Overview#
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 efficient simulation. The core objectives of the framework are:
Modularity: Easily customize and add new environments, robots, and sensors.
Agility: Adapt to the changing needs of the community.
Openness: Remain open-sourced to allow the community to contribute and extend the framework.
Battery-included: Include a number of environments, sensors, and tasks that are ready to use.
Key features available in Isaac Lab include fast and accurate physics simulation provided by PhysX, tiled rendering APIs for vectorized rendering, domain randomization for improving robustness and adaptability, and support for running in the cloud.
For more information about the framework, please refer to the paper [MYY+23]. For clarifications on NVIDIA Isaac ecosystem, please check out the Frequently Asked Questions section.
License#
The Isaac Lab framework is open-sourced under the BSD-3-Clause license. Please refer to License for more details.
Acknowledgement#
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}
}
Table of Contents#
Getting Started
Features
Resources
Source API
Migration Guides
References