Yuval Tassa
8e38a8a020
PiperOrigin-RevId: 453178202 Change-Id: I0cb3a52983930fb3665cc40e26d5d19b44ac99f1
140 lines
6.2 KiB
Markdown
140 lines
6.2 KiB
Markdown
# MuJoCo Physics
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<p>
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<a href="https://github.com/deepmind/mujoco/actions/workflows/build.yml?query=branch%3Amain" alt="GitHub Actions">
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<img src="https://img.shields.io/github/workflow/status/deepmind/mujoco/build/main">
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</a>
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</p>
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**MuJoCo** stands for **Mu**lti-**Jo**int dynamics with **Co**ntact. It is a
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general purpose physics engine that aims to facilitate research and development
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in robotics, biomechanics, graphics and animation, machine learning, and other
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areas which demand fast and accurate simulation of articulated structures
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interacting with their environment.
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This repository is maintained by DeepMind, please see our [acquisition] and
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[open sourcing] announcements.
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MuJoCo has a C API and is intended for researchers and developers. The runtime
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simulation module is tuned to maximize performance and operates on low-level
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data structures that are preallocated by the built-in XML compiler. The library
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includes interactive visualization with a native GUI, rendered in OpenGL. MuJoCo
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further exposes a large number of utility functions for computing physics-related
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quantities. We also provide Python bindings and a plug-in for the [Unity]
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game engine.
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## Documentation
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MuJoCo's documentation is available at [mujoco.readthedocs.io], which serves
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webpages derived from the [documentation source files].
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## Releases
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Versioned releases are available as precompiled binaries from the GitHub
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[releases page], built for Linux (x86-64 and AArch64), Windows (x86-64 only),
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and macOS (universal). This is the recommended way to use the software.
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Users who wish to build MuJoCo from source, please consult the [build from
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source] section of the documentation. However, please note that the commit at
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the tip of the `main` branch may be unstable.
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## Getting Started
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There are two easy ways to get started with MuJoCo:
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1. **Run `simulate` on your machine.**
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[This video](https://www.youtube.com/watch?v=0ORsj_E17B0) shows a screen capture
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of `simulate`, MuJoCo's native interactive viewer. Follow the steps described in
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the [Getting Started] section of the documentation to get `simulate` running on
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your machine.
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2. **Explore our online IPython notebooks.**
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If you are a Python user, you might want to start with our tutorial notebooks,
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running on Google Colab:
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- The first tutorial focuses on the basic MuJoCo Python bindings: [](https://colab.research.google.com/github/deepmind/dm_control/blob/main/dm_control/mujoco/tutorial.ipynb)
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- The second tutorial includes more examples of `dm_control`-specific functionality: [](https://colab.research.google.com/github/deepmind/dm_control/blob/main/tutorial.ipynb)
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## Asking Questions
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We welcome community engagement: questions, requests for help, bug reports and
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feature requests. To read more about bug reports, feature requests and more
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ambitious contributions, please see our [contributors guide](CONTRIBUTING.md).
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Questions and requests for help are welcome on the
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GitHub [issues](https://github.com/deepmind/mujoco/issues) and
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[discussions](https://github.com/deepmind/mujoco/discussions) pages. Issues
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should be focused on a specific problem or question, while discussions should
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address wider concerns that might require input from multiple participants.
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Here are some guidelines for asking good questions:
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1. Search for existing questions or issues that touch on the same subject.
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You can add comments to existing threads or start new ones. If you start a
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new thread and there are existing relevant threads, please link to them.
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2. Use a clear and descriptive title.
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3. Introduce yourself and your project more generally.
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If your level of expertise is exceptional (either high or low), and it might
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be relevant to what we can assume you know, please state that as well.
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4. Make it easy for others to reproduce the problem or understand your question.
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If this requires a model, please include it. Short, minimal, pure XML models
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(the preferred format) should be pasted inline. Longer XML models should be
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attached as a `.txt` file (GitHub does not accept `.xml`) or in a `.zip`.
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Models requiring binary assets (meshes, textures), should be attached as
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`.zip` files. Please remember to make sure the included model is loadable
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before you attach it.
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5. Include an illustrative screenshot or video, if relevant.
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6. Tell us which MuJoCo version and operating system you are using.
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## Citation
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If you use MuJoCo for published research, please cite:
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```
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@inproceedings{todorov2012mujoco,
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title={MuJoCo: A physics engine for model-based control},
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author={Todorov, Emanuel and Erez, Tom and Tassa, Yuval},
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booktitle={2012 IEEE/RSJ International Conference on Intelligent Robots and Systems},
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pages={5026--5033},
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year={2012},
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organization={IEEE},
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doi={10.1109/IROS.2012.6386109}
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}
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```
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## License and Disclaimer
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Copyright 2021 DeepMind Technologies Limited.
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Box collision code ([`engine_collision_box.c`](https://github.com/deepmind/mujoco/tree/main/src/engine/engine_collision_box.c))
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is Copyright 2016 Svetoslav Kolev.
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ReStructuredText documents, images, and videos in the `doc` directory are made
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available under the terms of the Creative Commons Attribution 4.0 (CC BY 4.0)
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license. You may obtain a copy of the License at
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https://creativecommons.org/licenses/by/4.0/legalcode.
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Source code is licensed under the Apache License, Version 2.0. You may obtain a
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copy of the License at https://www.apache.org/licenses/LICENSE-2.0.
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This is not an officially supported Google product.
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[build from source]: https://mujoco.readthedocs.io/en/latest/programming.html#building-mujoco-from-source
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[Getting Started]: https://mujoco.readthedocs.io/en/latest/programming.html#getting-started
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[acquisition]: https://www.deepmind.com/blog/opening-up-a-physics-simulator-for-robotics
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[open sourcing]: https://www.deepmind.com/blog/open-sourcing-mujoco
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[Unity]: https://unity.com/
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[releases page]: https://github.com/deepmind/mujoco/releases
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[GitHub Issues]: https://github.com/deepmind/mujoco/issues
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[documentation source files]: https://github.com/deepmind/mujoco/tree/main/doc
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[mujoco.readthedocs.io]: https://mujoco.readthedocs.io
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