`PyRoki`: Python Robot Kinematics Library

Project page • arXiv

PyRoki is a modular, extensible, and cross-platform toolkit for kinematic optimization, all in Python.

Core 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 implementations (e.g., end effector pose, self/world-collision, manipulability).
Arbitrary costs, autodiff or analytical Jacobians.
Integration with a Levenberg-Marquardt Solver.
Cross-platform support (CPU, GPU, TPU).

Please refer to the documentation for more details, features, and usage examples.

Installation

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

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

Status

May 6, 2025: Initial release

We are preparing and will release by May 16, 2025:

Examples + documentation for hand / humanoid motion retargeting
Documentation for using manually defined Jacobians.
Support with python 3.10+

Citation

This codebase is released with the following preprint.

Chung Min Kim*, Brent Yi*, Hongsuk Choi, Yi Ma, Ken Goldberg, Angjoo Kanazawa. PyRoki: A Modular Toolkit for Robot Kinematic Optimization arXiV, 2025.

^*Equal Contribution, UC Berkeley.

Please cite PyRoki if you find this work useful for your research:

@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!

danielpmorton/pyroki

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