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GitHub - google-deepmind/mujoco: Multi-Joint dynamics with Contact. A general purpose physics simulator.

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Pangram verdict · v3.3

We believe that this document is fully human-written

4 %

AI likelihood · overall

Human
100% human-written 0% AI-generated
SEGMENTS · HUMAN 3 of 3
SEGMENTS · AI 0 of 3
WORD COUNT 711
PEAK AI % 6% · §3
Analyzed
Apr 22
backend: pangram/v3.3
Segments scanned
3 windows
avg 237 words each
Distribution
100 / 0%
human / AI fraction
Verdict
Human
Pangram v3.3

Article text · 711 words · 3 segments analyzed

Human AI-generated
§1 Human · 3%

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:

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.

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.

§2 Human · 3%

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. Related software 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:

Python bindings

dm_control, Google DeepMind's related environment stack, includes PyMJCF, a module for procedural manipulation of MuJoCo models.

JavaScript bindings and WebAssembly support (inspired stillonearth and zalo's community projects; mjswan extends these with real-time policy control, interactive force application, and more). C# bindings and Unity plug-in

Third-party bindings:

MATLAB Simulink: Simulink Blockset for MuJoCo Simulator by Manoj Velmurugan. Swift: swift-mujoco Java: mujoco-java Julia: MuJoCo.jl Rust: MuJoCo-rs

Converters

OpenSim: MyoConverter converts OpenSim models to MJCF. SDFormat: gz-mujoco is a two-way SDFormat <-> MJCF conversion tool. OBJ: obj2mjcf a script for converting composite OBJ files into a loadable MJCF model.

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onshape: Onshape to Robot Converts onshape CAD assemblies to MJCF.

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.