Orbit 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, and tutorials.
We're excited to announce merging of our latest development branch into the main branch! This update introduces several improvements and fixes to enhance the modularity and user-friendliness of the framework. We have added several new environments, especially for legged locomotion, and are in the process of adding new environments.
Feel free to explore the latest changes and updates. We appreciate your ongoing support and contributions!
For more details, please check the post here: #106
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.
Please 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.
NVIDIA Isaac Sim is available freely under individual license. For more information about its license terms, please check here.
Orbit framework is released under BSD-3 License. The license files of its dependencies and assets are present in the docs/licenses directory.
Please cite this paper if you use this framework in your work:
@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}
}