint_pos_env_cfg:FrankaCubeLiftEnvCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:LiftCubePPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_ppo_cfg.yaml", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_cfg.yaml", @@ -34,7 +32,7 @@ id="Isaac-Lift-Cube-Franka-Play-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", kwargs={ - "env_cfg_entry_point": f"{task_entry}.joint_pos_env_cfg:FrankaCubeLiftEnvCfg_PLAY", + "env_cfg_entry_point": f"{__name__}.joint_pos_env_cfg:FrankaCubeLiftEnvCfg_PLAY", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:LiftCubePPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_ppo_cfg.yaml", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_cfg.yaml", @@ -51,7 +49,7 @@ id="Isaac-Lift-Cube-Franka-IK-Abs-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", kwargs={ - "env_cfg_entry_point": f"{task_entry}.ik_abs_env_cfg:FrankaCubeLiftEnvCfg", + "env_cfg_entry_point": f"{__name__}.ik_abs_env_cfg:FrankaCubeLiftEnvCfg", }, disable_env_checker=True, ) @@ -60,7 +58,7 @@ id="Isaac-Lift-Teddy-Bear-Franka-IK-Abs-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", kwargs={ - "env_cfg_entry_point": f"{task_entry}.ik_abs_env_cfg:FrankaTeddyBearLiftEnvCfg", + "env_cfg_entry_point": f"{__name__}.ik_abs_env_cfg:FrankaTeddyBearLiftEnvCfg", }, disable_env_checker=True, ) @@ -73,7 +71,7 @@ id="Isaac-Lift-Cube-Franka-IK-Rel-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", kwargs={ - "env_cfg_entry_point": f"{task_entry}.ik_rel_env_cfg:FrankaCubeLiftEnvCfg", + "env_cfg_entry_point": f"{__name__}.ik_rel_env_cfg:FrankaCubeLiftEnvCfg", "robomimic_bc_cfg_entry_point": os.path.join(agents.__path__[0], "robomimic/bc.json"), }, disable_env_checker=True, diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/reach/config/franka/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/reach/config/franka/__init__.py index 9bfd737a90..f66d0ba910 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/reach/config/franka/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/reach/config/franka/__init__.py @@ -11,8 +11,6 @@ # Register Gym environments. ## -task_entry = "omni.isaac.lab_tasks.manager_based.manipulation.reach.config.franka" - ## # Joint Position Control ## @@ -22,7 +20,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.joint_pos_env_cfg:FrankaReachEnvCfg", + "env_cfg_entry_point": f"{__name__}.joint_pos_env_cfg:FrankaReachEnvCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_cfg.yaml", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:FrankaReachPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_ppo_cfg.yaml", @@ -34,7 +32,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.joint_pos_env_cfg:FrankaReachEnvCfg_PLAY", + "env_cfg_entry_point": f"{__name__}.joint_pos_env_cfg:FrankaReachEnvCfg_PLAY", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_cfg.yaml", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:FrankaReachPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_ppo_cfg.yaml", @@ -50,7 +48,7 @@ id="Isaac-Reach-Franka-IK-Abs-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", kwargs={ - "env_cfg_entry_point": f"{task_entry}.ik_abs_env_cfg:FrankaReachEnvCfg", + "env_cfg_entry_point": f"{__name__}.ik_abs_env_cfg:FrankaReachEnvCfg", }, disable_env_checker=True, ) @@ -63,7 +61,7 @@ id="Isaac-Reach-Franka-IK-Rel-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", kwargs={ - "env_cfg_entry_point": f"{task_entry}.ik_rel_env_cfg:FrankaReachEnvCfg", + "env_cfg_entry_point": f"{__name__}.ik_rel_env_cfg:FrankaReachEnvCfg", }, disable_env_checker=True, ) diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/reach/config/ur_10/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/reach/config/ur_10/__init__.py index 1c1fc72621..c2ce4c673d 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/reach/config/ur_10/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/manipulation/reach/config/ur_10/__init__.py @@ -11,14 +11,12 @@ # Register Gym environments. ## -task_entry = "omni.isaac.lab_tasks.manager_based.manipulation.reach.config.ur_10" - gym.register( id="Isaac-Reach-UR10-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.joint_pos_env_cfg:UR10ReachEnvCfg", + "env_cfg_entry_point": f"{__name__}.joint_pos_env_cfg:UR10ReachEnvCfg", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_cfg.yaml", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:UR10ReachPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_ppo_cfg.yaml", @@ -30,7 +28,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.joint_pos_env_cfg:UR10ReachEnvCfg_PLAY", + "env_cfg_entry_point": f"{__name__}.joint_pos_env_cfg:UR10ReachEnvCfg_PLAY", "rl_games_cfg_entry_point": f"{agents.__name__}:rl_games_ppo_cfg.yaml", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:UR10ReachPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_ppo_cfg.yaml", diff --git a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/navigation/config/anymal_c/__init__.py b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/navigation/config/anymal_c/__init__.py index 6911bea515..31e7989bc8 100644 --- a/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/navigation/config/anymal_c/__init__.py +++ b/source/extensions/omni.isaac.lab_tasks/omni/isaac/lab_tasks/manager_based/navigation/config/anymal_c/__init__.py @@ -11,14 +11,12 @@ # Register Gym environments. ## -task_entry = "omni.isaac.lab_tasks.manager_based.navigation.config.anymal_c" - gym.register( id="Isaac-Navigation-Flat-Anymal-C-v0", entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.navigation_env_cfg:NavigationEnvCfg", + "env_cfg_entry_point": f"{__name__}.navigation_env_cfg:NavigationEnvCfg", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:NavigationEnvPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_flat_ppo_cfg.yaml", }, @@ -29,7 +27,7 @@ entry_point="omni.isaac.lab.envs:ManagerBasedRLEnv", disable_env_checker=True, kwargs={ - "env_cfg_entry_point": f"{task_entry}.navigation_env_cfg:NavigationEnvCfg_PLAY", + "env_cfg_entry_point": f"{__name__}.navigation_env_cfg:NavigationEnvCfg_PLAY", "rsl_rl_cfg_entry_point": f"{agents.__name__}.rsl_rl_ppo_cfg:NavigationEnvPPORunnerCfg", "skrl_cfg_entry_point": f"{agents.__name__}:skrl_flat_ppo_cfg.yaml", }, From b9a49caebc912b86f2ace0709c08d9884d167cda Mon Sep 17 00:00:00 2001 From: OOmotuyi <159472067+OOmotuyi@users.noreply.github.com> Date: Tue, 5 Nov 2024 15:59:57 -0800 Subject: [PATCH 060/111] Adds Isaac Lab Reference Architecture documentation (#1371) # Description Adding Isaac Lab Reference Architecture documentation to present an overview of the end-to-end robot learning process with Isaac Lab. ## Checklist - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [x] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [ ] I have added tests that prove my fix is effective or that my feature works - [ ] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [x] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --------- Co-authored-by: Kelly Guo --- docs/index.rst | 1 + .../deployment-dark.svg | 3 + .../deployment-light.svg | 3 + .../isaac-lab-ra-dark.svg | 3 + .../isaac-lab-ra-light.svg | 3 + .../multi-gpu-training-dark.svg | 3 + .../multi-gpu-training-light.svg | 3 + .../single-gpu-training-dark.svg | 3 + .../single-gpu-training-light.svg | 3 + .../refs/reference_architecture/index.rst | 375 ++++++++++++++++++ 10 files changed, 400 insertions(+) create mode 100644 docs/source/_static/reference-architecture/deployment-dark.svg create mode 100644 docs/source/_static/reference-architecture/deployment-light.svg create mode 100644 docs/source/_static/reference-architecture/isaac-lab-ra-dark.svg create mode 100644 docs/source/_static/reference-architecture/isaac-lab-ra-light.svg create mode 100644 docs/source/_static/reference-architecture/multi-gpu-training-dark.svg create mode 100644 docs/source/_static/reference-architecture/multi-gpu-training-light.svg create mode 100644 docs/source/_static/reference-architecture/single-gpu-training-dark.svg create mode 100644 docs/source/_static/reference-architecture/single-gpu-training-light.svg create mode 100644 docs/source/refs/reference_architecture/index.rst diff --git a/docs/index.rst b/docs/index.rst index 1d88042df2..2c1561104a 100644 --- a/docs/index.rst +++ b/docs/index.rst @@ -127,6 +127,7 @@ Table of Contents :maxdepth: 1 :caption: References + source/refs/reference_architecture/index source/refs/additional_resources source/refs/contributing source/refs/troubleshooting diff --git a/docs/source/_static/reference-architecture/deployment-dark.svg b/docs/source/_static/reference-architecture/deployment-dark.svg new file mode 100644 index 0000000000..ba8c739724 --- /dev/null +++ b/docs/source/_static/reference-architecture/deployment-dark.svg @@ -0,0 +1,3 @@ + + +
Robot Hardware
NVIDIA Isaac Perceptor
Custom Estimator
Isaac ROS Packages
State Estimator
Extract Observation
Actions Controller
Trained Model (.onnx, .pt)
Commanded Actions
Model Inference Runtime
Scaled Actions
1
2
3
4
5
6
7
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Robot Hardware
NVIDIA Isaac Perceptor
Custom Estimator
Isaac ROS Packages
State Estimator
Extract Observation
Actions Controller
Trained Model (.onnx, .pt)
Commanded Actions
Model Inference Runtime
Scaled Actions
1
2
3
4
5
6
7
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Scene Assets
Robot Assets (.usd, .urdf)
Asset Input
Design Robot Learning Task
Scene Configuration
Asset Configuration
Configuration
Register Environment with Gymnasium
Learning Framework Wrapper
Video Wrapper
Wrap Environment
Wrapper API
Test Model
Multi-Node Training
Single GPU Training
Cloud-based Training
Multi-GPU Training
Run Training
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Scene Assets
Robot Assets (.usd, .urdf)
Asset Input
Design Robot Learning Task
Scene Configuration
Asset Configuration
Configuration
Register Environment with Gymnasium
Learning Framework Wrapper
Video Wrapper
Wrap Environment
Wrapper API
Test Model
Multi-Node Training
Single GPU Training
Cloud-based Training
Multi-GPU Training
Run Training
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Environment 0
Gradients
Global Network
Updated Model
GPU 0
Learner 0
Environment 1
GPU 1
Learner 1
Environment N
GPU N
Learner N
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Environment 0
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Isaac Lab
2
States
Add Noise
Assets
Rendering
Trained Model (.pt, .onnx)
Isaac Sim
1
Physics Sim
4
5
RL Libraries
3
Policy
Actions
Observations
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Isaac Lab
2
States
Add Noise
Assets
Rendering
Trained Model (.pt, .onnx)
Isaac Sim
1
Physics Sim
4
5
RL Libraries
3
Policy
Actions
Observations
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diff --git a/docs/source/refs/reference_architecture/index.rst b/docs/source/refs/reference_architecture/index.rst new file mode 100644 index 0000000000..338b8a4415 --- /dev/null +++ b/docs/source/refs/reference_architecture/index.rst @@ -0,0 +1,375 @@ +Reference Architecture +====================== + +This document presents an overview of the end-to-end robot learning process with +Isaac Lab and Isaac Sim. This is demonstrated using a reference architecture that highlights +the major building blocks for training and deployment workflows. It provides a comprehensive, +user-friendly guide on the entire process of developing applications from training to deploying +the trained model in the real world, including links to demos, working examples, and documentation. + +Who is this document for? +~~~~~~~~~~~~~~~~~~~~~~~~~~ + +This document is designed to assist robotics developers and researchers working with NVIDIA Isaac Lab +in the robot learning field, including those at research labs, Original Equipment Manufacturers (OEM), +Solutions Providers, Solutions Integrators (SI), and independent software vendors (ISV). It offers +guidance on utilizing Isaac Lab’s robot training framework and workflows as a foundational starting +point for environment configuration, task design, and policy training and testing. + + + +.. image:: ../../_static/reference-architecture/isaac-lab-ra-light.svg + :class: only-light + :align: center + :alt: Isaac Lab Reference Architecture + +.. image:: ../../_static/reference-architecture/isaac-lab-ra-dark.svg + :class: only-dark + :align: center + :alt: Isaac Lab Reference Architecture + + +| + +The reference architecture for Isaac Lab comprises the following components: + +1. :ref:`Asset Input` +2. :ref:`Configuration - Assets & Scene` +3. :ref:`Robot Learning Task Design` +4. :ref:`Register with Gymnasium` +5. :ref:`Environment Wrapping` +6. :ref:`Run Training` +7. :ref:`Run Testing` + + + + +Components +~~~~~~~~~~~ +In this section, we will briefly discuss the individual blocks for creating a +sample reference application in Isaac Lab. + + +.. _ra-asset-input: + +Component 1 - Asset Input +--------------------------- +Isaac Lab accepts URDF, MJCF XML or USD files for the assets. The first step to training using Isaac Lab is to +have the USD file of your asset and the USD or URDF file of your robot. This can be achieved in +the following ways: + + +1. Design your assets or robot in Isaac Sim and export the USD file. + +2. Design your assets or robot in any software of your choice and export it to USD using Isaac Sim converters. Isaac Sim supports the different converters/importers to USD such as the `CAD Converter`_, `URDF Importer`_, `MJCF Importer`_, `Onshape Importer`_, etc. More details are found in the `Importing Assets section`_ in the `Isaac Sim Reference Architecture`_. + +3. If you already have the URDF or MJCF file of your robot, you do not need to convert to USD as Isaac Lab takes URDF and MJCF XML. + + +.. _ra-configuration: + +Component 2 - Configuration (Assets and Scene) +------------------------------------------------------ + +Asset Configuration +^^^^^^^^^^^^^^^^^^^^^^^^ + +Given that you have the asset file for your robot and other assets such as environment objects based on the task, the next step is to import them into Isaac Lab. Isaac Lab uses asset configuration classes to spawn various objects (or prims) into the scene using Python. The first step is to write a configuration class to define the properties for the assets needed to complete the task. For example, a simple go-to-goal task for a mobile robot will include the robot asset, an object like cubes to signify the goal pose visually, lights, ground plane, etc. Isaac Lab understands these assets using the configuration classes. Isaac Lab provides various sim-ready assets such as physically accurate +3D objects that encompass accurate physical properties and behavior. It also provides connected data streams to represent the real world in simulated digital worlds such as `robots `__ +like ANYbotics Anymal, Unitree H1 Humanoid, etc. as well as `sensors `__. We provide these assets configuration classes. Users can also define their own assets using the configuration classes. + +Follow the tutorial on `how to write an Articulation and ArticulationCfg class `__. + +Scene Configuration +^^^^^^^^^^^^^^^^^^^^^^^^ + +Given the individual asset configurations, the next step is to put all the assets together into a +scene. The scene configuration is a simple config class that initializes all the assets in the +scene that are needed for the task and for visualization. This is an example for the +`Cartpole example scene configuration `__, +which includes the cartpole, ground plane, and dome light. + + +.. _ra-robot-learning-task-design: + +Component 3 - Robot Learning Task Design +------------------------------------------------------ +Now, we have the scene for the task, but we need to define the robot learning task. We will focus on +`reinforcement learning (RL) `__ algorithm here. We define the RL task +that the agent is going to do. RL tasks are defined as a Markov Decision Process (MDP), +which is a stochastic decision-making process where optional decisions are made for the agents +considering their current state and environment they interact with. The environment provides the +agents’ current state or observations, and executes the actions provided by the agent. +The environment responds to the agents by providing the next states, reward of taking the +action, done flag and information about the current episode. Therefore, different components +of the MDP formulation (the environment) – states, actions, rewards, reset, done, etc. — must +be defined by the user for the agent to perform the given task. + +In Isaac Lab, we provide two different workflows for designing environments. + +Manager-based +^^^^^^^^^^^^^^^^^ +.. image:: ../../_static/task-workflows/manager-based-light.svg + :class: only-light + :align: center + :alt: Manager-based Task Workflow + +.. image:: ../../_static/task-workflows/manager-based-dark.svg + :class: only-dark + :align: center + :alt: Manager-based Task Workflow + +This workflow is modular, and the environment is decomposed into individual components (or managers) +that handle the different aspects of the environment, such as computing observations, +applying actions, and applying randomization. As a user, you define different configuration classes +for each component. + +- An RL task should have the following configuration classes: + + - Observations Config: Defines the agents’ observations for the task. + - Actions Config: Defines the agent’s action type, i.e. how the output of the agent are mapped to + the robot's control inputs. + - Rewards Config: Defines the reward function for the task + - Terminations Config: Defines the conditions for termination of an episode or when the task + is completed. + +- You can add other optional configuration classes such as Event Config which defines the set of randomizations and noisification for the agent and environment, Curriculum Config for tasks that require `curriculum learning`_ and Commands Config for tasks where the input is from a controller/setpoint controls e.g. a gamepad controller. + +.. tip:: + + To learn more on how you can design your own manager-based environment, see :ref:`tutorial-create-manager-rl-env`. + + + +Direct +^^^^^^^^ +.. image:: ../../_static/task-workflows/direct-based-light.svg + :class: only-light + :align: center + :alt: Direct-based Task Workflow + +.. image:: ../../_static/task-workflows/direct-based-dark.svg + :class: only-dark + :align: center + :alt: Direct-based Task Workflow + +In this workflow, you implement a single class that is responsible for computing observations, applying actions, and computing rewards. This workflow allows for direct control of the environment logic. + +.. tip:: + To learn more on how you can design your own direct environment, see :ref:`tutorial-create-direct-rl-env`. + +Users can choose from Isaac Lab’s large suite of pre-configured environments or users can define +their own environments. For more technical information about the two workflows, please see the +`documentation `__. + + +In addition to designing the RL task, you will need to design your agent’s model, the neural +network policy and value function. To train the RL agent to solve the task, you need to define +the hyperparameters such as number of epochs, learning rate, etc. for training and the +policy/value model architecture. This is defined in the training configuration file specific +to the RL library you want to use. Examples are created under the agent's folder in each task directory. +See an example of `RSL-RL `__ for Anymal-B. + + +.. _ra-register-gym: + +Component 4 - Register with Gymnasium +------------------------------------------------------ + +The next step is to register the environments with the gymnasium registry to allow you to create the environment using the unique environment name. +Registration is a way to make the environment accessible and reusable across different +RL algorithms and experiments. This is common in the RL community. Follow the tutorial on +`Registering an Environment `__ to learn more about how to register in your own environment. + +.. _ra-env-wrap: + +Component 5 - Environment Wrapping +------------------------------------------------------ +In running your RL task, you might want to change the behavior of your environment without +changing the environment itself. For example, you might want to create functions to modify +observations or rewards, record videos, or enforce time limits. Isaac Lab utilizes the API +available in the `gymnasium.Wrapper `__ class to create interfaces to the simulated environments. + +Some wrappers include: + +* `Video Wrappers `__ +* `RL Libraries Wrappers `__ + +Most RL libraries expect their own variation of an environment interface. This means the +data types needed by each library differs. Isaac Lab provides its own wrappers to convert +the environment into the expected interface by the RL library a user wants to use. These are +specified in the `Isaac Lab utils wrapper module `__. + +See the `full list `__ of other wrappers APIs. For more information on how these wrappers work, +please refer to the `Wrapping environments `__ documentation. + +Adding your own wrappers +^^^^^^^^^^^^^^^^^^^^^^^^ + +You can define your own wrappers by adding them to the Isaac Lab utils wrapper module. More information is available `on the GitHub page for wrapping environments `__. + +.. _ra-run-training: + +Component 6 - Run Training +--------------------------- + +Finally, the last step is to run the training of the RL agent. Isaac Lab provides scripts which utilizes four popular RL libraries for training the models (GPU-based training): + +* `StableBaselines3 `__ +* `RSL-RL `__ +* `RL-Games `__ +* `SKRL `__ + + +.. note:: + + Isaac Lab does not provide the implementation of these RL libraries. They are already implemented by different authors. We provide the environments and framework wrappers for the RL libraries. + + + +If you want to integrate a different version of the provided algorithms or your learning library, you can follow +`these instructions `__. + + + +Single GPU Training +^^^^^^^^^^^^^^^^^^^^^^^^ +.. image:: ../../_static/reference-architecture/single-gpu-training-light.svg + :class: only-light + :align: center + :alt: Single GPU Training Data Flow + +.. image:: ../../_static/reference-architecture/single-gpu-training-dark.svg + :class: only-dark + :align: center + :alt: Single GPU Training Data Flow + +Isaac Lab supports training massively parallel environments to speed up RL training and provides rich data for the model to train. +For single GPU training, the following steps show how training works in Isaac Sim and Isaac Lab: + +1. **In Isaac Sim** + +* Isaac Sim provides the asset states such as robot and sensor states, including the observations defined in the task observation config class. + +2. **In Isaac Lab** + +* Randomizations are added to the states defined in the event configuration class to obtain the observation for the task. Randomizations are however optional. If not defined, the states are the observations. +* The observations are computed as PyTorch tensors, and it can optionally include the action provided by the trained model based on the task. + +3. **In the RL library** + +* The observation is passed to the policy. +* The policy is trained to output the right actions for the robot using RL library algorithms such as PPO, TRPO, etc. +* The actions can serve either as a setpoint for a controller that generates the action to the robot or used directly as the action to the robot based on the task. +* Action types such as joint position for a quadruped is an input to a joint controller, velocity of 1 or 0 is used to control the cart directly in the cartpole task, etc. +* In addition, based on how the task is defined, the previous action can be part of the next set of observations that is sent. + +4. **In Isaac Sim** + +* The actions from the policy are sent back to Isaac Sim to control the agent that is learning i.e. the robot. This is the physics simulation (sim) step. This generates the next states in Isaac Sim and the rewards are calculated in Isaac Lab. + +5. **Rendering** + +* The scene can be rendered to produce the cameras' images. + + +The next state is then passed in the flow till the training reaches the specified training steps or epochs. The final product is the trained model/agent. + + + +Multi-GPU and Multi-Node Training +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +.. image:: ../../_static/reference-architecture/multi-gpu-training-light.svg + :class: only-light + :align: center + :alt: Multi GPU Training Data Flow + +.. image:: ../../_static/reference-architecture/multi-gpu-training-dark.svg + :class: only-dark + :align: center + :alt: Multi GPU Training Data Flow + + +Isaac Lab supports scaling up training by taking advantage of multi-GPU and multi-node training on Linux. Follow the tutorial on `Multi-GPU training `__ and `Multi-Node training `__ to get started. + + +Cloud-Based Training +^^^^^^^^^^^^^^^^^^^^^^^^ +Isaac Lab can be deployed alongside Isaac Sim onto the public clouds with `Isaac Automator `__. AWS, GCP, Azure, and Alibaba Cloud are currently supported. Follow the tutorial on `how to run Isaac Lab in the cloud `__. + +.. note:: + + Both multi-GPU and multi-node jobs can be easily scaled across heterogeneous environments with `OSMO `__, a cloud-native, orchestration platform for scheduling complex multi-stage and multi-container heterogeneous computing workflows. Isaac Lab also provides the tools to run your RL task in Docker. See more details on `container deployment `__. + +.. _ra-run-testing: + +Component 7: Run Testing +----------------------------- +Isaac Lab provides scripts for `testing/playing the trained policy `__ on the environment and functions for converting the trained model from .pt to +.jit and .onnx for deployment. + + +Deployment on Physical Robots +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +.. image:: ../../_static/reference-architecture/deployment-light.svg + :class: only-light + :align: center + :alt: Isaac Lab Trained Policy Deployment + +.. image:: ../../_static/reference-architecture/deployment-dark.svg + :class: only-dark + :align: center + :alt: Isaac Lab Trained Policy Deployment + + +To deploy your trained model on a real robot, you would need what is shown in the flow diagram. Note, this is a sample reference architecture, hence it can be tweaked for a different application. +First, you need a robot with the required sensors and processing computer such as `NVIDIA Jetson `__ to deploy on. Next, you need a state estimator for your robot. The state estimator should be able to deliver the list of observations used for training. + +Once the observations are extracted, they are passed into the model which delivers the action using the model inferencing runtime. The commanded action from the model serves as setpoints for the action controller. The action controller outputs scaled actions which are then used to control the robot to get to the next state, and this continues till the task is done. + +NVIDIA Isaac platform provides some tools for state estimation, including visual slam and inferencing engines such as `TensorRT `__. Other inferencing runtime includes `OnnxRuntime `__, direct inferencing on the PyTorch model, etc. + + + + +Summary +~~~~~~~~~~~ + +This document presents a reference architecture for Isaac Lab that has undergone SQA testing. We have provided a user-friendly guide to end-to-end robot learning with Isaac Lab and Isaac Sim from training to real-world deployment, including demos, examples, and documentation links. + + +How to Get Started +~~~~~~~~~~~~~~~~~~~~~~ +Check out our resources on using Isaac Lab with your robots. + +Review Our Documentation & Samples Resources + +* `Isaac Lab Tutorials`_ +* `Fast-Track Robot Learning in Simulation Using NVIDIA Isaac Lab`_ +* `Supercharge Robotics Workflows with AI and Simulation Using NVIDIA Isaac Sim 4.0 and NVIDIA Isaac Lab`_ +* `Closing the Sim-to-Real Gap: Training Spot Quadruped Locomotion with NVIDIA Isaac Lab `__ +* `Additional Resources`_ + +Learn More About Featured NVIDIA Solutions + +* `Scale AI-Enabled Robotics Development Workloads with NVIDIA OSMO`_ +* `Parkour and More: How Simulation-Based RL Helps to Push the Boundaries in Legged Locomotion (GTC session) `__ +* `Isaac Perceptor`_ +* `Isaac Manipulator`_ + +.. _curriculum learning: https://arxiv.org/abs/2109.11978 +.. _CAD Converter: https://docs.omniverse.nvidia.com/extensions/latest/ext_cad-converter.html +.. _URDF Importer: https://docs.omniverse.nvidia.com/isaacsim/latest/advanced_tutorials/tutorial_advanced_import_urdf.html +.. _MJCF Importer: https://docs.omniverse.nvidia.com/isaacsim/latest/advanced_tutorials/tutorial_advanced_import_mjcf.html#import-mjcf +.. _Onshape Importer: https://docs.omniverse.nvidia.com/extensions/latest/ext_onshape.html +.. _Isaac Sim Reference Architecture: https://docs.omniverse.nvidia.com/isaacsim/latest/isaac_sim_reference_architecture.html +.. _Importing Assets section: https://docs.omniverse.nvidia.com/isaacsim/latest/isaac_sim_reference_architecture.html#importing-assets + +.. _Scale AI-Enabled Robotics Development Workloads with NVIDIA OSMO: https://developer.nvidia.com/blog/scale-ai-enabled-robotics-development-workloads-with-nvidia-osmo/ +.. _Isaac Perceptor: https://developer.nvidia.com/isaac/perceptor +.. _Isaac Manipulator: https://developer.nvidia.com/isaac/manipulator +.. _Additional Resources: https://isaac-sim.github.io/IsaacLab/main/source/refs/additional_resources.html +.. _Isaac Lab Tutorials: file:///home/oomotuyi/isaac/IsaacLab/docs/_build/current/source/tutorials/index.html +.. _Fast-Track Robot Learning in Simulation Using NVIDIA Isaac Lab: https://developer.nvidia.com/blog/fast-track-robot-learning-in-simulation-using-nvidia-isaac-lab/ +.. _Supercharge Robotics Workflows with AI and Simulation Using NVIDIA Isaac Sim 4.0 and NVIDIA Isaac Lab: https://developer.nvidia.com/blog/supercharge-robotics-workflows-with-ai-and-simulation-using-nvidia-isaac-sim-4-0-and-nvidia-isaac-lab/ From 84b2d2d8849e86752aa5a948d5f818d8430eec5a Mon Sep 17 00:00:00 2001 From: David Hoeller Date: Fri, 8 Nov 2024 12:03:43 +0100 Subject: [PATCH 061/111] Adds a rigid body collection class (#1288) # Description Adds a rigid body collection class, which allows to spawn multiple objects in each environment and access/modify the quantities with a unified (env_ids, object_ids) API. ## Type of change - New feature (non-breaking change which adds functionality) ## Checklist - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [x] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [x] I have added tests that prove my fix is effective or that my feature works - [x] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [x] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --- docs/source/_static/demos/multi_asset.jpg | Bin 559660 -> 551533 bytes docs/source/api/lab/omni.isaac.lab.assets.rst | 23 + docs/source/how-to/multi_asset_spawning.rst | 56 +- .../omni.isaac.lab/config/extension.toml | 2 +- .../omni.isaac.lab/docs/CHANGELOG.rst | 12 +- .../omni/isaac/lab/assets/__init__.py | 1 + .../rigid_object_collection/__init__.py | 10 + .../rigid_object_collection.py | 507 ++++++++++++++++++ .../rigid_object_collection_cfg.py | 28 + .../rigid_object_collection_data.py | 251 +++++++++ .../isaac/lab/managers/scene_entity_cfg.py | 65 ++- .../omni/isaac/lab/scene/interactive_scene.py | 27 +- .../assets/test_rigid_object_collection.py | 506 +++++++++++++++++ source/standalone/demos/multi_asset.py | 69 ++- 14 files changed, 1530 insertions(+), 27 deletions(-) create mode 100644 source/extensions/omni.isaac.lab/omni/isaac/lab/assets/rigid_object_collection/__init__.py create mode 100644 source/extensions/omni.isaac.lab/omni/isaac/lab/assets/rigid_object_collection/rigid_object_collection.py create mode 100644 source/extensions/omni.isaac.lab/omni/isaac/lab/assets/rigid_object_collection/rigid_object_collection_cfg.py create mode 100644 source/extensions/omni.isaac.lab/omni/isaac/lab/assets/rigid_object_collection/rigid_object_collection_data.py create mode 100644 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b/docs/source/api/lab/omni.isaac.lab.assets.rst @@ -12,6 +12,9 @@ RigidObject RigidObjectData RigidObjectCfg + RigidObjectCollection + RigidObjectCollectionData + RigidObjectCollectionCfg Articulation ArticulationData ArticulationCfg @@ -51,6 +54,26 @@ Rigid Object :show-inheritance: :exclude-members: __init__, class_type +Rigid Object Collection +----------------------- + +.. autoclass:: RigidObjectCollection + :members: + :inherited-members: + :show-inheritance: + +.. autoclass:: RigidObjectCollectionData + :members: + :inherited-members: + :show-inheritance: + :exclude-members: __init__ + +.. autoclass:: RigidObjectCollectionCfg + :members: + :inherited-members: + :show-inheritance: + :exclude-members: __init__, class_type + Articulation ------------ diff --git a/docs/source/how-to/multi_asset_spawning.rst b/docs/source/how-to/multi_asset_spawning.rst index 9f74e39f6b..fe141981fc 100644 --- a/docs/source/how-to/multi_asset_spawning.rst +++ b/docs/source/how-to/multi_asset_spawning.rst @@ -1,16 +1,23 @@ + Spawning Multiple Assets ======================== .. currentmodule:: omni.isaac.lab -Typical, spawning configurations (introduced in the :ref:`tutorial-spawn-prims` tutorial) copy the same +Typical spawning configurations (introduced in the :ref:`tutorial-spawn-prims` tutorial) copy the same asset (or USD primitive) across the different resolved prim paths from the expressions. For instance, if the user specifies to spawn the asset at "/World/Table\_.*/Object", the same asset is created at the paths "/World/Table_0/Object", "/World/Table_1/Object" and so on. -However, at times, it might be desirable to spawn different assets under the prim paths to -ensure a diversity in the simulation. This guide describes how to create different assets under -each prim path using the spawning functionality. +However, we also support multi-asset spawning with two mechanisms: + +1. Rigid object collections. This allows the user to spawn multiple rigid objects in each environment and access/modify + them with a unified API, improving performance. + +2. Spawning different assets under the same prim path. This allows the user to create diverse simulations, where each + environment has a different asset. + +This guide describes how to use these two mechanisms. The sample script ``multi_asset.py`` is used as a reference, located in the ``IsaacLab/source/standalone/demos`` directory. @@ -20,20 +27,41 @@ The sample script ``multi_asset.py`` is used as a reference, located in the .. literalinclude:: ../../../source/standalone/demos/multi_asset.py :language: python - :emphasize-lines: 101-123, 130-149 + :emphasize-lines: 109-131, 135-179, 184-203 :linenos: -This script creates multiple environments, where each environment has a rigid object that is either a cone, -a cube, or a sphere, and an articulation that is either the ANYmal-C or ANYmal-D robot. +This script creates multiple environments, where each environment has: + +* a rigid object collection containing a cone, a cube, and a sphere +* a rigid object that is either a cone, a cube, or a sphere, chosen at random +* an articulation that is either the ANYmal-C or ANYmal-D robot, chosen at random .. image:: ../_static/demos/multi_asset.jpg :width: 100% :alt: result of multi_asset.py -Using Multi-Asset Spawning Functions ------------------------------------- -It is possible to spawn different assets and USDs in each environment using the spawners +Rigid Object Collections +------------------------ + +Multiple rigid objects can be spawned in each environment and accessed/modified with a unified ``(env_ids, obj_ids)`` API. +While the user could also create multiple rigid objects by spawning them individually, the API is more user-friendly and +more efficient since it uses a single physics view under the hood to handle all the objects. + +.. literalinclude:: ../../../source/standalone/demos/multi_asset.py + :language: python + :lines: 135-179 + :dedent: + +The configuration :class:`~assets.RigidObjectCollectionCfg` is used to create the collection. It's attribute :attr:`~assets.RigidObjectCollectionCfg.rigid_objects` +is a dictionary containing :class:`~assets.RigidObjectCfg` objects. The keys serve as unique identifiers for each +rigid object in the collection. + + +Spawning different assets under the same prim path +-------------------------------------------------- + +It is possible to spawn different assets and USDs under the same prim path in each environment using the spawners :class:`~sim.spawners.wrappers.MultiAssetSpawnerCfg` and :class:`~sim.spawners.wrappers.MultiUsdFileCfg`: * We set the spawn configuration in :class:`~assets.RigidObjectCfg` to be @@ -41,7 +69,7 @@ It is possible to spawn different assets and USDs in each environment using the .. literalinclude:: ../../../source/standalone/demos/multi_asset.py :language: python - :lines: 99-125 + :lines: 107-133 :dedent: This function allows you to define a list of different assets that can be spawned as rigid objects. @@ -53,14 +81,14 @@ It is possible to spawn different assets and USDs in each environment using the .. literalinclude:: ../../../source/standalone/demos/multi_asset.py :language: python - :lines: 128-161 + :lines: 182-215 :dedent: Similar to before, this configuration allows the selection of different USD files representing articulated assets. Things to Note --------------- +~~~~~~~~~~~~~~ Similar asset structuring ~~~~~~~~~~~~~~~~~~~~~~~~~ @@ -85,7 +113,7 @@ anymore. Hence the flag :attr:`scene.InteractiveScene.replicate_physics` must be .. literalinclude:: ../../../source/standalone/demos/multi_asset.py :language: python - :lines: 221-224 + :lines: 280-283 :dedent: The Code Execution diff --git a/source/extensions/omni.isaac.lab/config/extension.toml b/source/extensions/omni.isaac.lab/config/extension.toml index 8fb3c29740..df78987189 100644 --- a/source/extensions/omni.isaac.lab/config/extension.toml +++ b/source/extensions/omni.isaac.lab/config/extension.toml @@ -1,7 +1,7 @@ [package] # Note: Semantic Versioning is used: https://semver.org/ -version = "0.27.13" +version = "0.27.14" # Description title = "Isaac Lab framework for Robot Learning" diff --git a/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst b/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst index 5faefa60fc..df775535be 100644 --- a/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst +++ b/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst @@ -1,6 +1,16 @@ Changelog --------- +0.27.14 (2024-10-23) +~~~~~~~~~~~~~~~~~~~~ + +Added +^^^^^ + +* Added the class :class:`~omni.isaac.lab.assets.RigidObjectCollection` which allows to spawn + multiple objects in each environment and access/modify the quantities with a unified (env_ids, object_ids) API. + + 0.27.13 (2024-10-30) ~~~~~~~~~~~~~~~~~~~~ @@ -13,7 +23,7 @@ Added 0.27.12 (2024-01-04) -~~~~~~~~~~~~~~~~~~~ +~~~~~~~~~~~~~~~~~~~~ Removed ^^^^^^^ diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/__init__.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/__init__.py index f0d29abcae..f91e4db7e6 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/__init__.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/__init__.py @@ -43,3 +43,4 @@ from .asset_base_cfg import AssetBaseCfg from .deformable_object import DeformableObject, DeformableObjectCfg, DeformableObjectData from .rigid_object import RigidObject, RigidObjectCfg, RigidObjectData +from .rigid_object_collection import RigidObjectCollection, RigidObjectCollectionCfg, RigidObjectCollectionData diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/rigid_object_collection/__init__.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/rigid_object_collection/__init__.py new file mode 100644 index 0000000000..c0f4b5a46c --- /dev/null +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/rigid_object_collection/__init__.py @@ -0,0 +1,10 @@ +# Copyright (c) 2022-2024, The Isaac Lab Project Developers. +# All rights reserved. +# +# SPDX-License-Identifier: BSD-3-Clause + +"""Sub-module for rigid object collection.""" + +from .rigid_object_collection import RigidObjectCollection +from .rigid_object_collection_cfg import RigidObjectCollectionCfg +from .rigid_object_collection_data import RigidObjectCollectionData diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/rigid_object_collection/rigid_object_collection.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/rigid_object_collection/rigid_object_collection.py new file mode 100644 index 0000000000..53fca921e7 --- /dev/null +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/rigid_object_collection/rigid_object_collection.py @@ -0,0 +1,507 @@ +# Copyright (c) 2022-2024, The Isaac Lab Project Developers. +# All rights reserved. +# +# SPDX-License-Identifier: BSD-3-Clause + +from __future__ import annotations + +import re +import torch +import weakref +from collections.abc import Sequence +from typing import TYPE_CHECKING + +import omni.kit.app +import omni.log +import omni.physics.tensors.impl.api as physx +import omni.timeline +from pxr import UsdPhysics + +import omni.isaac.lab.sim as sim_utils +import omni.isaac.lab.utils.math as math_utils +import omni.isaac.lab.utils.string as string_utils + +from ..asset_base import AssetBase +from .rigid_object_collection_data import RigidObjectCollectionData + +if TYPE_CHECKING: + from .rigid_object_collection_cfg import RigidObjectCollectionCfg + + +class RigidObjectCollection(AssetBase): + """A rigid object collection class. + + This class represents a collection of rigid objects in the simulation, where the state of the rigid objects can be + accessed and modified using a batched ``(env_ids, object_ids)`` API. + + For each rigid body in the collection, the root prim of the asset must have the `USD RigidBodyAPI`_ + applied to it. This API is used to define the simulation properties of the rigid bodies. On playing the + simulation, the physics engine will automatically register the rigid bodies and create a corresponding + rigid body handle. This handle can be accessed using the :attr:`root_physx_view` attribute. + + .. note:: + Rigid objects in the collection are uniquely identified via the key of the dictionary + :attr:`~omni.isaac.lab.assets.RigidObjectCollectionCfg.rigid_objects` in :class:`~omni.isaac.lab.assets.RigidObjectCollectionCfg`. + This differs from the class :class:`~omni.isaac.lab.assets.RigidObject`, where a rigid object is identified by + the name of the Xform where the `USD RigidBodyAPI`_ is applied. This would not be possible for the rigid object + collection since the :attr:`~omni.isaac.lab.assets.RigidObjectCollectionCfg.rigid_objects` dictionary could + contain the same rigid object multiple times, leading to ambiguity. + + .. _`USD RigidBodyAPI`: https://openusd.org/dev/api/class_usd_physics_rigid_body_a_p_i.html + """ + + cfg: RigidObjectCollectionCfg + """Configuration instance for the rigid object collection.""" + + def __init__(self, cfg: RigidObjectCollectionCfg): + """Initialize the rigid object collection. + + Args: + cfg: A configuration instance. + """ + # check that the config is valid + cfg.validate() + # store inputs + self.cfg = cfg + # flag for whether the asset is initialized + self._is_initialized = False + for rigid_object_cfg in self.cfg.rigid_objects.values(): + # check if the rigid object path is valid + # note: currently the spawner does not work if there is a regex pattern in the leaf + # For example, if the prim path is "/World/Object_[1,2]" since the spawner will not + # know which prim to spawn. This is a limitation of the spawner and not the asset. + asset_path = rigid_object_cfg.prim_path.split("/")[-1] + asset_path_is_regex = re.match(r"^[a-zA-Z0-9/_]+$", asset_path) is None + # spawn the asset + if rigid_object_cfg.spawn is not None and not asset_path_is_regex: + rigid_object_cfg.spawn.func( + rigid_object_cfg.prim_path, + rigid_object_cfg.spawn, + translation=rigid_object_cfg.init_state.pos, + orientation=rigid_object_cfg.init_state.rot, + ) + # check that spawn was successful + matching_prims = sim_utils.find_matching_prims(rigid_object_cfg.prim_path) + if len(matching_prims) == 0: + raise RuntimeError(f"Could not find prim with path {rigid_object_cfg.prim_path}.") + + # stores object names + self._object_names_list = [] + + # note: Use weakref on all callbacks to ensure that this object can be deleted when its destructor is called. + # add callbacks for stage play/stop + # The order is set to 10 which is arbitrary but should be lower priority than the default order of 0 + timeline_event_stream = omni.timeline.get_timeline_interface().get_timeline_event_stream() + self._initialize_handle = timeline_event_stream.create_subscription_to_pop_by_type( + int(omni.timeline.TimelineEventType.PLAY), + lambda event, obj=weakref.proxy(self): obj._initialize_callback(event), + order=10, + ) + self._invalidate_initialize_handle = timeline_event_stream.create_subscription_to_pop_by_type( + int(omni.timeline.TimelineEventType.STOP), + lambda event, obj=weakref.proxy(self): obj._invalidate_initialize_callback(event), + order=10, + ) + + self._debug_vis_handle = None + + """ + Properties + """ + + @property + def data(self) -> RigidObjectCollectionData: + return self._data + + @property + def num_instances(self) -> int: + """Number of instances of the collection.""" + return self.root_physx_view.count // self.num_objects + + @property + def num_objects(self) -> int: + """Number of objects in the collection. + + This corresponds to the distinct number of rigid bodies in the collection. + """ + return len(self.object_names) + + @property + def object_names(self) -> list[str]: + """Ordered names of objects in the rigid object collection.""" + return self._object_names_list + + @property + def root_physx_view(self) -> physx.RigidBodyView: + """Rigid body view for the rigid body collection (PhysX). + + Note: + Use this view with caution. It requires handling of tensors in a specific way. + """ + return self._root_physx_view + + """ + Operations. + """ + + def reset(self, env_ids: torch.Tensor | None = None, object_ids: slice | torch.Tensor | None = None): + """Resets all internal buffers of selected environments and objects. + + Args: + env_ids: The indices of the object to reset. Defaults to None (all instances). + object_ids: The indices of the object to reset. Defaults to None (all objects). + """ + # resolve all indices + if env_ids is None: + env_ids = self._ALL_ENV_INDICES + if object_ids is None: + object_ids = self._ALL_OBJ_INDICES + # reset external wrench + self._external_force_b[env_ids[:, None], object_ids] = 0.0 + self._external_torque_b[env_ids[:, None], object_ids] = 0.0 + + def write_data_to_sim(self): + """Write external wrench to the simulation. + + Note: + We write external wrench to the simulation here since this function is called before the simulation step. + This ensures that the external wrench is applied at every simulation step. + """ + # write external wrench + if self.has_external_wrench: + self.root_physx_view.apply_forces_and_torques_at_position( + force_data=self.reshape_data_to_view(self._external_force_b), + torque_data=self.reshape_data_to_view(self._external_torque_b), + position_data=None, + indices=self._env_obj_ids_to_view_ids(self._ALL_ENV_INDICES, self._ALL_OBJ_INDICES), + is_global=False, + ) + + def update(self, dt: float): + self._data.update(dt) + + """ + Operations - Finders. + """ + + def find_objects( + self, name_keys: str | Sequence[str], preserve_order: bool = False + ) -> tuple[torch.Tensor, list[str]]: + """Find objects in the collection based on the name keys. + + Please check the :meth:`omni.isaac.lab.utils.string_utils.resolve_matching_names` function for more + information on the name matching. + + Args: + name_keys: A regular expression or a list of regular expressions to match the object names. + preserve_order: Whether to preserve the order of the name keys in the output. Defaults to False. + + Returns: + A tuple containing the object indices and names. + """ + obj_ids, obj_names = string_utils.resolve_matching_names(name_keys, self.object_names, preserve_order) + return torch.tensor(obj_ids, device=self.device), obj_names + + """ + Operations - Write to simulation. + """ + + def write_object_state_to_sim( + self, + object_state: torch.Tensor, + env_ids: torch.Tensor | None = None, + object_ids: slice | torch.Tensor | None = None, + ): + """Set the object state over selected environment and object indices into the simulation. + + The object state comprises of the cartesian position, quaternion orientation in (w, x, y, z), and linear + and angular velocity. All the quantities are in the simulation frame. + + Args: + object_state: Object state in simulation frame. Shape is (len(env_ids), len(object_ids), 13). + env_ids: Environment indices. If None, then all indices are used. + object_ids: Object indices. If None, then all indices are used. + """ + # set into simulation + self.write_object_pose_to_sim(object_state[..., :7], env_ids=env_ids, object_ids=object_ids) + self.write_object_velocity_to_sim(object_state[..., 7:], env_ids=env_ids, object_ids=object_ids) + + def write_object_pose_to_sim( + self, + object_pose: torch.Tensor, + env_ids: torch.Tensor | None = None, + object_ids: slice | torch.Tensor | None = None, + ): + """Set the object pose over selected environment and object indices into the simulation. + + The object pose comprises of the cartesian position and quaternion orientation in (w, x, y, z). + + Args: + object_pose: Object poses in simulation frame. Shape is (len(env_ids), len(object_ids), 7). + env_ids: Environment indices. If None, then all indices are used. + object_ids: Object indices. If None, then all indices are used. + """ + # resolve all indices + # -- env_ids + if env_ids is None: + env_ids = self._ALL_ENV_INDICES + # -- object_ids + if object_ids is None: + object_ids = self._ALL_OBJ_INDICES + # note: we need to do this here since tensors are not set into simulation until step. + # set into internal buffers + self._data.object_state_w[env_ids[:, None], object_ids, :7] = object_pose.clone() + # convert the quaternion from wxyz to xyzw + poses_xyzw = self._data.object_state_w[..., :7].clone() + poses_xyzw[..., 3:] = math_utils.convert_quat(poses_xyzw[..., 3:], to="xyzw") + # set into simulation + view_ids = self._env_obj_ids_to_view_ids(env_ids, object_ids) + self.root_physx_view.set_transforms(self.reshape_data_to_view(poses_xyzw), indices=view_ids) + + def write_object_velocity_to_sim( + self, + object_velocity: torch.Tensor, + env_ids: torch.Tensor | None = None, + object_ids: slice | torch.Tensor | None = None, + ): + """Set the object velocity over selected environment and object indices into the simulation. + + Args: + object_velocity: Object velocities in simulation frame. Shape is (len(env_ids), len(object_ids), 6). + env_ids: Environment indices. If None, then all indices are used. + object_ids: Object indices. If None, then all indices are used. + """ + # resolve all indices + # -- env_ids + if env_ids is None: + env_ids = self._ALL_ENV_INDICES + # -- object_ids + if object_ids is None: + object_ids = self._ALL_OBJ_INDICES + + self._data.object_state_w[env_ids[:, None], object_ids, 7:] = object_velocity.clone() + self._data.object_acc_w[env_ids[:, None], object_ids] = 0.0 + + # set into simulation + view_ids = self._env_obj_ids_to_view_ids(env_ids, object_ids) + self.root_physx_view.set_velocities( + self.reshape_data_to_view(self._data.object_state_w[..., 7:]), indices=view_ids + ) + + """ + Operations - Setters. + """ + + def set_external_force_and_torque( + self, + forces: torch.Tensor, + torques: torch.Tensor, + object_ids: slice | torch.Tensor | None = None, + env_ids: torch.Tensor | None = None, + ): + """Set external force and torque to apply on the objects' bodies in their local frame. + + For many applications, we want to keep the applied external force on rigid bodies constant over a period of + time (for instance, during the policy control). This function allows us to store the external force and torque + into buffers which are then applied to the simulation at every step. + + .. caution:: + If the function is called with empty forces and torques, then this function disables the application + of external wrench to the simulation. + + .. code-block:: python + + # example of disabling external wrench + asset.set_external_force_and_torque(forces=torch.zeros(0, 0, 3), torques=torch.zeros(0, 0, 3)) + + .. note:: + This function does not apply the external wrench to the simulation. It only fills the buffers with + the desired values. To apply the external wrench, call the :meth:`write_data_to_sim` function + right before the simulation step. + + Args: + forces: External forces in bodies' local frame. Shape is (len(env_ids), len(object_ids), 3). + torques: External torques in bodies' local frame. Shape is (len(env_ids), len(object_ids), 3). + object_ids: Object indices to apply external wrench to. Defaults to None (all objects). + env_ids: Environment indices to apply external wrench to. Defaults to None (all instances). + """ + if forces.any() or torques.any(): + self.has_external_wrench = True + # resolve all indices + # -- env_ids + if env_ids is None: + env_ids = self._ALL_ENV_INDICES + # -- object_ids + if object_ids is None: + object_ids = self._ALL_OBJ_INDICES + # set into internal buffers + self._external_force_b[env_ids[:, None], object_ids] = forces + self._external_torque_b[env_ids[:, None], object_ids] = torques + else: + self.has_external_wrench = False + + """ + Internal helper. + """ + + def _initialize_impl(self): + # create simulation view + self._physics_sim_view = physx.create_simulation_view(self._backend) + self._physics_sim_view.set_subspace_roots("/") + root_prim_path_exprs = [] + for name, rigid_object_cfg in self.cfg.rigid_objects.items(): + # obtain the first prim in the regex expression (all others are assumed to be a copy of this) + template_prim = sim_utils.find_first_matching_prim(rigid_object_cfg.prim_path) + if template_prim is None: + raise RuntimeError(f"Failed to find prim for expression: '{rigid_object_cfg.prim_path}'.") + template_prim_path = template_prim.GetPath().pathString + + # find rigid root prims + root_prims = sim_utils.get_all_matching_child_prims( + template_prim_path, predicate=lambda prim: prim.HasAPI(UsdPhysics.RigidBodyAPI) + ) + if len(root_prims) == 0: + raise RuntimeError( + f"Failed to find a rigid body when resolving '{rigid_object_cfg.prim_path}'." + " Please ensure that the prim has 'USD RigidBodyAPI' applied." + ) + if len(root_prims) > 1: + raise RuntimeError( + f"Failed to find a single rigid body when resolving '{rigid_object_cfg.prim_path}'." + f" Found multiple '{root_prims}' under '{template_prim_path}'." + " Please ensure that there is only one rigid body in the prim path tree." + ) + + # check that no rigid object has an articulation root API, which decreases simulation performance + articulation_prims = sim_utils.get_all_matching_child_prims( + template_prim_path, predicate=lambda prim: prim.HasAPI(UsdPhysics.ArticulationRootAPI) + ) + if len(articulation_prims) != 0: + if articulation_prims[0].GetAttribute("physxArticulation:articulationEnabled").Get(): + raise RuntimeError( + f"Found an articulation root when resolving '{rigid_object_cfg.prim_path}' in the rigid object" + f" collection. These are located at: '{articulation_prims}' under '{template_prim_path}'." + " Please disable the articulation root in the USD or from code by setting the parameter" + " 'ArticulationRootPropertiesCfg.articulation_enabled' to False in the spawn configuration." + ) + + # resolve root prim back into regex expression + root_prim_path = root_prims[0].GetPath().pathString + root_prim_path_expr = rigid_object_cfg.prim_path + root_prim_path[len(template_prim_path) :] + root_prim_path_exprs.append(root_prim_path_expr.replace(".*", "*")) + + self._object_names_list.append(name) + + # -- object view + self._root_physx_view = self._physics_sim_view.create_rigid_body_view(root_prim_path_exprs) + + # check if the rigid body was created + if self._root_physx_view._backend is None: + raise RuntimeError("Failed to create rigid body collection. Please check PhysX logs.") + + # log information about the rigid body + omni.log.info(f"Number of instances: {self.num_instances}") + omni.log.info(f"Number of distinct objects: {self.num_objects}") + omni.log.info(f"Object names: {self.object_names}") + + # container for data access + self._data = RigidObjectCollectionData(self.root_physx_view, self.num_objects, self.device) + + # create buffers + self._create_buffers() + # process configuration + self._process_cfg() + # update the rigid body data + self.update(0.0) + + def _create_buffers(self): + """Create buffers for storing data.""" + # constants + self._ALL_ENV_INDICES = torch.arange(self.num_instances, dtype=torch.long, device=self.device) + self._ALL_OBJ_INDICES = torch.arange(self.num_objects, dtype=torch.long, device=self.device) + + # external forces and torques + self.has_external_wrench = False + self._external_force_b = torch.zeros((self.num_instances, self.num_objects, 3), device=self.device) + self._external_torque_b = torch.zeros_like(self._external_force_b) + + # set information about rigid body into data + self._data.object_names = self.object_names + self._data.default_mass = self.reshape_view_to_data(self.root_physx_view.get_masses().clone()) + self._data.default_inertia = self.reshape_view_to_data(self.root_physx_view.get_inertias().clone()) + + def _process_cfg(self): + """Post processing of configuration parameters.""" + # default state + # -- object state + default_object_states = [] + for rigid_object_cfg in self.cfg.rigid_objects.values(): + default_object_state = ( + tuple(rigid_object_cfg.init_state.pos) + + tuple(rigid_object_cfg.init_state.rot) + + tuple(rigid_object_cfg.init_state.lin_vel) + + tuple(rigid_object_cfg.init_state.ang_vel) + ) + default_object_state = ( + torch.tensor(default_object_state, dtype=torch.float, device=self.device) + .repeat(self.num_instances, 1) + .unsqueeze(1) + ) + default_object_states.append(default_object_state) + # concatenate the default state for each object + default_object_states = torch.cat(default_object_states, dim=1) + self._data.default_object_state = default_object_states + + def reshape_view_to_data(self, data: torch.Tensor) -> torch.Tensor: + """Reshapes and arranges the data coming from the :attr:`root_physx_view` to (num_instances, num_objects, data_size). + + Args: + data: The data coming from the :attr:`root_physx_view`. Shape is (num_instances*num_objects, data_size). + + Returns: + The reshaped data. Shape is (num_instances, num_objects, data_size). + """ + return torch.einsum("ijk -> jik", data.reshape(self.num_objects, self.num_instances, -1)) + + def reshape_data_to_view(self, data: torch.Tensor) -> torch.Tensor: + """Reshapes and arranges the data to the be consistent with data from the :attr:`root_physx_view`. + + Args: + data: The data to be reshaped. Shape is (num_instances, num_objects, data_size). + + Returns: + The reshaped data. Shape is (num_instances*num_objects, data_size). + """ + return torch.einsum("ijk -> jik", data).reshape(self.num_objects * self.num_instances, *data.shape[2:]) + + def _env_obj_ids_to_view_ids( + self, env_ids: torch.Tensor, object_ids: Sequence[int] | slice | torch.Tensor + ) -> torch.Tensor: + """Converts environment and object indices to indices consistent with data from :attr:`root_physx_view`. + + Args: + env_ids: Environment indices. + object_ids: Object indices. + + Returns: + The view indices. + """ + # the order is env_0/object_0, env_0/object_1, env_0/object_..., env_1/object_0, env_1/object_1, ... + # return a flat tensor of indices + if isinstance(object_ids, slice): + object_ids = self._ALL_OBJ_INDICES + elif isinstance(object_ids, Sequence): + object_ids = torch.tensor(object_ids, device=self.device) + return (object_ids.unsqueeze(1) * self.num_instances + env_ids).flatten() + + """ + Internal simulation callbacks. + """ + + def _invalidate_initialize_callback(self, event): + """Invalidates the scene elements.""" + # call parent + super()._invalidate_initialize_callback(event) + # set all existing views to None to invalidate them + self._physics_sim_view = None + self._root_physx_view = None diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/rigid_object_collection/rigid_object_collection_cfg.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/rigid_object_collection/rigid_object_collection_cfg.py new file mode 100644 index 0000000000..bf21fd6091 --- /dev/null +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/rigid_object_collection/rigid_object_collection_cfg.py @@ -0,0 +1,28 @@ +# Copyright (c) 2022-2024, The Isaac Lab Project Developers. +# All rights reserved. +# +# SPDX-License-Identifier: BSD-3-Clause + +from dataclasses import MISSING + +from omni.isaac.lab.assets.rigid_object import RigidObjectCfg +from omni.isaac.lab.utils import configclass + +from .rigid_object_collection import RigidObjectCollection + + +@configclass +class RigidObjectCollectionCfg: + """Configuration parameters for a rigid object collection.""" + + class_type: type = RigidObjectCollection + """The associated asset class. + + The class should inherit from :class:`omni.isaac.lab.assets.asset_base.AssetBase`. + """ + + rigid_objects: dict[str, RigidObjectCfg] = MISSING + """Dictionary of rigid object configurations to spawn. + + The keys are the names for the objects, which are used as unique identifiers throughout the code. + """ diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/rigid_object_collection/rigid_object_collection_data.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/rigid_object_collection/rigid_object_collection_data.py new file mode 100644 index 0000000000..c9930cf740 --- /dev/null +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/rigid_object_collection/rigid_object_collection_data.py @@ -0,0 +1,251 @@ +# Copyright (c) 2022-2024, The Isaac Lab Project Developers. +# All rights reserved. +# +# SPDX-License-Identifier: BSD-3-Clause + +import torch +import weakref + +import omni.physics.tensors.impl.api as physx + +import omni.isaac.lab.utils.math as math_utils +from omni.isaac.lab.utils.buffers import TimestampedBuffer + + +class RigidObjectCollectionData: + """Data container for a rigid object collection. + + This class contains the data for a rigid object collection in the simulation. The data includes the state of + all the bodies in the collection. The data is stored in the simulation world frame unless otherwise specified. + The data is in the order ``(num_instances, num_objects, data_size)``, where data_size is the size of the data. + + For a rigid body, there are two frames of reference that are used: + + - Actor frame: The frame of reference of the rigid body prim. This typically corresponds to the Xform prim + with the rigid body schema. + - Center of mass frame: The frame of reference of the center of mass of the rigid body. + + Depending on the settings of the simulation, the actor frame and the center of mass frame may be the same. + This needs to be taken into account when interpreting the data. + + The data is lazily updated, meaning that the data is only updated when it is accessed. This is useful + when the data is expensive to compute or retrieve. The data is updated when the timestamp of the buffer + is older than the current simulation timestamp. The timestamp is updated whenever the data is updated. + """ + + def __init__(self, root_physx_view: physx.RigidBodyView, num_objects: int, device: str): + """Initializes the data. + + Args: + root_physx_view: The root rigid body view. + num_objects: The number of objects in the collection. + device: The device used for processing. + """ + # Set the parameters + self.device = device + self.num_objects = num_objects + # Set the root rigid body view + # note: this is stored as a weak reference to avoid circular references between the asset class + # and the data container. This is important to avoid memory leaks. + self._root_physx_view: physx.RigidBodyView = weakref.proxy(root_physx_view) + self.num_instances = self._root_physx_view.count // self.num_objects + + # Set initial time stamp + self._sim_timestamp = 0.0 + + # Obtain global physics sim view + physics_sim_view = physx.create_simulation_view("torch") + physics_sim_view.set_subspace_roots("/") + gravity = physics_sim_view.get_gravity() + # Convert to direction vector + gravity_dir = torch.tensor((gravity[0], gravity[1], gravity[2]), device=self.device) + gravity_dir = math_utils.normalize(gravity_dir.unsqueeze(0)).squeeze(0) + + # Initialize constants + self.GRAVITY_VEC_W = gravity_dir.repeat(self.num_instances, self.num_objects, 1) + self.FORWARD_VEC_B = torch.tensor((1.0, 0.0, 0.0), device=self.device).repeat( + self.num_instances, self.num_objects, 1 + ) + + # Initialize the lazy buffers. + self._object_state_w = TimestampedBuffer() + self._object_acc_w = TimestampedBuffer() + + def update(self, dt: float): + """Updates the data for the rigid object collection. + + Args: + dt: The time step for the update. This must be a positive value. + """ + # update the simulation timestamp + self._sim_timestamp += dt + + ## + # Names. + ## + + object_names: list[str] = None + """Object names in the order parsed by the simulation view.""" + + ## + # Defaults. + ## + + default_object_state: torch.Tensor = None + """Default object state ``[pos, quat, lin_vel, ang_vel]`` in local environment frame. Shape is (num_instances, num_objects, 13). + + The position and quaternion are of each object's rigid body's actor frame. Meanwhile, the linear and angular velocities are + of the center of mass frame. + """ + + default_mass: torch.Tensor = None + """Default object mass read from the simulation. Shape is (num_instances, num_objects, 1).""" + + default_inertia: torch.Tensor = None + """Default object inertia tensor read from the simulation. Shape is (num_instances, num_objects, 9). + + The inertia is the inertia tensor relative to the center of mass frame. The values are stored in + the order :math:`[I_{xx}, I_{xy}, I_{xz}, I_{yx}, I_{yy}, I_{yz}, I_{zx}, I_{zy}, I_{zz}]`. + """ + + ## + # Properties. + ## + + @property + def object_state_w(self): + """Object state ``[pos, quat, lin_vel, ang_vel]`` in simulation world frame. Shape is (num_instances, num_objects, 13). + + The position and orientation are of the rigid body's actor frame. Meanwhile, the linear and angular + velocities are of the rigid body's center of mass frame. + """ + if self._object_state_w.timestamp < self._sim_timestamp: + # read data from simulation + pose = self._reshape_view_to_data(self._root_physx_view.get_transforms().clone()) + pose[..., 3:7] = math_utils.convert_quat(pose[..., 3:7], to="wxyz") + velocity = self._reshape_view_to_data(self._root_physx_view.get_velocities()) + # set the buffer data and timestamp + self._object_state_w.data = torch.cat((pose, velocity), dim=-1) + self._object_state_w.timestamp = self._sim_timestamp + return self._object_state_w.data + + @property + def object_acc_w(self): + """Acceleration of all objects. Shape is (num_instances, num_objects, 6). + + This quantity is the acceleration of the rigid bodies' center of mass frame. + """ + if self._object_acc_w.timestamp < self._sim_timestamp: + # note: we use finite differencing to compute acceleration + self._object_acc_w.data = self._reshape_view_to_data(self._root_physx_view.get_accelerations().clone()) + self._object_acc_w.timestamp = self._sim_timestamp + return self._object_acc_w.data + + @property + def projected_gravity_b(self): + """Projection of the gravity direction on base frame. Shape is (num_instances, num_objects, 3).""" + return math_utils.quat_rotate_inverse(self.object_quat_w, self.GRAVITY_VEC_W) + + @property + def heading_w(self): + """Yaw heading of the base frame (in radians). Shape is (num_instances, num_objects,). + + Note: + This quantity is computed by assuming that the forward-direction of the base + frame is along x-direction, i.e. :math:`(1, 0, 0)`. + """ + forward_w = math_utils.quat_apply(self.object_quat_w, self.FORWARD_VEC_B) + return torch.atan2(forward_w[..., 1], forward_w[..., 0]) + + ## + # Derived properties. + ## + + @property + def object_pos_w(self) -> torch.Tensor: + """Object position in simulation world frame. Shape is (num_instances, num_objects, 3). + + This quantity is the position of the actor frame of the rigid bodies. + """ + return self.object_state_w[..., :3] + + @property + def object_quat_w(self) -> torch.Tensor: + """Object orientation (w, x, y, z) in simulation world frame. Shape is (num_instances, num_objects, 4). + + This quantity is the orientation of the actor frame of the rigid bodies. + """ + return self.object_state_w[..., 3:7] + + @property + def object_vel_w(self) -> torch.Tensor: + """Object velocity in simulation world frame. Shape is (num_instances, num_objects, 6). + + This quantity contains the linear and angular velocities of the rigid bodies' center of mass frame. + """ + return self.object_state_w[..., 7:13] + + @property + def object_lin_vel_w(self) -> torch.Tensor: + """Object linear velocity in simulation world frame. Shape is (num_instances, num_objects, 3). + + This quantity is the linear velocity of the rigid bodies' center of mass frame. + """ + return self.object_state_w[..., 7:10] + + @property + def object_ang_vel_w(self) -> torch.Tensor: + """Object angular velocity in simulation world frame. Shape is (num_instances, num_objects, 3). + + This quantity is the angular velocity of the rigid bodies' center of mass frame. + """ + return self.object_state_w[..., 10:13] + + @property + def object_lin_vel_b(self) -> torch.Tensor: + """Object linear velocity in base frame. Shape is (num_instances, num_objects, 3). + + This quantity is the linear velocity of the rigid bodies' center of mass frame with respect to the + rigid body's actor frame. + """ + return math_utils.quat_rotate_inverse(self.object_quat_w, self.object_lin_vel_w) + + @property + def object_ang_vel_b(self) -> torch.Tensor: + """Object angular velocity in base world frame. Shape is (num_instances, num_objects, 3). + + This quantity is the angular velocity of the rigid bodies' center of mass frame with respect to the + rigid body's actor frame. + """ + return math_utils.quat_rotate_inverse(self.object_quat_w, self.object_ang_vel_w) + + @property + def object_lin_acc_w(self) -> torch.Tensor: + """Linear acceleration of all bodies in simulation world frame. Shape is (num_instances, num_objects, 3). + + This quantity is the linear acceleration of the rigid bodies' center of mass frame. + """ + return self.object_acc_w[..., 0:3] + + @property + def object_ang_acc_w(self) -> torch.Tensor: + """Angular acceleration of all bodies in simulation world frame. Shape is (num_instances, num_objects, 3). + + This quantity is the angular acceleration of the rigid bodies' center of mass frame. + """ + return self.object_acc_w[..., 3:6] + + ## + # Helpers. + ## + + def _reshape_view_to_data(self, data: torch.Tensor) -> torch.Tensor: + """Reshapes and arranges the data from the physics view to (num_instances, num_objects, data_size). + + Args: + data: The data from the physics view. Shape is (num_instances*num_objects, data_size). + + Returns: + The reshaped data. Shape is (num_objects, num_instances, data_size). + """ + return torch.einsum("ijk -> jik", data.reshape(self.num_objects, self.num_instances, -1)) diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/scene_entity_cfg.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/scene_entity_cfg.py index 17095c6615..3b801dec19 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/scene_entity_cfg.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/managers/scene_entity_cfg.py @@ -7,7 +7,7 @@ from dataclasses import MISSING -from omni.isaac.lab.assets import Articulation, RigidObject +from omni.isaac.lab.assets import Articulation, RigidObject, RigidObjectCollection from omni.isaac.lab.scene import InteractiveScene from omni.isaac.lab.utils import configclass @@ -78,16 +78,34 @@ class for more details. manager. """ + object_collection_names: str | list[str] | None = None + """The names of the objects in the rigid object collection required by the term. Defaults to None. + + The names can be either names or a regular expression matching the object names in the collection. + + These are converted to object indices on initialization of the manager and passed to the term + function as a list of object indices under :attr:`object_collection_ids`. + """ + + object_collection_ids: list[int] | slice = slice(None) + """The indices of the objects from the rigid object collection required by the term. Defaults to slice(None), + which means all the objects in the collection. + + If :attr:`object_collection_names` is specified, this is filled in automatically on initialization of the manager. + """ + preserve_order: bool = False - """Whether to preserve indices ordering to match with that in the specified joint or body names. Defaults to False. + """Whether to preserve indices ordering to match with that in the specified joint, body, or object collection names. + Defaults to False. - If False, the ordering of the indices are sorted in ascending order (i.e. the ordering in the entity's joints - or bodies). Otherwise, the indices are preserved in the order of the specified joint and body names. + If False, the ordering of the indices are sorted in ascending order (i.e. the ordering in the entity's joints, + bodies, or object in the object collection). Otherwise, the indices are preserved in the order of the specified + joint, body, or object collection names. For more details, see the :meth:`omni.isaac.lab.utils.string.resolve_matching_names` function. .. note:: - This attribute is only used when :attr:`joint_names` or :attr:`body_names` are specified. + This attribute is only used when :attr:`joint_names`, :attr:`body_names`, or :attr:`object_collection_names` are specified. """ @@ -106,6 +124,7 @@ def resolve(self, scene: InteractiveScene): ValueError: If both ``joint_names`` and ``joint_ids`` are specified and are not consistent. ValueError: If both ``fixed_tendon_names`` and ``fixed_tendon_ids`` are specified and are not consistent. ValueError: If both ``body_names`` and ``body_ids`` are specified and are not consistent. + ValueError: If both ``object_collection_names`` and ``object_collection_ids`` are specified and are not consistent. """ # check if the entity is valid if self.name not in scene.keys(): @@ -120,6 +139,9 @@ def resolve(self, scene: InteractiveScene): # convert body names to indices based on regex self._resolve_body_names(scene) + # convert object collection names to indices based on regex + self._resolve_object_collection_names(scene) + def _resolve_joint_names(self, scene: InteractiveScene): # convert joint names to indices based on regex if self.joint_names is not None or self.joint_ids != slice(None): @@ -228,3 +250,36 @@ def _resolve_body_names(self, scene: InteractiveScene): if isinstance(self.body_ids, int): self.body_ids = [self.body_ids] self.body_names = [entity.body_names[i] for i in self.body_ids] + + def _resolve_object_collection_names(self, scene: InteractiveScene): + # convert object names to indices based on regex + if self.object_collection_names is not None or self.object_collection_ids != slice(None): + entity: RigidObjectCollection = scene[self.name] + # -- if both are not their default values, check if they are valid + if self.object_collection_names is not None and self.object_collection_ids != slice(None): + if isinstance(self.object_collection_names, str): + self.object_collection_names = [self.object_collection_names] + if isinstance(self.object_collection_ids, int): + self.object_collection_ids = [self.object_collection_ids] + object_ids, _ = entity.find_objects(self.object_collection_names, preserve_order=self.preserve_order) + object_names = [entity.object_names[i] for i in self.object_collection_ids] + if object_ids != self.object_collection_ids or object_names != self.object_collection_names: + raise ValueError( + "Both 'object_collection_names' and 'object_collection_ids' are specified, and are not" + " consistent.\n\tfrom object collection names:" + f" {self.object_collection_names} [{object_ids}]\n\tfrom object collection ids:" + f" {object_names} [{self.object_collection_ids}]\nHint: Use either 'object_collection_names' or" + " 'object_collection_ids' to avoid confusion." + ) + # -- from object names to object indices + elif self.object_collection_names is not None: + if isinstance(self.object_collection_names, str): + self.object_collection_names = [self.object_collection_names] + self.object_collection_ids, _ = entity.find_objects( + self.object_collection_names, preserve_order=self.preserve_order + ) + # -- from object indices to object names + elif self.object_collection_ids != slice(None): + if isinstance(self.object_collection_ids, int): + self.object_collection_ids = [self.object_collection_ids] + self.object_collection_names = [entity.object_names[i] for i in self.object_collection_ids] diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/scene/interactive_scene.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/scene/interactive_scene.py index 0e74a9f878..ca8f8afde9 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/scene/interactive_scene.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/scene/interactive_scene.py @@ -22,6 +22,8 @@ DeformableObjectCfg, RigidObject, RigidObjectCfg, + RigidObjectCollection, + RigidObjectCollectionCfg, ) from omni.isaac.lab.sensors import ContactSensorCfg, FrameTransformerCfg, SensorBase, SensorBaseCfg from omni.isaac.lab.terrains import TerrainImporter, TerrainImporterCfg @@ -113,6 +115,7 @@ def __init__(self, cfg: InteractiveSceneCfg): self._articulations = dict() self._deformable_objects = dict() self._rigid_objects = dict() + self._rigid_object_collections = dict() self._sensors = dict() self._extras = dict() # obtain the current stage @@ -309,6 +312,11 @@ def rigid_objects(self) -> dict[str, RigidObject]: """A dictionary of rigid objects in the scene.""" return self._rigid_objects + @property + def rigid_object_collections(self) -> dict[str, RigidObjectCollection]: + """A dictionary of rigid object collections in the scene.""" + return self._rigid_object_collections + @property def sensors(self) -> dict[str, SensorBase]: """A dictionary of the sensors in the scene, such as cameras and contact reporters.""" @@ -351,6 +359,8 @@ def reset(self, env_ids: Sequence[int] | None = None): deformable_object.reset(env_ids) for rigid_object in self._rigid_objects.values(): rigid_object.reset(env_ids) + for rigid_object_collection in self._rigid_object_collections.values(): + rigid_object_collection.reset(env_ids) # -- sensors for sensor in self._sensors.values(): sensor.reset(env_ids) @@ -364,6 +374,8 @@ def write_data_to_sim(self): deformable_object.write_data_to_sim() for rigid_object in self._rigid_objects.values(): rigid_object.write_data_to_sim() + for rigid_object_collection in self._rigid_object_collections.values(): + rigid_object_collection.write_data_to_sim() def update(self, dt: float) -> None: """Update the scene entities. @@ -378,6 +390,8 @@ def update(self, dt: float) -> None: deformable_object.update(dt) for rigid_object in self._rigid_objects.values(): rigid_object.update(dt) + for rigid_object_collection in self._rigid_object_collections.values(): + rigid_object_collection.update(dt) # -- sensors for sensor in self._sensors.values(): sensor.update(dt, force_recompute=not self.cfg.lazy_sensor_update) @@ -397,6 +411,7 @@ def keys(self) -> list[str]: self._articulations, self._deformable_objects, self._rigid_objects, + self._rigid_object_collections, self._sensors, self._extras, ]: @@ -422,6 +437,7 @@ def __getitem__(self, key: str) -> Any: self._articulations, self._deformable_objects, self._rigid_objects, + self._rigid_object_collections, self._sensors, self._extras, ]: @@ -454,7 +470,8 @@ def _add_entities_from_cfg(self): if asset_name in InteractiveSceneCfg.__dataclass_fields__ or asset_cfg is None: continue # resolve regex - asset_cfg.prim_path = asset_cfg.prim_path.format(ENV_REGEX_NS=self.env_regex_ns) + if hasattr(asset_cfg, "prim_path"): + asset_cfg.prim_path = asset_cfg.prim_path.format(ENV_REGEX_NS=self.env_regex_ns) # create asset if isinstance(asset_cfg, TerrainImporterCfg): # terrains are special entities since they define environment origins @@ -467,6 +484,14 @@ def _add_entities_from_cfg(self): self._deformable_objects[asset_name] = asset_cfg.class_type(asset_cfg) elif isinstance(asset_cfg, RigidObjectCfg): self._rigid_objects[asset_name] = asset_cfg.class_type(asset_cfg) + elif isinstance(asset_cfg, RigidObjectCollectionCfg): + for rigid_object_cfg in asset_cfg.rigid_objects.values(): + rigid_object_cfg.prim_path = rigid_object_cfg.prim_path.format(ENV_REGEX_NS=self.env_regex_ns) + self._rigid_object_collections[asset_name] = asset_cfg.class_type(asset_cfg) + for rigid_object_cfg in asset_cfg.rigid_objects.values(): + if hasattr(rigid_object_cfg, "collision_group") and rigid_object_cfg.collision_group == -1: + asset_paths = sim_utils.find_matching_prim_paths(rigid_object_cfg.prim_path) + self._global_prim_paths += asset_paths elif isinstance(asset_cfg, SensorBaseCfg): # Update target frame path(s)' regex name space for FrameTransformer if isinstance(asset_cfg, FrameTransformerCfg): diff --git a/source/extensions/omni.isaac.lab/test/assets/test_rigid_object_collection.py b/source/extensions/omni.isaac.lab/test/assets/test_rigid_object_collection.py new file mode 100644 index 0000000000..5674359ab0 --- /dev/null +++ b/source/extensions/omni.isaac.lab/test/assets/test_rigid_object_collection.py @@ -0,0 +1,506 @@ +# Copyright (c) 2022-2024, The Isaac Lab Project Developers. +# All rights reserved. +# +# SPDX-License-Identifier: BSD-3-Clause + +# ignore private usage of variables warning +# pyright: reportPrivateUsage=none + + +"""Launch Isaac Sim Simulator first.""" + +from omni.isaac.lab.app import AppLauncher, run_tests + +# Can set this to False to see the GUI for debugging +# This will also add lights to the scene +HEADLESS = True + +# launch omniverse app +app_launcher = AppLauncher(headless=HEADLESS) +simulation_app = app_launcher.app + +"""Rest everything follows.""" + +import ctypes +import torch +import unittest + +import omni.isaac.core.utils.prims as prim_utils + +import omni.isaac.lab.sim as sim_utils +from omni.isaac.lab.assets import RigidObjectCfg, RigidObjectCollection, RigidObjectCollectionCfg +from omni.isaac.lab.sim import build_simulation_context +from omni.isaac.lab.utils.assets import ISAAC_NUCLEUS_DIR +from omni.isaac.lab.utils.math import default_orientation, random_orientation + + +def generate_cubes_scene( + num_envs: int = 1, + num_cubes: int = 1, + height=1.0, + has_api: bool = True, + kinematic_enabled: bool = False, + device: str = "cuda:0", +) -> tuple[RigidObjectCollection, torch.Tensor]: + """Generate a scene with the provided number of cubes. + + Args: + num_envs: Number of envs to generate. + num_cubes: Number of cubes to generate. + height: Height of the cubes. + has_api: Whether the cubes have a rigid body API on them. + kinematic_enabled: Whether the cubes are kinematic. + device: Device to use for the simulation. + + Returns: + A tuple containing the rigid object representing the cubes and the origins of the cubes. + + """ + origins = torch.tensor([(i * 3.0, 0, height) for i in range(num_envs)]).to(device) + # Create Top-level Xforms, one for each cube + for i, origin in enumerate(origins): + prim_utils.create_prim(f"/World/Table_{i}", "Xform", translation=origin) + + # Resolve spawn configuration + if has_api: + spawn_cfg = sim_utils.UsdFileCfg( + usd_path=f"{ISAAC_NUCLEUS_DIR}/Props/Blocks/DexCube/dex_cube_instanceable.usd", + rigid_props=sim_utils.RigidBodyPropertiesCfg(kinematic_enabled=kinematic_enabled), + ) + else: + # since no rigid body properties defined, this is just a static collider + spawn_cfg = sim_utils.CuboidCfg( + size=(0.1, 0.1, 0.1), + collision_props=sim_utils.CollisionPropertiesCfg(), + ) + + # create the rigid object configs + cube_config_dict = {} + for i in range(num_cubes): + cube_object_cfg = RigidObjectCfg( + prim_path=f"/World/Table_.*/Object_{i}", + spawn=spawn_cfg, + init_state=RigidObjectCfg.InitialStateCfg(pos=(0.0, 3 * i, height)), + ) + cube_config_dict[f"cube_{i}"] = cube_object_cfg + # create the rigid object collection + cube_object_collection_cfg = RigidObjectCollectionCfg(rigid_objects=cube_config_dict) + cube_object_colection = RigidObjectCollection(cfg=cube_object_collection_cfg) + + return cube_object_colection, origins + + +class TestRigidObjectCollection(unittest.TestCase): + """Test for rigid object collection class.""" + + """ + Tests + """ + + def test_initialization(self): + """Test initialization for prim with rigid body API at the provided prim path.""" + for num_envs in (1, 2): + for num_cubes in (1, 3): + for device in ("cuda:0", "cpu"): + with self.subTest(num_envs=num_envs, num_cubes=num_cubes, device=device): + with build_simulation_context(device=device, auto_add_lighting=True) as sim: + # Generate cubes scene + object_collection, _ = generate_cubes_scene( + num_envs=num_envs, num_cubes=num_cubes, device=device + ) + + # Check that boundedness of rigid object is correct + self.assertEqual(ctypes.c_long.from_address(id(object_collection)).value, 1) + + # Play sim + sim.reset() + + # Check if object is initialized + self.assertTrue(object_collection.is_initialized) + self.assertEqual(len(object_collection.object_names), num_cubes) + + # Check buffers that exists and have correct shapes + self.assertEqual(object_collection.data.object_pos_w.shape, (num_envs, num_cubes, 3)) + self.assertEqual(object_collection.data.object_quat_w.shape, (num_envs, num_cubes, 4)) + self.assertEqual(object_collection.data.default_mass.shape, (num_envs, num_cubes, 1)) + self.assertEqual(object_collection.data.default_inertia.shape, (num_envs, num_cubes, 9)) + + # Simulate physics + for _ in range(2): + # perform rendering + sim.step() + # update object + object_collection.update(sim.cfg.dt) + + def test_id_conversion(self): + """Test environment and object index conversion to physics view indices.""" + for device in ("cuda:0", "cpu"): + with self.subTest(num_envs=2, num_cubes=3, device=device): + with build_simulation_context(device=device, auto_add_lighting=True) as sim: + # Generate cubes scene + object_collection, _ = generate_cubes_scene(num_envs=2, num_cubes=3, device=device) + + # Play sim + sim.reset() + + expected = [ + torch.tensor([4, 5], device=device, dtype=torch.long), + torch.tensor([4], device=device, dtype=torch.long), + torch.tensor([0, 2, 4], device=device, dtype=torch.long), + torch.tensor([1, 3, 5], device=device, dtype=torch.long), + ] + + view_ids = object_collection._env_obj_ids_to_view_ids( + object_collection._ALL_ENV_INDICES, object_collection._ALL_OBJ_INDICES[None, 2] + ) + self.assertTrue((view_ids == expected[0]).all()) + view_ids = object_collection._env_obj_ids_to_view_ids( + object_collection._ALL_ENV_INDICES[None, 0], object_collection._ALL_OBJ_INDICES[None, 2] + ) + self.assertTrue((view_ids == expected[1]).all()) + view_ids = object_collection._env_obj_ids_to_view_ids( + object_collection._ALL_ENV_INDICES[None, 0], object_collection._ALL_OBJ_INDICES + ) + self.assertTrue((view_ids == expected[2]).all()) + view_ids = object_collection._env_obj_ids_to_view_ids( + object_collection._ALL_ENV_INDICES[None, 1], object_collection._ALL_OBJ_INDICES + ) + self.assertTrue((view_ids == expected[3]).all()) + + def test_initialization_with_kinematic_enabled(self): + """Test that initialization for prim with kinematic flag enabled.""" + for num_envs in (1, 2): + for num_cubes in (1, 3): + for device in ("cuda:0", "cpu"): + with self.subTest(num_envs=num_envs, num_cubes=num_cubes, device=device): + with build_simulation_context(device=device, auto_add_lighting=True) as sim: + # Generate cubes scene + object_collection, origins = generate_cubes_scene( + num_envs=num_envs, num_cubes=num_cubes, kinematic_enabled=True, device=device + ) + + # Check that boundedness of rigid object is correct + self.assertEqual(ctypes.c_long.from_address(id(object_collection)).value, 1) + + # Play sim + sim.reset() + + # Check if object is initialized + self.assertTrue(object_collection.is_initialized) + self.assertEqual(len(object_collection.object_names), num_cubes) + + # Check buffers that exists and have correct shapes + self.assertEqual(object_collection.data.object_pos_w.shape, (num_envs, num_cubes, 3)) + self.assertEqual(object_collection.data.object_quat_w.shape, (num_envs, num_cubes, 4)) + + # Simulate physics + for _ in range(2): + # perform rendering + sim.step() + # update object + object_collection.update(sim.cfg.dt) + # check that the object is kinematic + default_object_state = object_collection.data.default_object_state.clone() + default_object_state[..., :3] += origins.unsqueeze(1) + torch.testing.assert_close(object_collection.data.object_state_w, default_object_state) + + def test_initialization_with_no_rigid_body(self): + """Test that initialization fails when no rigid body is found at the provided prim path.""" + for num_cubes in (1, 2): + for device in ("cuda:0", "cpu"): + with self.subTest(num_cubes=num_cubes, device=device): + with build_simulation_context(device=device, auto_add_lighting=True) as sim: + # Generate cubes scene + object_collection, _ = generate_cubes_scene(num_cubes=num_cubes, has_api=False, device=device) + + # Check that boundedness of rigid object is correct + self.assertEqual(ctypes.c_long.from_address(id(object_collection)).value, 1) + + # Play sim + sim.reset() + + # Check if object is initialized + self.assertFalse(object_collection.is_initialized) + + def test_external_force_on_single_body(self): + """Test application of external force on the base of the object. + + In this test, we apply a force equal to the weight of an object on the base of + one of the objects. We check that the object does not move. For the other object, + we do not apply any force and check that it falls down. + """ + for num_envs in (1, 2): + for num_cubes in (1, 4): + for device in ("cuda:0", "cpu"): + with self.subTest(num_envs=num_envs, num_cubes=num_cubes, device=device): + # Generate cubes scene + with build_simulation_context( + device=device, add_ground_plane=True, auto_add_lighting=True + ) as sim: + object_collection, origins = generate_cubes_scene( + num_envs=num_envs, num_cubes=num_cubes, device=device + ) + + # Play the simulator + sim.reset() + + # Find objects to apply the force + object_ids, object_names = object_collection.find_objects(".*") + + # Sample a force equal to the weight of the object + external_wrench_b = torch.zeros( + object_collection.num_instances, len(object_ids), 6, device=sim.device + ) + # Every 2nd cube should have a force applied to it + external_wrench_b[:, 0::2, 2] = 9.81 * object_collection.data.default_mass[:, 0::2, 0] + + # Now we are ready! + for _ in range(5): + # reset object state + object_state = object_collection.data.default_object_state.clone() + + # need to shift the position of the cubes otherwise they will be on top of each other + object_state[..., :2] += origins.unsqueeze(1)[..., :2] + object_collection.write_object_state_to_sim(object_state) + + # reset object + object_collection.reset() + + # apply force + object_collection.set_external_force_and_torque( + external_wrench_b[..., :3], external_wrench_b[..., 3:], object_ids=object_ids + ) + # perform simulation + for _ in range(10): + # apply action to the object + object_collection.write_data_to_sim() + + # perform step + sim.step() + + # update buffers + object_collection.update(sim.cfg.dt) + + # First object should still be at the same Z position (1.0) + torch.testing.assert_close( + object_collection.data.object_pos_w[:, 0::2, 2], + torch.ones_like(object_collection.data.object_pos_w[:, 0::2, 2]), + ) + # Second object should have fallen, so it's Z height should be less than initial height of 1.0 + self.assertTrue(torch.all(object_collection.data.object_pos_w[:, 1::2, 2] < 1.0)) + + def test_set_object_state(self): + """Test setting the state of the object. + + In this test, we set the state of the object to a random state and check + that the object is in that state after simulation. We set gravity to zero as + we don't want any external forces acting on the object to ensure state remains static. + """ + for num_envs in (1, 3): + for num_cubes in (1, 2): + for device in ("cuda:0", "cpu"): + with self.subTest(num_envs=num_envs, num_cubes=num_cubes, device=device): + # Turn off gravity for this test as we don't want any external forces acting on the object + # to ensure state remains static + with build_simulation_context( + device=device, gravity_enabled=False, auto_add_lighting=True + ) as sim: + # Generate cubes scene + object_collection, origins = generate_cubes_scene( + num_envs=num_envs, num_cubes=num_cubes, device=device + ) + + # Play the simulator + sim.reset() + + state_types = ["object_pos_w", "object_quat_w", "object_lin_vel_w", "object_ang_vel_w"] + + # Set each state type individually as they are dependent on each other + for state_type_to_randomize in state_types: + state_dict = { + "object_pos_w": torch.zeros_like( + object_collection.data.object_pos_w, device=sim.device + ), + "object_quat_w": default_orientation( + num=num_cubes * num_envs, device=sim.device + ).view(num_envs, num_cubes, 4), + "object_lin_vel_w": torch.zeros_like( + object_collection.data.object_lin_vel_w, device=sim.device + ), + "object_ang_vel_w": torch.zeros_like( + object_collection.data.object_ang_vel_w, device=sim.device + ), + } + + # Now we are ready! + for _ in range(5): + # reset object + object_collection.reset() + + # Set random state + if state_type_to_randomize == "object_quat_w": + state_dict[state_type_to_randomize] = random_orientation( + num=num_cubes * num_envs, device=sim.device + ).view(num_envs, num_cubes, 4) + else: + state_dict[state_type_to_randomize] = torch.randn( + num_envs, num_cubes, 3, device=sim.device + ) + # make sure objects do not overlap + if state_type_to_randomize == "object_pos_w": + state_dict[state_type_to_randomize][..., :2] += origins.unsqueeze(1)[ + ..., :2 + ] + + # perform simulation + for _ in range(5): + object_state = torch.cat( + [ + state_dict["object_pos_w"], + state_dict["object_quat_w"], + state_dict["object_lin_vel_w"], + state_dict["object_ang_vel_w"], + ], + dim=-1, + ) + # reset object state + object_collection.write_object_state_to_sim(object_state=object_state) + + sim.step() + + # assert that set object quantities are equal to the ones set in the state_dict + for key, expected_value in state_dict.items(): + value = getattr(object_collection.data, key) + torch.testing.assert_close(value, expected_value, rtol=1e-5, atol=1e-5) + + object_collection.update(sim.cfg.dt) + + def test_reset_object_collection(self): + """Test resetting the state of the rigid object.""" + for num_envs in (1, 3): + for num_cubes in (1, 2): + for device in ("cuda:0", "cpu"): + with self.subTest(num_envs=num_envs, num_cubes=num_cubes, device=device): + with build_simulation_context( + device=device, gravity_enabled=True, auto_add_lighting=True + ) as sim: + # Generate cubes scene + object_collection, _ = generate_cubes_scene( + num_envs=num_envs, num_cubes=num_cubes, device=device + ) + + # Play the simulator + sim.reset() + + for i in range(5): + # perform rendering + sim.step() + + # update object + object_collection.update(sim.cfg.dt) + + # Move the object to a random position + object_state = object_collection.data.default_object_state.clone() + object_state[..., :3] = torch.randn(num_envs, num_cubes, 3, device=sim.device) + + # Random orientation + object_state[..., 3:7] = random_orientation(num=num_cubes, device=sim.device) + object_collection.write_object_state_to_sim(object_state) + + if i % 2 == 0: + # reset object + object_collection.reset() + + # Reset should zero external forces and torques + self.assertFalse(object_collection.has_external_wrench) + self.assertEqual(torch.count_nonzero(object_collection._external_force_b), 0) + self.assertEqual(torch.count_nonzero(object_collection._external_torque_b), 0) + + def test_set_material_properties(self): + """Test getting and setting material properties of rigid object.""" + for num_envs in (1, 3): + for num_cubes in (1, 2): + for device in ("cuda:0", "cpu"): + with self.subTest(num_envs=num_envs, num_cubes=num_cubes, device=device): + with build_simulation_context( + device=device, gravity_enabled=True, add_ground_plane=True, auto_add_lighting=True + ) as sim: + # Generate cubes scene + object_collection, _ = generate_cubes_scene( + num_envs=num_envs, num_cubes=num_cubes, device=device + ) + + # Play sim + sim.reset() + + # Set material properties + static_friction = torch.FloatTensor(num_envs, num_cubes, 1).uniform_(0.4, 0.8) + dynamic_friction = torch.FloatTensor(num_envs, num_cubes, 1).uniform_(0.4, 0.8) + restitution = torch.FloatTensor(num_envs, num_cubes, 1).uniform_(0.0, 0.2) + + materials = torch.cat([static_friction, dynamic_friction, restitution], dim=-1) + + indices = torch.tensor(range(num_cubes * num_envs), dtype=torch.int) + # Add friction to cube + object_collection.root_physx_view.set_material_properties( + object_collection.reshape_data_to_view(materials), indices + ) + + # Simulate physics + sim.step() + # update object + object_collection.update(sim.cfg.dt) + + # Get material properties + materials_to_check = object_collection.root_physx_view.get_material_properties() + + # Check if material properties are set correctly + torch.testing.assert_close( + object_collection.reshape_view_to_data(materials_to_check), materials + ) + + def test_gravity_vec_w(self): + """Test that gravity vector direction is set correctly for the rigid object.""" + for num_envs in (1, 3): + for num_cubes in (1, 2): + for device in ("cuda:0", "cpu"): + for gravity_enabled in [True, False]: + with self.subTest( + num_envs=num_envs, num_cubes=num_cubes, device=device, gravity_enabled=gravity_enabled + ): + with build_simulation_context(device=device, gravity_enabled=gravity_enabled) as sim: + # Create a scene with random cubes + object_collection, _ = generate_cubes_scene( + num_envs=num_envs, num_cubes=num_cubes, device=device + ) + + # Obtain gravity direction + if gravity_enabled: + gravity_dir = (0.0, 0.0, -1.0) + else: + gravity_dir = (0.0, 0.0, 0.0) + + # Play sim + sim.reset() + + # Check that gravity is set correctly + self.assertEqual(object_collection.data.GRAVITY_VEC_W[0, 0, 0], gravity_dir[0]) + self.assertEqual(object_collection.data.GRAVITY_VEC_W[0, 0, 1], gravity_dir[1]) + self.assertEqual(object_collection.data.GRAVITY_VEC_W[0, 0, 2], gravity_dir[2]) + + # Simulate physics + for _ in range(2): + sim.step() + # update object + object_collection.update(sim.cfg.dt) + + # Expected gravity value is the acceleration of the body + gravity = torch.zeros(num_envs, num_cubes, 6, device=device) + if gravity_enabled: + gravity[..., 2] = -9.81 + # Check the body accelerations are correct + torch.testing.assert_close(object_collection.data.object_acc_w, gravity) + + +if __name__ == "__main__": + run_tests() diff --git a/source/standalone/demos/multi_asset.py b/source/standalone/demos/multi_asset.py index 6363999949..2df770d13f 100644 --- a/source/standalone/demos/multi_asset.py +++ b/source/standalone/demos/multi_asset.py @@ -23,7 +23,7 @@ # add argparse arguments parser = argparse.ArgumentParser(description="Demo on spawning different objects in multiple environments.") -parser.add_argument("--num_envs", type=int, default=1024, help="Number of environments to spawn.") +parser.add_argument("--num_envs", type=int, default=512, help="Number of environments to spawn.") # append AppLauncher cli args AppLauncher.add_app_launcher_args(parser) # parse the arguments @@ -41,7 +41,15 @@ from pxr import Gf, Sdf import omni.isaac.lab.sim as sim_utils -from omni.isaac.lab.assets import ArticulationCfg, AssetBaseCfg, RigidObjectCfg +from omni.isaac.lab.assets import ( + Articulation, + ArticulationCfg, + AssetBaseCfg, + RigidObject, + RigidObjectCfg, + RigidObjectCollection, + RigidObjectCollectionCfg, +) from omni.isaac.lab.scene import InteractiveScene, InteractiveSceneCfg from omni.isaac.lab.sim import SimulationContext from omni.isaac.lab.utils import Timer, configclass @@ -124,6 +132,52 @@ class MultiObjectSceneCfg(InteractiveSceneCfg): init_state=RigidObjectCfg.InitialStateCfg(pos=(0.0, 0.0, 2.0)), ) + # object collection + object_collection: RigidObjectCollectionCfg = RigidObjectCollectionCfg( + rigid_objects={ + "object_A": RigidObjectCfg( + prim_path="/World/envs/env_.*/Object_A", + spawn=sim_utils.SphereCfg( + radius=0.1, + visual_material=sim_utils.PreviewSurfaceCfg(diffuse_color=(1.0, 0.0, 0.0), metallic=0.2), + rigid_props=sim_utils.RigidBodyPropertiesCfg( + solver_position_iteration_count=4, solver_velocity_iteration_count=0 + ), + mass_props=sim_utils.MassPropertiesCfg(mass=1.0), + collision_props=sim_utils.CollisionPropertiesCfg(), + ), + init_state=RigidObjectCfg.InitialStateCfg(pos=(0.0, -0.5, 2.0)), + ), + "object_B": RigidObjectCfg( + prim_path="/World/envs/env_.*/Object_B", + spawn=sim_utils.CuboidCfg( + size=(0.1, 0.1, 0.1), + visual_material=sim_utils.PreviewSurfaceCfg(diffuse_color=(1.0, 0.0, 0.0), metallic=0.2), + rigid_props=sim_utils.RigidBodyPropertiesCfg( + solver_position_iteration_count=4, solver_velocity_iteration_count=0 + ), + mass_props=sim_utils.MassPropertiesCfg(mass=1.0), + collision_props=sim_utils.CollisionPropertiesCfg(), + ), + init_state=RigidObjectCfg.InitialStateCfg(pos=(0.0, 0.5, 2.0)), + ), + "object_C": RigidObjectCfg( + prim_path="/World/envs/env_.*/Object_C", + spawn=sim_utils.ConeCfg( + radius=0.1, + height=0.3, + visual_material=sim_utils.PreviewSurfaceCfg(diffuse_color=(1.0, 0.0, 0.0), metallic=0.2), + rigid_props=sim_utils.RigidBodyPropertiesCfg( + solver_position_iteration_count=4, solver_velocity_iteration_count=0 + ), + mass_props=sim_utils.MassPropertiesCfg(mass=1.0), + collision_props=sim_utils.CollisionPropertiesCfg(), + ), + init_state=RigidObjectCfg.InitialStateCfg(pos=(0.5, 0.0, 2.0)), + ), + } + ) + # articulation robot: ArticulationCfg = ArticulationCfg( prim_path="/World/envs/env_.*/Robot", @@ -170,15 +224,16 @@ def run_simulator(sim: SimulationContext, scene: InteractiveScene): """Runs the simulation loop.""" # Extract scene entities # note: we only do this here for readability. - rigid_object = scene["object"] - robot = scene["robot"] + rigid_object: RigidObject = scene["object"] + rigid_object_collection: RigidObjectCollection = scene["object_collection"] + robot: Articulation = scene["robot"] # Define simulation stepping sim_dt = sim.get_physics_dt() count = 0 # Simulation loop while simulation_app.is_running(): # Reset - if count % 500 == 0: + if count % 250 == 0: # reset counter count = 0 # reset the scene entities @@ -186,6 +241,10 @@ def run_simulator(sim: SimulationContext, scene: InteractiveScene): root_state = rigid_object.data.default_root_state.clone() root_state[:, :3] += scene.env_origins rigid_object.write_root_state_to_sim(root_state) + # object collection + object_state = rigid_object_collection.data.default_object_state.clone() + object_state[..., :3] += scene.env_origins.unsqueeze(1) + rigid_object_collection.write_object_state_to_sim(object_state) # robot # -- root state root_state = robot.data.default_root_state.clone() From 9d6594b4b360d5c48e460d5886440affd2810563 Mon Sep 17 00:00:00 2001 From: Kelly Guo Date: Sun, 17 Nov 2024 08:13:36 -0500 Subject: [PATCH 062/111] Clarifies Isaac Lab ecosystem and installation steps in documentation (#1338) # Description This change adds a new page highlighting the Isaac Lab ecosystem and relationship with Omniverse and Isaac Sim. It also clarifies the installation steps with recommendations on when each installation approach should be used. ## Type of change - This change requires a documentation update ## Checklist - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [x] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [ ] I have added tests that prove my fix is effective or that my feature works - [ ] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [ ] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --- docs/index.rst | 2 ++ docs/source/_static/setup/ecosystem-dark.jpg | Bin 0 -> 182687 bytes docs/source/_static/setup/ecosystem-light.jpg | Bin 0 -> 176206 bytes docs/source/_static/setup/verify_install.jpg | Bin 0 -> 199658 bytes .../overview/core-concepts/actuators.rst | 2 +- docs/source/overview/core-concepts/index.rst | 2 -- .../overview/developer-guide/template.rst | 34 +++++++++++++++++- docs/source/setup/ecosystem.rst | 32 +++++++++++++++++ .../installation/binaries_installation.rst | 8 ++++- docs/source/setup/installation/index.rst | 13 +++---- .../setup/installation/pip_installation.rst | 18 ++++++++-- .../standalone/tutorials/00_sim/log_time.py | 6 ++-- 12 files changed, 99 insertions(+), 18 deletions(-) create mode 100644 docs/source/_static/setup/ecosystem-dark.jpg create mode 100644 docs/source/_static/setup/ecosystem-light.jpg create mode 100644 docs/source/_static/setup/verify_install.jpg create mode 100644 docs/source/setup/ecosystem.rst diff --git a/docs/index.rst b/docs/index.rst index 2c1561104a..d5c3ad249e 100644 --- a/docs/index.rst +++ b/docs/index.rst @@ -74,7 +74,9 @@ Table of Contents :maxdepth: 2 :caption: Getting Started + source/setup/ecosystem source/setup/installation/index + source/setup/installation/cloud_installation source/setup/faq .. toctree:: diff --git 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This section we introduce core concepts in Isaac Lab. task_workflows actuators - -# motion_generators diff --git a/docs/source/overview/developer-guide/template.rst b/docs/source/overview/developer-guide/template.rst index defaa2b78c..e6c55b9b61 100644 --- a/docs/source/overview/developer-guide/template.rst +++ b/docs/source/overview/developer-guide/template.rst @@ -22,4 +22,36 @@ This template serves three distinct use cases: features and improvements in Isaac Lab. -To get started, please follow the instructions in the `extension template repository `_. +Installation +------------ + +Install Isaac Lab by following the `installation guide <../../setup/installation/index.html>`_. We recommend using the conda installation as it simplifies calling Python scripts from the terminal. + +Clone the extension template repository separately from the Isaac Lab installation (i.e. outside the IsaacLab directory): + +.. code:: bash + + # Option 1: HTTPS + git clone https://github.com/isaac-sim/IsaacLabExtensionTemplate.git + + # Option 2: SSH + git clone git@github.com:isaac-sim/IsaacLabExtensionTemplate.git + +Throughout the repository, the name ``ext_template`` only serves as an example and we provide a script to rename all the references to it automatically: + +.. code:: bash + + # Enter the repository + cd IsaacLabExtensionTemplate + + # Rename all occurrences of ext_template (in files/directories) to your_fancy_extension_name + python scripts/rename_template.py your_fancy_extension_name + +Using a python interpreter that has Isaac Lab installed, install the library: + +.. code:: bash + + python -m pip install -e exts/ext_template + + +For more details, please follow the instructions in the `extension template repository `_. diff --git a/docs/source/setup/ecosystem.rst b/docs/source/setup/ecosystem.rst new file mode 100644 index 0000000000..107c95843d --- /dev/null +++ b/docs/source/setup/ecosystem.rst @@ -0,0 +1,32 @@ +Isaac Lab Ecosystem +=================== + +Isaac Lab is built on top of Isaac Sim to provide a unified and flexible framework +for robot learning that exploits latest simulation technologies. It is designed to be modular and extensible, +and aims to simplify common workflows in robotics research (such as RL, learning from demonstrations, and +motion planning). While it includes some pre-built environments, sensors, and tasks, its main goal is to +provide an open-sourced, unified, and easy-to-use interface for developing and testing custom environments +and robot learning algorithms. + +Working with Isaac Lab requires the installation of Isaac Sim, which is packaged with core robotics tools +that Isaac Lab depends on, including URDF and MJCF importers, simulation managers, and ROS features. Isaac +Sim also builds on top of the Nvidia Omniverse platform, leveraging advanced physics simulation from PhysX, +photorealistic rendering technologies, and Universal Scene Description (USD) for scene creation. + +Isaac Lab not only inherits the capabilities of Isaac Sim, but also adds a number +of new features that pertain to robot learning research. For example, including actuator dynamics in the +simulation, procedural terrain generation, and support to collect data from human demonstrations. + +.. image:: ../_static/setup/ecosystem-light.jpg + :class: only-light + :align: center + :alt: The Isaac Lab, Isaac Sim, and Nvidia Omniverse ecosystem + +.. image:: ../_static/setup/ecosystem-dark.jpg + :class: only-dark + :align: center + :alt: The Isaac Lab, Isaac Sim, and Nvidia Omniverse ecosystem + + +For a detailed explanation of Nvidia's development journey of robot learning frameworks, please visit +the `FAQ page `_. diff --git a/docs/source/setup/installation/binaries_installation.rst b/docs/source/setup/installation/binaries_installation.rst index 9fef4f5fa3..73138ebd17 100644 --- a/docs/source/setup/installation/binaries_installation.rst +++ b/docs/source/setup/installation/binaries_installation.rst @@ -407,8 +407,14 @@ top of the repository: The above command should launch the simulator and display a window with a black -ground plane. You can exit the script by pressing ``Ctrl+C`` on your terminal. +viewport. You can exit the script by pressing ``Ctrl+C`` on your terminal. On Windows machines, please terminate the process from Command Prompt using ``Ctrl+Break`` or ``Ctrl+fn+B``. +.. figure:: ../../_static/setup/verify_install.jpg + :align: center + :figwidth: 100% + :alt: Simulator with a black window. + + If you see this, then the installation was successful! |:tada:| diff --git a/docs/source/setup/installation/index.rst b/docs/source/setup/installation/index.rst index cae19383b2..90c8937cfc 100644 --- a/docs/source/setup/installation/index.rst +++ b/docs/source/setup/installation/index.rst @@ -1,5 +1,5 @@ -Installation Guide -=================== +Local Installation +================== .. image:: https://img.shields.io/badge/IsaacSim-4.2.0-silver.svg :target: https://developer.nvidia.com/isaac-sim @@ -31,14 +31,9 @@ Installation Guide For the full list of system requirements for Isaac Sim, please refer to the `Isaac Sim system requirements `_. -As an experimental feature since Isaac Sim 4.0 release, Isaac Sim can also be installed through pip. -This simplifies the installation -process by avoiding the need to download the Omniverse Launcher and installing Isaac Sim through -the launcher. Therefore, there are two ways to install Isaac Lab: .. toctree:: :maxdepth: 2 - Option 1: Installation using Isaac Sim pip - Option 2: Installation using Isaac Sim binaries - cloud_installation + Pip installation (recommended for Ubuntu 22.04 and Windows) + Binary installation (recommended for Ubuntu 20.04) diff --git a/docs/source/setup/installation/pip_installation.rst b/docs/source/setup/installation/pip_installation.rst index cc014fd887..b0ddf378d0 100644 --- a/docs/source/setup/installation/pip_installation.rst +++ b/docs/source/setup/installation/pip_installation.rst @@ -88,7 +88,14 @@ compatibility issues with some Linux distributions. If you encounter any issues, pip install --upgrade pip -- Then, install the Isaac Sim packages necessary for running Isaac Lab: +- Then, install the Isaac Sim package + + .. code-block:: bash + + pip install isaacsim==4.2.0.2 --extra-index-url https://pypi.nvidia.com + + +- To install a minimal set of packages for running Isaac Lab only, the following command can be used. Note that you cannot run ``isaacsim`` with this. .. code-block:: bash @@ -310,8 +317,15 @@ top of the repository: The above command should launch the simulator and display a window with a black -ground plane. You can exit the script by pressing ``Ctrl+C`` on your terminal. +viewport as shown below. You can exit the script by pressing ``Ctrl+C`` on your terminal. On Windows machines, please terminate the process from Command Prompt using ``Ctrl+Break`` or ``Ctrl+fn+B``. + +.. figure:: ../../_static/setup/verify_install.jpg + :align: center + :figwidth: 100% + :alt: Simulator with a black window. + + If you see this, then the installation was successful! |:tada:| diff --git a/source/standalone/tutorials/00_sim/log_time.py b/source/standalone/tutorials/00_sim/log_time.py index e55c9f2a62..f47d96222a 100644 --- a/source/standalone/tutorials/00_sim/log_time.py +++ b/source/standalone/tutorials/00_sim/log_time.py @@ -40,12 +40,14 @@ def main(): """Main function.""" # Specify that the logs must be in logs/docker_tutorial - log_dir_path = os.path.join("logs", "docker_tutorial") + log_dir_path = os.path.join("logs") + if not os.path.isdir(log_dir_path): + os.mkdir(log_dir_path) # In the container, the absolute path will be # /workspace/isaaclab/logs/docker_tutorial, because # all python execution is done through /workspace/isaaclab/isaaclab.sh # and the calling process' path will be /workspace/isaaclab - log_dir_path = os.path.abspath(log_dir_path) + log_dir_path = os.path.abspath(os.path.join(log_dir_path, "docker_tutorial")) if not os.path.isdir(log_dir_path): os.mkdir(log_dir_path) print(f"[INFO] Logging experiment to directory: {log_dir_path}") From b3ecfe3d3cd494ad6a43951d579f7b1735d3ec41 Mon Sep 17 00:00:00 2001 From: Kelly Guo Date: Sun, 17 Nov 2024 09:12:20 -0500 Subject: [PATCH 063/111] Fixes indexing bug in write_joint_limits_to_sim (#1401) # Description This change fixes bugs in Articulation class `write_joint_limits_to_sim` method, where previously env_ids and joint_ids were not taken into account when ids passed in are not None. ## Type of change - Bug fix (non-breaking change which fixes an issue) ## Checklist - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [ ] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [x] I have added tests that prove my fix is effective or that my feature works - [x] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [x] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --- .../omni.isaac.lab/config/extension.toml | 2 +- .../omni.isaac.lab/docs/CHANGELOG.rst | 9 +++++++ .../lab/assets/articulation/articulation.py | 9 +++++-- .../test/assets/test_articulation.py | 24 +++++++++++++++++++ 4 files changed, 41 insertions(+), 3 deletions(-) diff --git a/source/extensions/omni.isaac.lab/config/extension.toml b/source/extensions/omni.isaac.lab/config/extension.toml index df78987189..9141590e3e 100644 --- a/source/extensions/omni.isaac.lab/config/extension.toml +++ b/source/extensions/omni.isaac.lab/config/extension.toml @@ -1,7 +1,7 @@ [package] # Note: Semantic Versioning is used: https://semver.org/ -version = "0.27.14" +version = "0.27.15" # Description title = "Isaac Lab framework for Robot Learning" diff --git a/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst b/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst index df775535be..3050693e4b 100644 --- a/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst +++ b/source/extensions/omni.isaac.lab/docs/CHANGELOG.rst @@ -1,6 +1,15 @@ Changelog --------- +0.27.15 (2024-11-09) +~~~~~~~~~~~~~~~~~~~~ + +Fixed +^^^^^ + +* Fixed indexing in :meth:`omni.isaac.lab.assets.Articulation.write_joint_limits_to_sim` to correctly process non-None ``env_ids`` and ``joint_ids``. + + 0.27.14 (2024-10-23) ~~~~~~~~~~~~~~~~~~~~ diff --git a/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/articulation/articulation.py b/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/articulation/articulation.py index d744f3387f..86b76fb881 100644 --- a/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/articulation/articulation.py +++ b/source/extensions/omni.isaac.lab/omni/isaac/lab/assets/articulation/articulation.py @@ -540,8 +540,13 @@ def write_joint_limits_to_sim( # set into internal buffers self._data.joint_limits[env_ids, joint_ids] = limits # update default joint pos to stay within the new limits - if torch.any((self._data.default_joint_pos < limits[..., 0]) | (self._data.default_joint_pos > limits[..., 1])): - self._data.default_joint_pos = torch.clamp(self._data.default_joint_pos, limits[..., 0], limits[..., 1]) + if torch.any( + (self._data.default_joint_pos[env_ids, joint_ids] < limits[..., 0]) + | (self._data.default_joint_pos[env_ids, joint_ids] > limits[..., 1]) + ): + self._data.default_joint_pos[env_ids, joint_ids] = torch.clamp( + self._data.default_joint_pos[env_ids, joint_ids], limits[..., 0], limits[..., 1] + ) omni.log.warn( "Some default joint positions are outside of the range of the new joint limits. Default joint positions" " will be clamped to be within the new joint limits." diff --git a/source/extensions/omni.isaac.lab/test/assets/test_articulation.py b/source/extensions/omni.isaac.lab/test/assets/test_articulation.py index da0b9accf6..5a4dd898e8 100644 --- a/source/extensions/omni.isaac.lab/test/assets/test_articulation.py +++ b/source/extensions/omni.isaac.lab/test/assets/test_articulation.py @@ -572,6 +572,18 @@ def test_joint_limits(self): torch.testing.assert_close(articulation._data.joint_limits, limits) torch.testing.assert_close(articulation._data.default_joint_pos, default_joint_pos) + # Set new joint limits with indexing + env_ids = torch.arange(1, device=device) + joint_ids = torch.arange(2, device=device) + limits = torch.zeros(env_ids.shape[0], joint_ids.shape[0], 2, device=device) + limits[..., 0] = (torch.rand(env_ids.shape[0], joint_ids.shape[0], device=device) + 5.0) * -1.0 + limits[..., 1] = torch.rand(env_ids.shape[0], joint_ids.shape[0], device=device) + 5.0 + articulation.write_joint_limits_to_sim(limits, env_ids=env_ids, joint_ids=joint_ids) + + # Check new limits are in place + torch.testing.assert_close(articulation._data.joint_limits[env_ids][:, joint_ids], limits) + torch.testing.assert_close(articulation._data.default_joint_pos, default_joint_pos) + # Set new joint limits that invalidate default joint pos limits = torch.zeros(num_articulations, articulation.num_joints, 2, device=device) limits[..., 0] = torch.rand(num_articulations, articulation.num_joints, device=device) * -0.1 @@ -584,6 +596,18 @@ def test_joint_limits(self): ) self.assertTrue(torch.all(within_bounds)) + # Set new joint limits that invalidate default joint pos with indexing + limits = torch.zeros(env_ids.shape[0], joint_ids.shape[0], 2, device=device) + limits[..., 0] = torch.rand(env_ids.shape[0], joint_ids.shape[0], device=device) * -0.1 + limits[..., 1] = torch.rand(env_ids.shape[0], joint_ids.shape[0], device=device) * 0.1 + articulation.write_joint_limits_to_sim(limits, env_ids=env_ids, joint_ids=joint_ids) + + # Check if all values are within the bounds + within_bounds = ( + articulation._data.default_joint_pos[env_ids][:, joint_ids] >= limits[..., 0] + ) & (articulation._data.default_joint_pos[env_ids][:, joint_ids] <= limits[..., 1]) + self.assertTrue(torch.all(within_bounds)) + def test_external_force_on_single_body(self): """Test application of external force on the base of the articulation.""" for num_articulations in (1, 2): From d603b67fd190eb3cc5c86d71b0a0aeadef5ad1be Mon Sep 17 00:00:00 2001 From: Kelly Guo Date: Thu, 21 Nov 2024 13:50:11 -0500 Subject: [PATCH 064/111] Updates code for release 1.3.0 (#1444) # Description Updates code for release 1.3.0 --------- Signed-off-by: Kelly Guo Co-authored-by: David Hoeller --- README.md | 27 +++- VERSION | 2 +- .../rl_existing_scripts.rst | 133 +++++++++--------- source/apps/isaaclab.python.headless.kit | 2 +- .../isaaclab.python.headless.rendering.kit | 2 +- source/apps/isaaclab.python.kit | 2 +- source/apps/isaaclab.python.rendering.kit | 2 +- 7 files changed, 93 insertions(+), 77 deletions(-) diff --git a/README.md b/README.md index 04f5106105..a46cd89d8f 100644 --- a/README.md +++ b/README.md @@ -13,13 +13,28 @@ [![License](https://img.shields.io/badge/license-BSD--3-yellow.svg)](https://opensource.org/licenses/BSD-3-Clause) -**Isaac Lab** is a unified and modular framework for robot learning that aims to simplify common workflows -in robotics research (such as RL, learning from demonstrations, and motion planning). It is built upon -[NVIDIA Isaac Sim](https://docs.omniverse.nvidia.com/isaacsim/latest/overview.html) to leverage the latest -simulation capabilities for photo-realistic scenes and fast and accurate simulation. +**Isaac Lab** is a GPU-accelerated, open-source framework designed to unify and simplify robotics research workflows, such as reinforcement learning, imitation learning, and motion planning. Built on [NVIDIA Isaac Sim](https://docs.omniverse.nvidia.com/isaacsim/latest/overview.html), it combines fast and accurate physics and sensor simulation, making it an ideal choice for sim-to-real transfer in robotics. + +Isaac Lab provides developers with a range of essential features for accurate sensor simulation, such as RTX-based cameras, LIDAR, or contact sensors. The framework's GPU acceleration enables users to run complex simulations and computations faster, which is key for iterative processes like reinforcement learning and data-intensive tasks. Moreover, Isaac Lab can run locally or be distributed across the cloud, offering flexibility for large-scale deployments. + +## Key Features + +Isaac Lab offers a comprehensive set of tools and environments designed to facilitate robot learning: +- **Robots**: A diverse collection of robots, from manipulators, quadrupeds, to humanoids, with 16 commonly available models. +- **Environments**: Ready-to-train implementations of more than 30 environments, which can be trained with popular reinforcement learning frameworks such as RSL RL, SKRL, RL Games, or Stable Baselines. We also support multi-agent reinforcement learning. +- **Physics**: Rigid bodies, articulated systems, deformable objects +- **Sensors**: RGB/depth/segmentation cameras, camera annotations, IMU, contact sensors, ray casters. + + +## Getting Started + +Our [documentation page](https://isaac-sim.github.io/IsaacLab) provides everything you need to get started, including detailed tutorials and step-by-step guides. Follow these links to learn more about: + +- [Installation steps](https://isaac-sim.github.io/IsaacLab/main/source/setup/installation/index.html#local-installation) +- [Reinforcement learning](https://isaac-sim.github.io/IsaacLab/main/source/overview/reinforcement-learning/rl_existing_scripts.html) +- [Tutorials](https://isaac-sim.github.io/IsaacLab/main/source/tutorials/index.html) +- [Available environments](https://isaac-sim.github.io/IsaacLab/main/source/overview/environments.html) -Please refer to our [documentation page](https://isaac-sim.github.io/IsaacLab) to learn more about the -installation steps, features, tutorials, and how to set up your project with Isaac Lab. ## Contributing to Isaac Lab diff --git a/VERSION b/VERSION index 26aaba0e86..f0bb29e763 100644 --- a/VERSION +++ b/VERSION @@ -1 +1 @@ -1.2.0 +1.3.0 diff --git a/docs/source/overview/reinforcement-learning/rl_existing_scripts.rst b/docs/source/overview/reinforcement-learning/rl_existing_scripts.rst index 6cc88137f2..6ee865fd36 100644 --- a/docs/source/overview/reinforcement-learning/rl_existing_scripts.rst +++ b/docs/source/overview/reinforcement-learning/rl_existing_scripts.rst @@ -4,12 +4,12 @@ Reinforcement Learning Wrappers We provide wrappers to different reinforcement libraries. These wrappers convert the data from the environments into the respective libraries function argument and return types. -Stable-Baselines3 ------------------ + +RL-Games +-------- - Training an agent with - `Stable-Baselines3 `__ - on ``Isaac-Cartpole-v0``: + `RL-Games `__ on ``Isaac-Ant-v0``: .. tab-set:: :sync-group: os @@ -19,30 +19,65 @@ Stable-Baselines3 .. code:: bash - # install python module (for stable-baselines3) - ./isaaclab.sh -i sb3 + # install python module (for rl-games) + ./isaaclab.sh -i rl_games # run script for training - # note: we set the device to cpu since SB3 doesn't optimize for GPU anyway - ./isaaclab.sh -p source/standalone/workflows/sb3/train.py --task Isaac-Cartpole-v0 --headless --device cpu + ./isaaclab.sh -p source/standalone/workflows/rl_games/train.py --task Isaac-Ant-v0 --headless # run script for playing with 32 environments - ./isaaclab.sh -p source/standalone/workflows/sb3/play.py --task Isaac-Cartpole-v0 --num_envs 32 --checkpoint /PATH/TO/model.zip + ./isaaclab.sh -p source/standalone/workflows/rl_games/play.py --task Isaac-Ant-v0 --num_envs 32 --checkpoint /PATH/TO/model.pth # run script for recording video of a trained agent (requires installing `ffmpeg`) - ./isaaclab.sh -p source/standalone/workflows/sb3/play.py --task Isaac-Cartpole-v0 --headless --video --video_length 200 + ./isaaclab.sh -p source/standalone/workflows/rl_games/play.py --task Isaac-Ant-v0 --headless --video --video_length 200 .. tab-item:: :icon:`fa-brands fa-windows` Windows :sync: windows .. code:: batch - :: install python module (for stable-baselines3) - isaaclab.bat -i sb3 + :: install python module (for rl-games) + isaaclab.bat -i rl_games :: run script for training - :: note: we set the device to cpu since SB3 doesn't optimize for GPU anyway - isaaclab.bat -p source\standalone\workflows\sb3\train.py --task Isaac-Cartpole-v0 --headless --device cpu + isaaclab.bat -p source\standalone\workflows\rl_games\train.py --task Isaac-Ant-v0 --headless :: run script for playing with 32 environments - isaaclab.bat -p source\standalone\workflows\sb3\play.py --task Isaac-Cartpole-v0 --num_envs 32 --checkpoint /PATH/TO/model.zip + isaaclab.bat -p source\standalone\workflows\rl_games\play.py --task Isaac-Ant-v0 --num_envs 32 --checkpoint /PATH/TO/model.pth :: run script for recording video of a trained agent (requires installing `ffmpeg`) - isaaclab.bat -p source\standalone\workflows\sb3\play.py --task Isaac-Cartpole-v0 --headless --video --video_length 200 + isaaclab.bat -p source\standalone\workflows\rl_games\play.py --task Isaac-Ant-v0 --headless --video --video_length 200 + +RSL-RL +------ + +- Training an agent with + `RSL-RL `__ on ``Isaac-Reach-Franka-v0``: + + .. tab-set:: + :sync-group: os + + .. tab-item:: :icon:`fa-brands fa-linux` Linux + :sync: linux + + .. code:: bash + + # install python module (for rsl-rl) + ./isaaclab.sh -i rsl_rl + # run script for training + ./isaaclab.sh -p source/standalone/workflows/rsl_rl/train.py --task Isaac-Reach-Franka-v0 --headless + # run script for playing with 32 environments + ./isaaclab.sh -p source/standalone/workflows/rsl_rl/play.py --task Isaac-Reach-Franka-v0 --num_envs 32 --load_run run_folder_name --checkpoint model.pt + # run script for recording video of a trained agent (requires installing `ffmpeg`) + ./isaaclab.sh -p source/standalone/workflows/rsl_rl/play.py --task Isaac-Reach-Franka-v0 --headless --video --video_length 200 + + .. tab-item:: :icon:`fa-brands fa-windows` Windows + :sync: windows + + .. code:: batch + + :: install python module (for rsl-rl) + isaaclab.bat -i rsl_rl + :: run script for training + isaaclab.bat -p source\standalone\workflows\rsl_rl\train.py --task Isaac-Reach-Franka-v0 --headless + :: run script for playing with 32 environments + isaaclab.bat -p source\standalone\workflows\rsl_rl\play.py --task Isaac-Reach-Franka-v0 --num_envs 32 --load_run run_folder_name --checkpoint model.pt + :: run script for recording video of a trained agent (requires installing `ffmpeg`) + isaaclab.bat -p source\standalone\workflows\rsl_rl\play.py --task Isaac-Reach-Franka-v0 --headless --video --video_length 200 SKRL ---- @@ -129,48 +164,12 @@ SKRL :: run script for playing with 32 environments with the MAPPO algorithm (IPPO is also supported) isaaclab.bat -p source\standalone\workflows\skrl\play.py --task Isaac-Shadow-Hand-Over-Direct-v0 --num_envs 32 --algorithm MAPPO --checkpoint /PATH/TO/model.pt -RL-Games --------- - -- Training an agent with - `RL-Games `__ on ``Isaac-Ant-v0``: - - .. tab-set:: - :sync-group: os - - .. tab-item:: :icon:`fa-brands fa-linux` Linux - :sync: linux - - .. code:: bash - - # install python module (for rl-games) - ./isaaclab.sh -i rl_games - # run script for training - ./isaaclab.sh -p source/standalone/workflows/rl_games/train.py --task Isaac-Ant-v0 --headless - # run script for playing with 32 environments - ./isaaclab.sh -p source/standalone/workflows/rl_games/play.py --task Isaac-Ant-v0 --num_envs 32 --checkpoint /PATH/TO/model.pth - # run script for recording video of a trained agent (requires installing `ffmpeg`) - ./isaaclab.sh -p source/standalone/workflows/rl_games/play.py --task Isaac-Ant-v0 --headless --video --video_length 200 - - .. tab-item:: :icon:`fa-brands fa-windows` Windows - :sync: windows - - .. code:: batch - - :: install python module (for rl-games) - isaaclab.bat -i rl_games - :: run script for training - isaaclab.bat -p source\standalone\workflows\rl_games\train.py --task Isaac-Ant-v0 --headless - :: run script for playing with 32 environments - isaaclab.bat -p source\standalone\workflows\rl_games\play.py --task Isaac-Ant-v0 --num_envs 32 --checkpoint /PATH/TO/model.pth - :: run script for recording video of a trained agent (requires installing `ffmpeg`) - isaaclab.bat -p source\standalone\workflows\rl_games\play.py --task Isaac-Ant-v0 --headless --video --video_length 200 - -RSL-RL ------- +Stable-Baselines3 +----------------- - Training an agent with - `RSL-RL `__ on ``Isaac-Reach-Franka-v0``: + `Stable-Baselines3 `__ + on ``Isaac-Cartpole-v0``: .. tab-set:: :sync-group: os @@ -180,28 +179,30 @@ RSL-RL .. code:: bash - # install python module (for rsl-rl) - ./isaaclab.sh -i rsl_rl + # install python module (for stable-baselines3) + ./isaaclab.sh -i sb3 # run script for training - ./isaaclab.sh -p source/standalone/workflows/rsl_rl/train.py --task Isaac-Reach-Franka-v0 --headless + # note: we set the device to cpu since SB3 doesn't optimize for GPU anyway + ./isaaclab.sh -p source/standalone/workflows/sb3/train.py --task Isaac-Cartpole-v0 --headless --device cpu # run script for playing with 32 environments - ./isaaclab.sh -p source/standalone/workflows/rsl_rl/play.py --task Isaac-Reach-Franka-v0 --num_envs 32 --load_run run_folder_name --checkpoint model.pt + ./isaaclab.sh -p source/standalone/workflows/sb3/play.py --task Isaac-Cartpole-v0 --num_envs 32 --checkpoint /PATH/TO/model.zip # run script for recording video of a trained agent (requires installing `ffmpeg`) - ./isaaclab.sh -p source/standalone/workflows/rsl_rl/play.py --task Isaac-Reach-Franka-v0 --headless --video --video_length 200 + ./isaaclab.sh -p source/standalone/workflows/sb3/play.py --task Isaac-Cartpole-v0 --headless --video --video_length 200 .. tab-item:: :icon:`fa-brands fa-windows` Windows :sync: windows .. code:: batch - :: install python module (for rsl-rl) - isaaclab.bat -i rsl_rl + :: install python module (for stable-baselines3) + isaaclab.bat -i sb3 :: run script for training - isaaclab.bat -p source\standalone\workflows\rsl_rl\train.py --task Isaac-Reach-Franka-v0 --headless + :: note: we set the device to cpu since SB3 doesn't optimize for GPU anyway + isaaclab.bat -p source\standalone\workflows\sb3\train.py --task Isaac-Cartpole-v0 --headless --device cpu :: run script for playing with 32 environments - isaaclab.bat -p source\standalone\workflows\rsl_rl\play.py --task Isaac-Reach-Franka-v0 --num_envs 32 --load_run run_folder_name --checkpoint model.pt + isaaclab.bat -p source\standalone\workflows\sb3\play.py --task Isaac-Cartpole-v0 --num_envs 32 --checkpoint /PATH/TO/model.zip :: run script for recording video of a trained agent (requires installing `ffmpeg`) - isaaclab.bat -p source\standalone\workflows\rsl_rl\play.py --task Isaac-Reach-Franka-v0 --headless --video --video_length 200 + isaaclab.bat -p source\standalone\workflows\sb3\play.py --task Isaac-Cartpole-v0 --headless --video --video_length 200 All the scripts above log the training progress to `Tensorboard`_ in the ``logs`` directory in the root of the repository. The logs directory follows the pattern ``logs///``, where ```` diff --git a/source/apps/isaaclab.python.headless.kit b/source/apps/isaaclab.python.headless.kit index 3435606b7b..9d13464ecf 100644 --- a/source/apps/isaaclab.python.headless.kit +++ b/source/apps/isaaclab.python.headless.kit @@ -5,7 +5,7 @@ [package] title = "Isaac Lab Python Headless" description = "An app for running Isaac Lab headlessly" -version = "1.2.0" +version = "1.3.0" # That makes it browsable in UI with "experience" filter keywords = ["experience", "app", "isaaclab", "python", "headless"] diff --git a/source/apps/isaaclab.python.headless.rendering.kit b/source/apps/isaaclab.python.headless.rendering.kit index 0e808021ee..cd39d0a797 100644 --- a/source/apps/isaaclab.python.headless.rendering.kit +++ b/source/apps/isaaclab.python.headless.rendering.kit @@ -9,7 +9,7 @@ [package] title = "Isaac Lab Python Headless Camera" description = "An app for running Isaac Lab headlessly with rendering enabled" -version = "1.2.0" +version = "1.3.0" # That makes it browsable in UI with "experience" filter keywords = ["experience", "app", "isaaclab", "python", "camera", "minimal"] diff --git a/source/apps/isaaclab.python.kit b/source/apps/isaaclab.python.kit index fdf924a6ad..7ea6fc1a05 100644 --- a/source/apps/isaaclab.python.kit +++ b/source/apps/isaaclab.python.kit @@ -5,7 +5,7 @@ [package] title = "Isaac Lab Python" description = "An app for running Isaac Lab" -version = "1.2.0" +version = "1.3.0" # That makes it browsable in UI with "experience" filter keywords = ["experience", "app", "usd"] diff --git a/source/apps/isaaclab.python.rendering.kit b/source/apps/isaaclab.python.rendering.kit index abd272a5fe..38a48b7460 100644 --- a/source/apps/isaaclab.python.rendering.kit +++ b/source/apps/isaaclab.python.rendering.kit @@ -9,7 +9,7 @@ [package] title = "Isaac Lab Python Camera" description = "An app for running Isaac Lab with rendering enabled" -version = "1.2.0" +version = "1.3.0" # That makes it browsable in UI with "experience" filter keywords = ["experience", "app", "isaaclab", "python", "camera", "minimal"] From 4d9914702d84577b59dc468485c6e31f61dcbfde Mon Sep 17 00:00:00 2001 From: Michael Gussert Date: Mon, 25 Nov 2024 10:22:46 -0600 Subject: [PATCH 065/111] Adds documentation and example scripts for sensors (#1443) ## Checklist - [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with `./isaaclab.sh --format` - [x] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [x] I have added tests that prove my fix is effective or that my feature works - [x] I have updated the changelog and the corresponding version in the extension's `config/extension.toml` file - [x] I have added my name to the `CONTRIBUTORS.md` or my name already exists there --------- Signed-off-by: Michael Gussert Co-authored-by: David Hoeller Co-authored-by: Kelly Guo --- docs/index.rst | 3 +- .../overview_sensors_contact_diagram.png | Bin 0 -> 130992 bytes .../overview/overview_sensors_depth.png | Bin 0 -> 27471 bytes .../overview_sensors_frame_transformer.png | Bin 0 -> 124527 bytes .../overview_sensors_ft_visualizer.png | Bin 0 -> 288346 bytes .../overview/overview_sensors_instance.png | Bin 0 -> 9940 bytes .../overview/overview_sensors_instanceID.png | Bin 0 -> 9871 bytes .../overview/overview_sensors_normals.png | Bin 0 -> 23251 bytes .../overview/overview_sensors_rc_patterns.png | Bin 0 -> 278121 bytes .../overview_sensors_rc_visualizer.png | Bin 0 -> 1623591 bytes .../_static/overview/overview_sensors_rgb.png | Bin 0 -> 214522 bytes .../overview/overview_sensors_semantic.png | Bin 0 -> 9795 bytes .../sensors/camera.rst} | 77 +++++--- .../overview/sensors/contact_sensor.rst | 145 +++++++++++++++ .../overview/sensors/frame_transformer.rst | 158 ++++++++++++++++ docs/source/overview/sensors/index.rst | 20 ++ docs/source/overview/sensors/ray_caster.rst | 108 +++++++++++ .../lab/assets/rigid_object/rigid_object.py | 3 + .../demos/sensors/contact_sensor.py | 176 ++++++++++++++++++ .../demos/sensors/frame_transformer_sensor.py | 170 +++++++++++++++++ .../demos/sensors/raycaster_sensor.py | 160 ++++++++++++++++ 21 files changed, 994 insertions(+), 26 deletions(-) create mode 100644 docs/source/_static/overview/overview_sensors_contact_diagram.png create mode 100644 docs/source/_static/overview/overview_sensors_depth.png create mode 100644 docs/source/_static/overview/overview_sensors_frame_transformer.png create mode 100644 docs/source/_static/overview/overview_sensors_ft_visualizer.png create mode 100644 docs/source/_static/overview/overview_sensors_instance.png create mode 100644 docs/source/_static/overview/overview_sensors_instanceID.png create mode 100644 docs/source/_static/overview/overview_sensors_normals.png create mode 100644 docs/source/_static/overview/overview_sensors_rc_patterns.png create mode 100644 docs/source/_static/overview/overview_sensors_rc_visualizer.png create mode 100644 docs/source/_static/overview/overview_sensors_rgb.png create mode 100644 docs/source/_static/overview/overview_sensors_semantic.png rename docs/source/{features/tiled_rendering.rst => overview/sensors/camera.rst} (68%) create mode 100644 docs/source/overview/sensors/contact_sensor.rst create mode 100644 docs/source/overview/sensors/frame_transformer.rst create mode 100644 docs/source/overview/sensors/index.rst create mode 100644 docs/source/overview/sensors/ray_caster.rst create mode 100644 source/standalone/demos/sensors/contact_sensor.py create mode 100644 source/standalone/demos/sensors/frame_transformer_sensor.py create mode 100644 source/standalone/demos/sensors/raycaster_sensor.py diff --git a/docs/index.rst b/docs/index.rst index d5c3ad249e..7acde411ec 100644 --- a/docs/index.rst +++ b/docs/index.rst @@ -86,6 +86,7 @@ Table of Contents source/overview/developer-guide/index source/overview/core-concepts/index + source/overview/sensors/index source/overview/environments source/overview/reinforcement-learning/index source/overview/teleop_imitation @@ -98,7 +99,7 @@ Table of Contents source/features/hydra source/features/multi_gpu - source/features/tiled_rendering + Tiled Rendering source/features/reproducibility .. toctree:: diff --git a/docs/source/_static/overview/overview_sensors_contact_diagram.png b/docs/source/_static/overview/overview_sensors_contact_diagram.png new file mode 100644 index 0000000000000000000000000000000000000000..91b05c51fa850b93c2f42181bffa7fa36bda3016 GIT binary patch literal 130992 zcmeEug;$ha7w^z0k}8O#ga`^K2m(V4N~544Ii%7pF~razV9+6rlt|YMB_W_7-7$cm z(y63?z&$hI_j=d5f5P=$>sktaWU`78tiAy-t8QG-B8tRWCW zDpF$bn@+xxR0!laTTw>(v75olBuR3##&GK|LDo8vdvp;Lw2$*LNUw*~7)d+u8WBCy zcyTr(BmLU78^80?*k z=KR(3idUlvcdtYrCnKW;^a#POr~jxP1+8%Y{Q&}D^(VE)``?eOXaE0CC(QVl6R=Lq zPKUH;$?BUzNTW`afZht@UyiZnFi!g1m8>^@{aCCx>#<~U;9z}0K}?=rivbzr*Xt76 zzc02_SWXU`FBNfC5lvqRME(6WYtG?LH{ag&sy@2?)if6lIm^&hmIp9(70$_|+ce*X@u(T7;W)|9(rgxumB#-0g^1E1aE8 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