duburcqa/jiminy

Jiminy: a fast and portable Python/C++ simulator of poly-articulated robots with OpenAI Gym interface for reinforcement learning

43
/ 100
Emerging

This project helps robotics researchers and engineers efficiently simulate poly-articulated robots to develop and test control algorithms, especially using reinforcement learning. You can input a robot's design (e.g., a URDF file) and define its environment and control logic. The output is a realistic simulation of the robot's behavior, along with detailed logs and performance metrics, used to train and evaluate AI models for robot control.

285 stars. No commits in the last 6 months.

Use this if you need a fast, physically accurate, and flexible simulation environment for developing and training AI-powered control systems for complex robots.

Not ideal if you primarily need high-fidelity visual rendering for animation or user interaction, or if your simulation does not involve poly-articulated systems or machine learning.

robotics simulation reinforcement learning robot control mechatronics AI for robotics
Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 15 / 25

How are scores calculated?

Stars

285

Forks

30

Language

Jupyter Notebook

License

MIT

Last pushed

Sep 05, 2025

Commits (30d)

0

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