mujoco README

The project's README from github.com/google-deepmind/mujoco. As one markdown file: README.md.

MuJoCo

MuJoCo stands for Multi-Joint dynamics with Contact. It is a general purpose physics engine that aims to facilitate research and development in robotics, biomechanics, graphics and animation, machine learning, and other areas which demand fast and accurate simulation of articulated structures interacting with their environment.

This repository is maintained by Google DeepMind.

MuJoCo has a C API and is intended for researchers and developers. The runtime simulation module is tuned to maximize performance and operates on low-level data structures that are preallocated by the built-in XML compiler. The library includes interactive visualization with a native GUI, rendered in OpenGL. MuJoCo further exposes a large number of utility functions for computing physics-related quantities.

We also provide Python bindings and a plug-in for the Unity game engine.

Documentation

MuJoCo's documentation can be found at mujoco.readthedocs.io. Upcoming features due for the next release can be found in the changelog in the "latest" branch.

Getting Started

There are two easy ways to get started with MuJoCo:

  1. Run simulate on your machine. This video shows a screen capture of simulate, MuJoCo's native interactive viewer. Follow the steps described in the Getting Started section of the documentation to get simulate running on your machine.

  2. Explore our online IPython notebooks. If you are a Python user, you might want to start with our tutorial notebooks running on Google Colab:

Installation

Prebuilt binaries

Versioned releases are available as precompiled binaries from the GitHub releases page, built for Linux (x86-64 and AArch64), Windows (x86-64 only), and macOS (universal). This is the recommended way to use the software.

Building from source

Users who wish to build MuJoCo from source should consult the build from source section of the documentation. However, note that the commit at the tip of the main branch may be unstable.

Python (>= 3.10)

The native Python bindings, which come pre-packaged with a copy of MuJoCo, can be installed from PyPI via:

pip install mujoco

Note that Pre-built Linux wheels target manylinux2014, see here for compatible distributions. For more information such as building the bindings from source, see the Python bindings section of the documentation.

Versioning

We aim to release MuJoCo in the first week of each month. Our versioning standards changed to modified Semantic Versioning in 3.5.0, see versioning for details.

Contributing

We welcome community engagement: questions, requests for help, bug reports and feature requests. To read more about bug reports, feature requests and more ambitious contributions, please see our contributors guide and style guide.

Asking Questions

Questions and requests for help are welcome as a GitHub "Asking for Help" Discussion and should focus on a specific problem or question.

Bug reports and feature requests

GitHub Issues are reserved for bug reports, feature requests and other development-related subjects.

MuJoCo is the backbone for numerous environment packages. Below we list several bindings and converters.

Bindings

These packages give users of various languages access to MuJoCo functionality:

First-party bindings:

Third-party bindings:

Converters

Citation

If you use MuJoCo for published research, please cite:

@inproceedings{todorov2012mujoco,
  title={MuJoCo: A physics engine for model-based control},
  author={Todorov, Emanuel and Erez, Tom and Tassa, Yuval},
  booktitle={2012 IEEE/RSJ International Conference on Intelligent Robots and Systems},
  pages={5026--5033},
  year={2012},
  organization={IEEE},
  doi={10.1109/IROS.2012.6386109}
}

License and Disclaimer

Copyright 2021 DeepMind Technologies Limited.

Box collision code (engine_collision_box.c) is Copyright 2016 Svetoslav Kolev.

ReStructuredText documents, images, and videos in the doc directory are made available under the terms of the Creative Commons Attribution 4.0 (CC BY 4.0) license. You may obtain a copy of the License at https://creativecommons.org/licenses/by/4.0/legalcode.

Source code is licensed under the Apache License, Version 2.0. You may obtain a copy of the License at https://www.apache.org/licenses/LICENSE-2.0.

This is not an officially supported Google product.

mujoco (google-deepmind/mujoco)

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15.7K ·GitHub
Mujoco
What is this?MuJoCo is a general-purpose physics engine for simulating articulated structures interacting with their environment, maintained by Google DeepMind. It targets robotics, biomechanics, graphics/animation, and machine learning research.
Is this a standalone app or a library I call from code?It is a C library with a native interactive GUI viewer called simulate, plus first-party Python, JavaScript/WebAssembly, and C#/Unity bindings for programmatic use.
How do I get it running?Download a precompiled binary from the GitHub releases page and run the 'simulate' viewer, or install the Python bindings via PyPI with pip for programmatic use.
Do I need Python to use it?No, the core engine and the simulate viewer work standalone via the prebuilt binaries; Python (>=3.10) is only needed if you want the native Python bindings from PyPI.
Is building from the main branch stable?No, the tip of the main branch can be unstable, so prebuilt releases are the recommended way to get a reliable build.
Who is this aimed at?Researchers and developers working in robotics, biomechanics, graphics/animation, and machine learning who need fast, accurate articulated-body physics simulation.
Which OSes are officially supported?Prebuilt binaries are provided for Linux (x86-64 and AArch64), Windows (x86-64), and macOS (universal binary).
Can I use MuJoCo outside of C and Python?Yes, first-party bindings cover JavaScript/WebAssembly and C#/Unity, and third-party bindings exist for MATLAB Simulink, Swift, Java, Julia, and Rust.
Can MuJoCo models be converted from other formats?Yes, community tools convert OpenSim models (MyoConverter), SDFormat files (gz-mujoco), OBJ files (obj2mjcf), and Onshape CAD assemblies into MJCF, MuJoCo's native model format.
What is MJX?MJX (MuJoCo XLA) is a branch of MuJoCo written in JAX, covered by a dedicated tutorial, enabling differentiable and hardware-accelerated physics for ML workflows.
How often are new versions released?The project aims to release a new version in the first week of each month, following modified Semantic Versioning since 3.5.0.
What are similar projects?AirSim, project_superdex, kimodo, genesis-world, carla, bullet3, ml-agents, quackd
Which topics is it in?mujoco, unity, physics, opengl, robotics, simulation, reinforcement-learning, wasm, c, c++, deep-learning, research
Creator
google-deepmind
Size
144.9 MB
Stars
15.7K
Updated
CommitOct 17Release3.16.0Oct 14
Age
5y
Commits · 90 Days