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.
DeepMind has acquired MuJoCo, and we are currently making preparations to open source the codebase. In the meantime, MuJoCo is available for download as a free and unrestricted precompiled binary under the Apache 2.0 license from the GitHub Releases page.
MuJoCo's source code will be released through this GitHub repository once it is ready. In the meantime, the repository hosts MuJoCo's documentation, C header files for its public API, sample program code, along with the full source code for the Python bindings and Unity plugin. If you wish to report bugs or make feature requests, please file them as GitHub Issues. You are also welcome to send us pull requests to improve anything that has been released into this repository.
MuJoCo is a compiled library with a C API, intended for researchers and developers. The runtime simulation module is tuned to maximize performance and operates on low-level data structures which are preallocated by the built-in XML parser and compiler. The user defines models in the native MJCF scene description language -- an XML file format designed to be as human readable and editable as possible. URDF model files can also be loaded. 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, not necessarily in a simulation loop. Features include
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Simulation in generalized coordinates, avoiding joint violations.
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Inverse dynamics that are well-defined even in the presence of contacts.
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Unified continuous-time formulation of constraints via convex optimization.
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Constraints include soft contacts, limits, dry friction, equality constraints.
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Simulation of particle systems, cloth, rope and soft objects.
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Actuators including motors, cylinders, muscles, tendons, slider-cranks.
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Choice of Newton, Conjugate Gradient, or Projected Gauss-Seidel solvers.
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Choice of pyramidal or elliptic friction cones, dense or sparse Jacobians.
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Choice of Euler or Runge-Kutta numerical integrators.
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Multi-threaded sampling and finite-difference approximations.
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Intuitive XML model format (called MJCF) and built-in model compiler.
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Cross-platform GUI with interactive 3D visualization in OpenGL.
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Run-time module written in ANSI C and hand-tuned for performance.
Python bindings and a plugin for the Unity game engine are also provided and are actively supported by the MuJoCo development team.
MuJoCo binaries are currently built for Linux (x86-64 and AArch64), Windows (x86-64 only), and macOS. If you require a build for a different platform, please let us know via GitHub Issues or Discussions.
MuJoco's current documentation is available at mujoco.org/book, which is serving Sphinx-based webpages derived from the ReStructuredText documentation source files.
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}
}
Copyright 2021 DeepMind Technologies Limited
ReStructuredText documents, images, and videos in the doc directory are made
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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.
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