From 2246042dc9637616b3c7c86d540d5dc979fdd72c Mon Sep 17 00:00:00 2001 From: peng Date: Mon, 23 Sep 2024 03:52:54 -0500 Subject: [PATCH] reconstruct --- .gitignore | 7 ++ 404.html | 25 +++++ Gemfile | 35 ++++++ Gemfile.lock | 189 ++++++++++++++++++++++++++++++++ README.md | 287 ++----------------------------------------------- _config.yml | 54 ++++++++++ annotation.md | 11 ++ download.md | 91 ++++++++++++++++ index.markdown | 26 +++++ platform.md | 19 ++++ 10 files changed, 463 insertions(+), 281 deletions(-) create mode 100644 .gitignore create mode 100644 404.html create mode 100644 Gemfile create mode 100644 Gemfile.lock create mode 100644 _config.yml create mode 100644 annotation.md create mode 100644 download.md create mode 100644 index.markdown create mode 100644 platform.md diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..74a9223 --- /dev/null +++ b/.gitignore @@ -0,0 +1,7 @@ +_site/ +.sass-cache/ +.jekyll-cache/ +.jekyll-metadata +# Ignore folders generated by Bundler +.bundle/ +vendor/ diff --git a/404.html b/404.html new file mode 100644 index 0000000..086a5c9 --- /dev/null +++ b/404.html @@ -0,0 +1,25 @@ +--- +permalink: /404.html +layout: default +--- + + + +
+

404

+ +

Page not found :(

+

The requested page could not be found.

+
diff --git a/Gemfile b/Gemfile new file mode 100644 index 0000000..248a276 --- /dev/null +++ b/Gemfile @@ -0,0 +1,35 @@ +source "https://rubygems.org" +# Hello! This is where you manage which Jekyll version is used to run. +# When you want to use a different version, change it below, save the +# file and run `bundle install`. Run Jekyll with `bundle exec`, like so: +# +# bundle exec jekyll serve +# +# This will help ensure the proper Jekyll version is running. +# Happy Jekylling! +gem "jekyll", "~> 4.3.4" +# This is the default theme for new Jekyll sites. You may change this to anything you like. +gem "minima", "~> 2.5" +# If you want to use GitHub Pages, remove the "gem "jekyll"" above and +# uncomment the line below. To upgrade, run `bundle update github-pages`. +# gem "github-pages", group: :jekyll_plugins +# If you have any plugins, put them here! +group :jekyll_plugins do + gem "jekyll-feed", "~> 0.12" +end + +# Windows and JRuby does not include zoneinfo files, so bundle the tzinfo-data gem +# and associated library. +platforms :mingw, :x64_mingw, :mswin, :jruby do + gem "tzinfo", ">= 1", "< 3" + gem "tzinfo-data" +end + +# Performance-booster for watching directories on Windows +gem "wdm", "~> 0.1", :platforms => [:mingw, :x64_mingw, :mswin] + +# Lock `http_parser.rb` gem to `v0.6.x` on JRuby builds since newer versions of the gem +# do not have a Java counterpart. +gem "http_parser.rb", "~> 0.6.0", :platforms => [:jruby] + +gem 'eventmachine', :git => 'https://github.com/eventmachine/eventmachine.git', :branch => 'master' diff --git a/Gemfile.lock b/Gemfile.lock new file mode 100644 index 0000000..f414e41 --- /dev/null +++ b/Gemfile.lock @@ -0,0 +1,189 @@ +GIT + remote: https://github.com/eventmachine/eventmachine.git + revision: e7320417cf291cc6a69471a64ecae5ddb5367715 + branch: master + specs: + eventmachine (1.3.0.dev.1) + +GEM + remote: https://rubygems.org/ + specs: + addressable (2.8.7) + public_suffix (>= 2.0.2, < 7.0) + bigdecimal (3.1.8) + colorator (1.1.0) + concurrent-ruby (1.3.4) + em-websocket (0.5.3) + eventmachine (>= 0.12.9) + http_parser.rb (~> 0) + ffi (1.17.0) + ffi (1.17.0-aarch64-linux-gnu) + ffi (1.17.0-aarch64-linux-musl) + ffi (1.17.0-arm-linux-gnu) + ffi (1.17.0-arm-linux-musl) + ffi (1.17.0-arm64-darwin) + ffi (1.17.0-x86-linux-gnu) + ffi (1.17.0-x86-linux-musl) + ffi (1.17.0-x86_64-darwin) + ffi (1.17.0-x86_64-linux-gnu) + ffi (1.17.0-x86_64-linux-musl) + forwardable-extended (2.6.0) + google-protobuf (4.28.2) + bigdecimal + rake (>= 13) + google-protobuf (4.28.2-aarch64-linux) + bigdecimal + rake (>= 13) + google-protobuf (4.28.2-arm64-darwin) + bigdecimal + rake (>= 13) + google-protobuf (4.28.2-x86-linux) + bigdecimal + rake (>= 13) + google-protobuf (4.28.2-x86_64-darwin) + bigdecimal + rake (>= 13) + google-protobuf (4.28.2-x86_64-linux) + bigdecimal + rake (>= 13) + http_parser.rb (0.8.0) + i18n (1.14.6) + concurrent-ruby (~> 1.0) + jekyll (4.3.4) + addressable (~> 2.4) + colorator (~> 1.0) + em-websocket (~> 0.5) + i18n (~> 1.0) + jekyll-sass-converter (>= 2.0, < 4.0) + jekyll-watch (~> 2.0) + kramdown (~> 2.3, >= 2.3.1) + kramdown-parser-gfm (~> 1.0) + liquid (~> 4.0) + mercenary (>= 0.3.6, < 0.5) + pathutil (~> 0.9) + rouge (>= 3.0, < 5.0) + safe_yaml (~> 1.0) + terminal-table (>= 1.8, < 4.0) + webrick (~> 1.7) + jekyll-feed (0.17.0) + jekyll (>= 3.7, < 5.0) + jekyll-sass-converter (3.0.0) + sass-embedded (~> 1.54) + jekyll-seo-tag (2.8.0) + jekyll (>= 3.8, < 5.0) + jekyll-watch (2.2.1) + listen (~> 3.0) + kramdown (2.4.0) + rexml + kramdown-parser-gfm (1.1.0) + kramdown (~> 2.0) + liquid (4.0.4) + listen (3.9.0) + rb-fsevent (~> 0.10, >= 0.10.3) + rb-inotify (~> 0.9, >= 0.9.10) + mercenary 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google-protobuf (~> 4.27) + sass-embedded (1.79.2-riscv64-linux-gnu) + google-protobuf (~> 4.27) + sass-embedded (1.79.2-riscv64-linux-musl) + google-protobuf (~> 4.27) + sass-embedded (1.79.2-x86-cygwin) + google-protobuf (~> 4.27) + sass-embedded (1.79.2-x86-linux-android) + google-protobuf (~> 4.27) + sass-embedded (1.79.2-x86-linux-gnu) + google-protobuf (~> 4.27) + sass-embedded (1.79.2-x86-linux-musl) + google-protobuf (~> 4.27) + sass-embedded (1.79.2-x86-mingw-ucrt) + google-protobuf (~> 4.27) + sass-embedded (1.79.2-x86_64-cygwin) + google-protobuf (~> 4.27) + sass-embedded (1.79.2-x86_64-darwin) + google-protobuf (~> 4.27) + sass-embedded (1.79.2-x86_64-linux-android) + google-protobuf (~> 4.27) + sass-embedded (1.79.2-x86_64-linux-gnu) + google-protobuf (~> 4.27) + sass-embedded (1.79.2-x86_64-linux-musl) + google-protobuf (~> 4.27) + terminal-table (3.0.2) + unicode-display_width (>= 1.1.1, < 3) + unicode-display_width (2.6.0) + webrick (1.8.1) + +PLATFORMS + aarch64-linux + aarch64-linux-android + aarch64-linux-gnu + aarch64-linux-musl + aarch64-mingw-ucrt + arm-linux-androideabi + arm-linux-gnu + arm-linux-gnueabihf + arm-linux-musl + arm-linux-musleabihf + arm64-darwin + riscv64-linux-android + riscv64-linux-gnu + riscv64-linux-musl + ruby + x86-cygwin + x86-linux + x86-linux-android + x86-linux-gnu + x86-linux-musl + x86-mingw-ucrt + x86_64-cygwin + x86_64-darwin + x86_64-linux + x86_64-linux-android + x86_64-linux-gnu + x86_64-linux-musl + +DEPENDENCIES + eventmachine! + http_parser.rb (~> 0.6.0) + jekyll (~> 4.3.4) + jekyll-feed (~> 0.12) + minima (~> 2.5) + tzinfo (>= 1, < 3) + tzinfo-data + wdm (~> 0.1) + +BUNDLED WITH + 2.5.19 diff --git a/README.md b/README.md index 05c5467..1dc0782 100644 --- a/README.md +++ b/README.md @@ -1,284 +1,9 @@ - -

The Great Outdoors Dataset: Off-Road Multi-Modal Dataset

- -

-Texas A&M University    The DEVCOM Army Research Laboratory

-

- Peng Jiang1, Philip Osteen2, Maggie Wigness2 and Srikanth Saripalli1
-1. Texas A&M University;  2. CCDC Army Research Laboratory
- -

+# god_dataset_site +""" +Install [jekyll](https://jekyllrb.com/) - -## Overview -The Great Outdoors Dataset: Off-Road Multi-Modal Dataset is a comprehensive resource aimed at advancing autonomous navigation research in challenging off-road environments. Collected using an unmanned ground vehicle (UGV) designed for unstructured terrain, this dataset offers a rich combination of sensor data to support robust and safe navigation. The sensor setup includes a 64-channel LiDAR for detailed 3D point cloud generation, multiple RGB cameras for high-resolution visual capture, and a thermal camera for infrared imaging in low-visibility or night-time conditions. In addition, the dataset features data from an inertial navigation system (INS) that provides accurate motion and orientation measurements, a 2D mmWave radar for enhanced perception in adverse weather conditions, and an RTK GPS system for precise geolocation. The Great Outdoors Dataset places a strong emphasis on semantic scene understanding, addressing the gap in off-road autonomy research by offering multimodal data with annotated labels for 3D semantic segmentation. Unlike many existing datasets that focus on urban environments, this dataset is specifically tailored for off-road applications, providing a crucial resource for the development of advanced machine learning models and sensor fusion techniques. By building on the foundation of [RELLIS-3D](https://github.com/unmannedlab/RELLIS-3D), it is designed to push the boundaries of autonomous navigation in unstructured environments, enabling the development of algorithms that can effectively navigate and perceive the complex dynamics of off-road settings. +bundle config set path "vendor/bundle" +bundle install -![LiDAR Scans Statics](./images/GOD_image.png) - -### Recording Platform -* [Clearpath Robobtics Warthog](https://clearpathrobotics.com/warthog-unmanned-ground-vehicle-robot/) - -### Sensor Setup -* 64 channels Lidar: [Ouster OS1](https://ouster.com/products/os1-lidar-sensor) -* 3 RGB Camera: [Basler acA1920-50gc](https://www.baslerweb.com/en/products/cameras/area-scan-cameras/ace/aca1920-50gc/) + [Edmund Optics 16mm/F1.8 86-571](https://www.edmundoptics.com/p/16mm-focal-length-hp-series-fixed-focal-length-lens/28990/) -* Thermal Camera: [FLIR Boson 640](https://www.flir.com/products/boson/?model=20640A032&vertical=lwir&segment=oem) -* Inertial Navigation System (IMU/GPS): [MicroStrain 3DM-GX5-AHRS](http://www.microstrain.com/inertial-sensors/3dm-gx5-25) -* 2D mmwave RADAR: [Navtech CTS350-X](https://navtechradar.com/radar-solutions/radar-for-intelligent-transport-solutions/clearway-technical-specification/) -* RTK GPS: [Saprkfun RTK Facet](https://www.sparkfun.com/products/19984) - -![Sensor Setup Illustration](./images/3D_arl.png) - -3D scan of the sensor setup.([Download](https://drive.google.com/file/d/1lTc4GO6WiOHxn7cqnY3baj5yh7qnQ5oX/view?usp=sharing)) - -## Folder structure - -
-The Great Outdoors Dataset
-├── pt_test.lst
-├── pt_val.lst
-├── pt_train.lst
-├── 00000
-      ├── os1_cloud_node_kitti_bin/             -- directory containing ".bin" files with Ouster 64-Channels point clouds.  
-      ├── nav_radar_node/       -- directory containing radar polar images.
-      ├── pylon_camera_node/    -- directory containing ".png" files from the color camera.  
-      ├── pylon_camera_node_label_color -- color image lable
-      ├── pylon_camera_node_label_id -- id image lable
-      ├──  lwir_camera_node/    -- directory containing ".png" files from the thermal camera.  
-      ├── lwir_camera_node_label_color -- color image lable
-      ├── lwir_camera_node_label_id -- id image lable
-      └── poses.txt             -- file containing the poses of every scan.
-
- - -## Annotated Data: -### Ontology: -To provide multi-modal data for enhancing autonomous off-road navigation, we developed an ontology of object and terrain classes that extends the foundation of the [RELLIS-3D dataset](https://github.com/unmannedlab/RELLIS-3D), while incorporating additional terrain and object categories specific to our dataset. Notably, our sequences introduce new classes such as gravel and mulch, which were absent in RELLIS-3D. Overall, the dataset encompasses 22 distinct classes, including trees, grass, dirt, sky, gravel, bush, mulch, water, poles, fences, persons, buildings, objects, vehicles, barriers, mud, concrete, puddles, rubble, asphalt, and a void class. This expanded ontology provides a more comprehensive understanding of off-road environments, offering enriched data for advanced semantic segmentation and improved performance in challenging, unstructured terrains. - -**Ontology Definition** ([Ontology](./images/GOD_Ontology.png)) - -### Images Statics: - -![Images Statics](./images/God_stat.png) - - -### RGB Image Download: - -**Image with Annotation Examples** ([Download](https://drive.google.com/file/d/1oi5KpBYXefvMpiUzrVE1BWcPfmMieTdx/view?usp=sharing)) - -**Full Images** ([Download](https://drive.google.com/file/d/1Y_XHZw6BeuqwD280K7xw4eapNRpSKXA5/view?usp=sharing)) - -**Full Image Annotations Color Format** ([Download](https://drive.google.com/file/d/1qc4J1DgiWU0MsUhUhyX0p8sQROoVb4uZ/view?usp=sharing)) - -**Full Image Annotations ID Format** ([Download](https://drive.google.com/file/d/1VehRXZ_Bw4DolGVvqVk4qr_pmbUXYgQA/view?usp=sharing)) - -### Thermal Image Download: - -**Full Images** ([Download](https://drive.google.com/file/d/1kTwL7O_v4Qc8WpzpT7416VXgENYm1ZK-/view?usp=sharing)) - -**Full Image Annotations Color Format** ([Download](https://drive.google.com/file/d/1g6Hf7-wg3JqQMDufhpHCyGK-cPrkQ7Ck/view?usp=sharing)) - -**Full Image Annotations ID Format** ([Download](https://drive.google.com/file/d/1u_cRN-SkU2b_M5pWCRU0rL4_RkCTUTsA/view?usp=sharing)) - -### LiDAR Data -**Synced LiDAR Pointcloud Semantic-KITTI Format** ([Download]()) - -### RADAR Data -**Synced RADAR Polar Images** ([Download](https://drive.google.com/file/d/1KC56g3GriVsIA5rkKCFA7mqBWeuZL9PQ/view?usp=sharing)) - - -### Calibration Download: -**Camera Instrinsic** ([Download 2KB](https://drive.google.com/file/d/1I489hMmcnly5gwao6YC2I0wnOcL8W96w/view?usp=sharing)) - -**RGB Cameras to Ouster LiDAR** ([Download 3KB](https://drive.google.com/file/d/1JZPWwZa7wA6mN_Qv8ze7_535D-xo8Zex/view?usp=sharing)) - -**Boson Thermal to RGB camera** ([Download 3KB](https://drive.google.com/file/d/1bal8q-ytdc8od2wV9nXW9-fKIPbGuNau/view?usp=sharing)) - - - -## ROS Bag Raw Data - -Data included in raw ROS bagfiles: - -Topic Name | Message Tpye | Message Descriptison ------------- | ------------- | --------------------------------- -/Navtech/FFTData | nav_ross/HighPrecisionFFTData | Radar FFT data -/lester/imu/data | sensor_msgs/Imu | Filtered imu data from embeded imu of Warthog -/lester/imu/data_raw | sensor_msgs/Imu | Raw imu data from embeded imu of Warthog -/img_node/intensity_image | sensor_msgs/Image | Intensity image generated by ouster Lidar -/lester/imu/mag | sensor_msgs/MagneticField | Raw magnetic field data from embeded imu of Warthog -/lester/lidar_points | sensor_msgs/PointCloud2 | Point cloud data from Ouster Lidar -/lester/ouster_center/imu | sensor_msgs/Imu | Raw imu data from embeded imu of Ouster Lidar -/lester/lidar_points_center | sensor_msgs/PointCloud2 | Centered point cloud data from Ouster Lidar -/lester/lwir_front/camera_info | sensor_msgs/CameraInfo | Intrinsics of thermal camera -/lester/lwir_front/image_rect/compressed | sensor_msgs/CompressedImage | sensor_msgs/Imu | Raw imu data from embeded imu of Ouster Lidar -/lester/stereo_left/camera_info | sensor_msgs/CameraInfo -/lester/stereo_left/image_rect_color/compressed | sensor_msgs/CompressedImage | Image from left RGB camera -/lester/stereo_right/camera_info | sensor_msgs/CameraInfo -/lester/stereo_right/image_rect_color/compressed | sensor_msgs/CompressedImage | Image from right RGB camera -/lester/rear_center/camera_info | sensor_msgs/CameraInfo -/lester/rear_center/image_rect_color/compressed | sensor_msgs/CompressedImage | Image from rear RGB camera -/lester/ublox/fix | sensor_msgs/NavSatFix | INS data from ublox -lester/right_drive/status/battery_current | std_msgs/Float64 | -lester/right_drive/status/battery_voltage | std_msgs/Float64 | -lester/left_drive/status/battery_current | std_msgs/Float64 | -lester/left_drive/status/battery_voltage | std_msgs/Float64 | -/lester/rc_teleop/cmd_vel | geometry_msgs/Twist | RC input to warthog -/tf | tf2_msgs/TFMessage | -/tf_static | tf2_msgs/TFMessage - -### ROS Bag Download -The following is the link to the rosbag.([Download](https://drive.google.com/file/d/1aze9xgbN1ID-9CW4U3CJtYi6ChBmaKGO/view?usp=sharing)) - -![Warthog in RVIZ](images/platform_ros.png) - -## Collaborator -The DEVCOM Army Research Laboratory - - -## Related Work - - -[A RUGD Dataset for Autonomous Navigation and Visual Perception inUnstructured Outdoor Environments](http://rugd.vision/) - -[RELLIS-3D Dataset](https://github.com/unmannedlab/RELLIS-3D) \ No newline at end of file +bundle exec jekyll serve" \ No newline at end of file diff --git a/_config.yml b/_config.yml new file mode 100644 index 0000000..3cb8cf8 --- /dev/null +++ b/_config.yml @@ -0,0 +1,54 @@ +# Welcome to Jekyll! +# +# This config file is meant for settings that affect your whole blog, values +# which you are expected to set up once and rarely edit after that. If you find +# yourself editing this file very often, consider using Jekyll's data files +# feature for the data you need to update frequently. +# +# For technical reasons, this file is *NOT* reloaded automatically when you use +# 'bundle exec jekyll serve'. If you change this file, please restart the server process. +# +# If you need help with YAML syntax, here are some quick references for you: +# https://learn-the-web.algonquindesign.ca/topics/markdown-yaml-cheat-sheet/#yaml +# https://learnxinyminutes.com/docs/yaml/ +# +# Site settings +# These are used to personalize your new site. If you look in the HTML files, +# you will see them accessed via {{ site.title }}, {{ site.email }}, and so on. +# You can create any custom variable you would like, and they will be accessible +# in the templates via {{ site.myvariable }}. + +title: The Great Outdoors Dataset +description: The Great Outdoors Dataset Off-Road Multi-Modal Dataset +baseurl: "" # leave this blank for GitHub Pages +url: "https://yourusername.github.io/repositoryname" # Replace with your GitHub Pages URL + + +# Build settings +theme: minima +plugins: + - jekyll-feed +markdown: kramdown + +kramdown: + math_engine: mathjax + syntax_highlighter: rouge +# Exclude from processing. +# The following items will not be processed, by default. +# Any item listed under the `exclude:` key here will be automatically added to +# the internal "default list". +# +# Excluded items can be processed by explicitly listing the directories or +# their entries' file path in the `include:` list. +# +# exclude: +# - .sass-cache/ +# - .jekyll-cache/ +# - gemfiles/ +# - Gemfile +# - Gemfile.lock +# - node_modules/ +# - vendor/bundle/ +# - vendor/cache/ +# - vendor/gems/ +# - vendor/ruby/ diff --git a/annotation.md b/annotation.md new file mode 100644 index 0000000..3a705b1 --- /dev/null +++ b/annotation.md @@ -0,0 +1,11 @@ +--- +layout: default +title: Annotation +--- + +## Annotated Data: +To provide multi-modal data for enhancing autonomous off-road navigation, we developed an ontology of object and terrain classes that extends the foundation of the [RELLIS-3D dataset](https://github.com/unmannedlab/RELLIS-3D), while incorporating additional terrain and object categories specific to our dataset. Notably, our sequences introduce new classes such as gravel and mulch, which were absent in RELLIS-3D. Overall, the dataset encompasses 22 distinct classes, including **trees, grass, dirt, sky, gravel, bush, mulch, water, poles, fences, persons, buildings, objects, vehicles, barriers, mud, concrete, puddles, rubble, asphalt, and a void class**. This expanded ontology provides a more comprehensive understanding of off-road environments, offering enriched data for advanced semantic segmentation and improved performance in challenging, unstructured terrains. + +### Images Statics: + +![Images Statics](./images/God_stat.png) \ No newline at end of file diff --git a/download.md b/download.md new file mode 100644 index 0000000..0720a0c --- /dev/null +++ b/download.md @@ -0,0 +1,91 @@ +--- +layout: default +title: Download +--- + +## Folder structure + +
+The Great Outdoors Dataset
+├── pt_test.lst
+├── pt_val.lst
+├── pt_train.lst
+├── 00000
+      ├── os1_cloud_node_kitti_bin/             -- directory containing ".bin" files with Ouster 64-Channels point clouds.  
+      ├── nav_radar_node/       -- directory containing radar polar images.
+      ├── pylon_camera_node/    -- directory containing ".png" files from the color camera.  
+      ├── pylon_camera_node_label_color -- color image lable
+      ├── pylon_camera_node_label_id -- id image lable
+      ├──  lwir_camera_node/    -- directory containing ".png" files from the thermal camera.  
+      ├── lwir_camera_node_label_color -- color image lable
+      ├── lwir_camera_node_label_id -- id image lable
+      └── poses.txt             -- file containing the poses of every scan.
+
+ +## Ontology Download: +- **Ontology Definition** ([Ontology](./images/GOD_Ontology.png)) + +## RGB Image Download: + +- **Image with Annotation Examples** ([Download](https://drive.google.com/file/d/1oi5KpBYXefvMpiUzrVE1BWcPfmMieTdx/view?usp=sharing)) + +- **Full Images** ([Download](https://drive.google.com/file/d/1Y_XHZw6BeuqwD280K7xw4eapNRpSKXA5/view?usp=sharing)) + +- **Full Image Annotations Color Format** ([Download](https://drive.google.com/file/d/1qc4J1DgiWU0MsUhUhyX0p8sQROoVb4uZ/view?usp=sharing)) + +- **Full Image Annotations ID Format** ([Download](https://drive.google.com/file/d/1VehRXZ_Bw4DolGVvqVk4qr_pmbUXYgQA/view?usp=sharing)) + +## Thermal Image Download: + +- **Full Images** ([Download](https://drive.google.com/file/d/1kTwL7O_v4Qc8WpzpT7416VXgENYm1ZK-/view?usp=sharing)) + +- **Full Image Annotations Color Format** ([Download](https://drive.google.com/file/d/1g6Hf7-wg3JqQMDufhpHCyGK-cPrkQ7Ck/view?usp=sharing)) + +- **Full Image Annotations ID Format** ([Download](https://drive.google.com/file/d/1u_cRN-SkU2b_M5pWCRU0rL4_RkCTUTsA/view?usp=sharing)) + +## LiDAR Data +- **Synced LiDAR Pointcloud Semantic-KITTI** ([Download]()) + +## RADAR Data +- **Synced RADAR Polar Images** ([Download](https://drive.google.com/file/d/1KC56g3GriVsIA5rkKCFA7mqBWeuZL9PQ/view?usp=sharing)) + +## Calibration Download: +- **Camera Instrinsic** ([Download 2KB](https://drive.google.com/file/d/1I489hMmcnly5gwao6YC2I0wnOcL8W96w/view?usp=sharing)) + +- **RGB Cameras to Ouster LiDAR** ([Download 3KB](https://drive.google.com/file/d/1JZPWwZa7wA6mN_Qv8ze7_535D-xo8Zex/view?usp=sharing)) + +- **Boson Thermal to RGB camera** ([Download 3KB](https://drive.google.com/file/d/1bal8q-ytdc8od2wV9nXW9-fKIPbGuNau/view?usp=sharing)) + + +## ROS Bag Raw Data +The following is the link to the rosbag.([Download](https://drive.google.com/file/d/1aze9xgbN1ID-9CW4U3CJtYi6ChBmaKGO/view?usp=sharing)) + +Data included in raw ROS bagfiles: + +Topic Name | Message Tpye | Message Descriptison +------------ | ------------- | --------------------------------- +/Navtech/FFTData | nav_ross/HighPrecisionFFTData | Radar FFT data +/lester/imu/data | sensor_msgs/Imu | Filtered imu data from embeded imu of Warthog +/lester/imu/data_raw | sensor_msgs/Imu | Raw imu data from embeded imu of Warthog +/img_node/intensity_image | sensor_msgs/Image | Intensity image generated by ouster Lidar +/lester/imu/mag | sensor_msgs/MagneticField | Raw magnetic field data from embeded imu of Warthog +/lester/lidar_points | sensor_msgs/PointCloud2 | Point cloud data from Ouster Lidar +/lester/ouster_center/imu | sensor_msgs/Imu | Raw imu data from embeded imu of Ouster Lidar +/lester/lidar_points_center | sensor_msgs/PointCloud2 | Centered point cloud data from Ouster Lidar +/lester/lwir_front/camera_info | sensor_msgs/CameraInfo | Intrinsics of thermal camera +/lester/lwir_front/image_rect/compressed | sensor_msgs/CompressedImage | sensor_msgs/Imu | Raw imu data from embeded imu of Ouster Lidar +/lester/stereo_left/camera_info | sensor_msgs/CameraInfo +/lester/stereo_left/image_rect_color/compressed | sensor_msgs/CompressedImage | Image from left RGB camera +/lester/stereo_right/camera_info | sensor_msgs/CameraInfo +/lester/stereo_right/image_rect_color/compressed | sensor_msgs/CompressedImage | Image from right RGB camera +/lester/rear_center/camera_info | sensor_msgs/CameraInfo +/lester/rear_center/image_rect_color/compressed | sensor_msgs/CompressedImage | Image from rear RGB camera +/lester/ublox/fix | sensor_msgs/NavSatFix | INS data from ublox +lester/right_drive/status/battery_current | std_msgs/Float64 | +lester/right_drive/status/battery_voltage | std_msgs/Float64 | +lester/left_drive/status/battery_current | std_msgs/Float64 | +lester/left_drive/status/battery_voltage | std_msgs/Float64 | +/lester/rc_teleop/cmd_vel | geometry_msgs/Twist | RC input to warthog +/tf | tf2_msgs/TFMessage | +/tf_static | tf2_msgs/TFMessage + diff --git a/index.markdown b/index.markdown new file mode 100644 index 0000000..cc00556 --- /dev/null +++ b/index.markdown @@ -0,0 +1,26 @@ +--- +layout: default +title: Home +--- + + +

The Great Outdoors Dataset: Off-Road Multi-Modal Dataset

+ +

+ + Texas A&M University +    + + The DEVCOM Army Research Laboratory + +

+ + +The Great Outdoors Dataset: Off-Road Multi-Modal Dataset is a comprehensive resource aimed at advancing autonomous navigation research in challenging off-road environments. Collected using an unmanned ground vehicle (UGV) designed for unstructured terrain, this dataset offers a rich combination of sensor data to support robust and safe navigation. The sensor setup includes a 64-channel LiDAR for detailed 3D point cloud generation, multiple RGB cameras for high-resolution visual capture, and a thermal camera for infrared imaging in low-visibility or night-time conditions. In addition, the dataset features data from an inertial navigation system (INS) that provides accurate motion and orientation measurements, a 2D mmWave radar for enhanced perception in adverse weather conditions, and an RTK GPS system for precise geolocation. The Great Outdoors Dataset places a strong emphasis on semantic scene understanding, addressing the gap in off-road autonomy research by offering multimodal data with annotated labels for 3D semantic segmentation. Unlike many existing datasets that focus on urban environments, this dataset is specifically tailored for off-road applications, providing a crucial resource for the development of advanced machine learning models and sensor fusion techniques. By building on the foundation of [RELLIS-3D](https://github.com/unmannedlab/RELLIS-3D), it is designed to push the boundaries of autonomous navigation in unstructured environments, enabling the development of algorithms that can effectively navigate and perceive the complex dynamics of off-road settings. + + +![LiDAR Scans Statics](./images/GOD_image.png) + +### Collaborators: +- [Texas A&M University](https://www.tamu.edu/): Peng Jiang, Kasi Viswanath, Akhil Nagariya, George Chustz, Srikanth Saripalli +- [CCDC Army Research Laboratory](https://www.arl.army.mil/) Maggie Wigness, Philip Osteen, Tim Overbye, Christian Ellis, Long Quang \ No newline at end of file diff --git a/platform.md b/platform.md new file mode 100644 index 0000000..d11fc78 --- /dev/null +++ b/platform.md @@ -0,0 +1,19 @@ +--- +layout: default +title: Platform +--- + +### Recording Platform +* [Clearpath Robobtics Warthog](https://clearpathrobotics.com/warthog-unmanned-ground-vehicle-robot/) + +### Sensor Setup +* 64 channels Lidar: [Ouster OS1](https://ouster.com/products/os1-lidar-sensor) +* 3 RGB Camera: [Basler acA1920-50gc](https://www.baslerweb.com/en/products/cameras/area-scan-cameras/ace/aca1920-50gc/) + [Edmund Optics 16mm/F1.8 86-571](https://www.edmundoptics.com/p/16mm-focal-length-hp-series-fixed-focal-length-lens/28990/) +* Thermal Camera: [FLIR Boson 640](https://www.flir.com/products/boson/?model=20640A032&vertical=lwir&segment=oem) +* Inertial Navigation System (IMU/GPS): [MicroStrain 3DM-GX5-AHRS](http://www.microstrain.com/inertial-sensors/3dm-gx5-25) +* 2D mmwave RADAR: [Navtech CTS350-X](https://navtechradar.com/radar-solutions/radar-for-intelligent-transport-solutions/clearway-technical-specification/) +* RTK GPS: [Saprkfun RTK Facet](https://www.sparkfun.com/products/19984) + +![Sensor Setup Illustration](./images/3D_arl.png) + +3D scan of the sensor setup.([Download](https://drive.google.com/file/d/1lTc4GO6WiOHxn7cqnY3baj5yh7qnQ5oX/view?usp=sharing)) \ No newline at end of file