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 to leverage the latest simulation capabilities for photo-realistic scenes and fast and accurate simulation.
Please refer to our documentation page to learn more about the installation steps, features, tutorials, and how to set up your project with Isaac Lab.
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.
# spawn the R1 robot and set random joint positions
python3 source/standalone/galaxea/basic/spawn_robot.py
# create a scene consisting of object, table, robot and so on
python3 source/standalone/galaxea/basic/creat_scene.py
python3 source/standalone/galaxea/basic/follow_target_diff_ik.py 
python3 source/standalone/galaxea/basic/follow_target_diff_ik.py 
#start to collected pick and place fruit data via Galaxea R1-DVT robot
python3 source/standalone/galaxea/rule_based_policy/collect_demos.py --enable_cameras
python3 source/standalone/workflows/robomimic/collect_demonstrations.pypython3 source/standalone/galaxea/scripted_policy/lift.pyPlease see the troubleshooting section for common fixes or submit an issue.
For issues related to Isaac Sim, we recommend checking its documentation or opening a question on its forums.
- Please use GitHub Discussions for discussing ideas, asking questions, and requests for new features.
- Github Issues should only be used to track executable pieces of work with a definite scope and a clear deliverable. These can be fixing bugs, documentation issues, new features, or general updates.
The Isaac Lab framework is released under BSD-3 License. The license files of its dependencies and assets are present in the docs/licenses directory.
Isaac Lab development initiated from the Orbit framework. We would appreciate if you would cite it in academic publications as well:
@article{mittal2023orbit,
author={Mittal, Mayank and Yu, Calvin and Yu, Qinxi and Liu, Jingzhou and Rudin, Nikita and Hoeller, David and Yuan, Jia Lin and Singh, Ritvik and Guo, Yunrong and Mazhar, Hammad and Mandlekar, Ajay and Babich, Buck and State, Gavriel and Hutter, Marco and Garg, Animesh},
journal={IEEE Robotics and Automation Letters},
title={Orbit: A Unified Simulation Framework for Interactive Robot Learning Environments},
year={2023},
volume={8},
number={6},
pages={3740-3747},
doi={10.1109/LRA.2023.3270034}
}