cuRobo

CUDA Accelerated Robot Library

Documentation | Paper

[!NOTE] cuRoboV2 is a significant rewrite and the public API has changed from cuRobo v1. If you depend on the v1 API, pin to the v0.7.8 tag.

cuRobo is a CUDA-accelerated library for robot motion generation, built on PyTorch, CUDA, and Warp. It provides GPU-parallel algorithms for forward/inverse kinematics, collision checking, trajectory optimization, geometric planning, GPU-native perception, and whole-body motion generation, scaling from single-arm manipulators to high-DoF humanoids.

Key capabilities:

• Dynamics-aware trajectory optimization with B-spline representation enforcing smoothness and torque limits
• GPU-native ESDF perception that generates dense signed distance fields from depth images, up to 10x faster than state-of-the-art
• Scalable whole-body computation including topology-aware kinematics, differentiable inverse dynamics, and map-reduce self-collision for high-DoF robots
• Collision-free motion generation combining IK, geometric planning, and trajectory optimization.

Citation

If you found this work useful, please cite cuRoboV2,

@misc{curobo_v2,
      title={cuRoboV2: Dynamics-Aware Motion Generation with Depth-Fused Distance Fields for High-DoF Robots},
      author={Balakumar Sundaralingam and Adithyavairavan Murali and Stan Birchfield},
      year={2026},
      eprint={2603.05493},
      archivePrefix={arXiv},
      primaryClass={cs.RO}
}

Contributing

Contributions are welcome. Bugs: open an issue. General usage questions: GitHub Discussions. For pull requests, please read CONTRIBUTING.md. All commits must include a DCO sign-off (git commit -s).

License

cuRobo is released under the Apache 2.0 license.

The example robot assets bundled in this repository are provided under their respective licenses. See LICENSE_ASSETS for details.

Third-Party Software

This project will download and install additional third-party open source software projects. Review the license terms of these open source projects before use.