PyRoki

Project page • arXiv • Code

PyRoki is a library for robot kinematic optimization (Python Robot Kinematics).

  1. Modular: Optimization variables and cost functions are decoupled, enabling reusable components across tasks. Objectives like collision avoidance and pose matching can be applied to both IK and trajectory optimization without reimplementation.

  2. Extensible: PyRoki supports automatic differentiation for user-defined costs with Jacobian computation, a real-time cost-weight tuning interface, and optional analytical Jacobians for performance-critical use cases.

  3. Cross-Platform: PyRoki runs on CPU, GPU, and TPU, allowing efficient scaling from single-robot use cases to large-scale parallel processing for motion datasets or planning.

We demonstrate how PyRoki solves IK, trajectory optimization, and motion retargeting for robot hands and humanoids in a unified framework. It uses a Levenberg-Marquardt optimizer to efficiently solve these tasks, and we evaluate its performance on batched IK.

Features include:

  • Differentiable robot forward kinematics model from a URDF.

  • Automatic generation of robot collision primitives (e.g., capsules).

  • Differentiable collision bodies with numpy broadcasting logic.

  • Common cost factors (e.g., end effector pose, self/world-collision, manipulability).

  • Arbitrary costs, getting Jacobians either calculated through autodiff or defined manually.

  • Integration with a Levenberg-Marquardt Solver.

  • Cross-platform support (CPU, GPU, TPU).

Installation

You can install pyroki with pip, with Python 3.12+:

git clone https://github.com/chungmin99/pyroki.git
cd pyroki
pip install -e .

Examples

Examples

Acknowledgements

PyRoki is heavily inspired by the prior work, including but not limited to Trac-IK, cuRobo, pink, mink, Drake, and Dex-Retargeting. Thank you so much for your great work!

Citation

If you find this work useful, please cite it as follows:

@article{pyroki2025,
author = {Kim, Chung Min* and Yi, Brent* and Choi, Hongsuk and Ma, Yi and Goldberg, Ken and Kanazawa, Angjoo},
title = {PyRoki: A Modular Toolkit for Robot Kinematic Optimization},
journal = {arXiv},
year = {2025},
}

Thanks for using PyRoki!