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A collection of high-quality models for the MuJoCo physics engine, curated by Google DeepMind.

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MuJoCo Menagerie

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Menagerie is a collection of high-quality models for the MuJoCo physics engine, curated by Google DeepMind.

A physics simulator is only as good as the model it is simulating, and in a powerful simulator like MuJoCo with many modeling options, it is easy to create "bad" models which do not behave as expected. The goal of this collection is to provide the community with a curated library of well-designed models that work well right out of the gate.

Getting Started

Prerequisites

The minimum required MuJoCo version for each model is specified in its respective README. You can download prebuilt binaries for MuJoCo from the GitHub releases page, or if you are working with Python, you can install the native bindings from PyPI via pip install mujoco. For alternative installation instructions, see here.

Overview

The structure of Menagerie is illustrated below. For brevity, we have only included one model directory since all others follow the exact same pattern.

├── unitree_go2
│   ├── assets
│   │   ├── base_0.obj
│   │   ├── ...
│   ├── go2.png
│   ├── go2.xml
│   ├── LICENSE
│   ├── README.md
│   └── scene.xml
│   └── go2_mjx.xml
│   └── scene_mjx.xml
  • assets: stores the 3D meshes (.stl or .obj) of the model used for visual and collision purposes
  • LICENSE: describes the copyright and licensing terms of the model
  • README.md: contains detailed steps describing how the model's MJCF XML file was generated
  • <model>.xml: contains the MJCF definition of the model
  • scene.xml: includes <model>.xml with a plane, a light source and potentially other objects
  • <model>.png: a PNG image of scene.xml
  • <model>_mjx.xml: contains an MJX-compatible version of the model. Not all models have an MJX variant (see Menagerie Models for more information).
  • scene_mjx.xml: same as scene.xml but loads the MJX variant

Note that <model>.xml solely describes the model, i.e., no other entity is defined in the kinematic tree. We leave additional body definitions for the scene.xml file, as can be seen in the Shadow Hand scene.xml.

Usage

Via robot-descriptions

You can use the opensource robot_descriptions package to load any model in Menagerie. It is available on PyPI and can be installed via pip install robot_descriptions.

Once installed, you can load a model of your choice as follows:

import mujoco

# Loading a specific model description as an imported module.
from robot_descriptions import panda_mj_description
model = mujoco.MjModel.from_xml_path(panda_mj_description.MJCF_PATH)

# Directly loading an instance of MjModel.
from robot_descriptions.loaders.mujoco import load_robot_description
model = load_robot_description("panda_mj_description")

# Loading a variant of the model, e.g. panda without a gripper.
model = load_robot_description("panda_mj_description", variant="panda_nohand")

Via git clone

You can also directly clone this repository in the directory of your choice:

git clone https://github.com/google-deepmind/mujoco_menagerie.git

You can then interactively explore the model using the Python viewer:

python -m mujoco.viewer --mjcf mujoco_menagerie/unitree_go2/scene.xml

If you have further questions, please check out our FAQ.

Model Quality and Contributing

Our goal is to eventually make all Menagerie models as faithful as possible to the real system they are being modeled after. Improving model quality is an ongoing effort, and the current state of many models is not necessarily as good as it could be.

However, by releasing Menagerie in its current state, we hope to consolidate and increase visibility for community contributions. To help Menagerie users set proper expectations around the quality of each model, we introduce the following grading system:

Grade Description
A+ Values are the product of proper system identification
A Values are realistic, but have not been properly identified
B Stable, but some values are unrealistic
C Conditionally stable, can be significantly improved

The grading system will be applied to each model once a proper system identification toolbox is created. We are currently planning to release this toolbox later this year.

For more information regarding contributions, for example to add a new model to Menagerie, see CONTRIBUTING.

Menagerie Models

Arms.

Name Maker DoFs License MJX
FR3 Franka Robotics 7 Apache-2.0 ✖️
iiwa14 KUKA 7 BSD-3-Clause ✖️
Lite6 UFACTORY 6 BSD-3-Clause ✖️
Panda Franka Robotics 7 BSD-3-Clause ✔️
Sawyer Rethink Robotics 7 Apache-2.0 ✖️
Unitree Z1 Unitree Robotics 6 BSD-3-Clause ✖️
UR5e Universal Robots 6 BSD-3-Clause ✖️
UR10e Universal Robots 6 BSD-3-Clause ✖️
ViperX 300 Trossen Robotics 8 BSD-3-Clause ✖️
WidowX 250 Trossen Robotics 8 BSD-3-Clause ✖️
xarm7 UFACTORY 7 BSD-3-Clause ✖️
Gen3 Kinova Robotics 7 BSD-3-Clause ✖️
SO-ARM100 The Robot Studio 5 Apache-2.0 ✖️

Bipeds.

Name Maker DoFs License MJX
Cassie Agility Robotics 28 BSD-3-Clause ✖️

Dual Arms.

Name Maker DoFs License MJX
ALOHA 2 Trossen Robotics, Google DeepMind 16 BSD-3-Clause ✔️

Drones.

Name Maker DoFs License MJX
Crazyflie 2 Bitcraze 0 MIT ✖️
Skydio X2 Skydio 0 Apache-2.0 ✖️

End-effectors.

Name Maker DoFs License MJX
Allegro Hand V3 Wonik Robotics 16 BSD-2-Clause ✖️
LEAP Hand Carnegie Mellon University 16 MIT ✖️
Robotiq 2F-85 Robotiq 8 BSD-2-Clause ✖️
Shadow Hand EM35 Shadow Robot Company 24 Apache-2.0 ✖️
Shadow DEX-EE Hand Shadow Robot Company 12 Apache-2.0 ✖️

Mobile Manipulators.

Name Maker DoFs License MJX
Google Robot Google DeepMind 9 Apache-2.0 ✖️
Stretch 2 Hello Robot 17 Clear BSD ✖️
Stretch 3 Hello Robot 17 Apache-2.0 ✖️
PAL Tiago PAL Robotics 12 Apache-2.0 ✖️
PAL Tiago Dual PAL Robotics 21 Apache-2.0 ✖️

Humanoids.

Name Maker DoFs License MJX
Berkeley Humanoid Hybrid Robotics 12 BSD-3-Clause ✖️
Robotis OP3 Robotis 20 Apache-2.0 ✖️
Unitree G1 Unitree Robotics 37 BSD-3-Clause ✖️
Unitree H1 Unitree Robotics 19 BSD-3-Clause ✖️
TALOS PAL Robotics 32 Apache-2.0 ✖️

Quadrupeds.

Name Maker DoFs License MJX
ANYmal B ANYbotics 12 BSD-3-Clause ✖️
ANYmal C ANYbotics 12 BSD-3-Clause ✔️
Spot Boston Dynamics 12 BSD-3-Clause ✖️
Unitree A1 Unitree Robotics 12 BSD-3-Clause ✖️
Unitree Go1 Unitree Robotics 12 BSD-3-Clause ✖️
Unitree Go2 Unitree Robotics 12 BSD-3-Clause ✔️
Google Barkour v0 Google DeepMind 12 Apache-2.0 ✔️
Google Barkour vB Google DeepMind 12 Apache-2.0 ✔️

Biomechanical.

Name Maker DoFs License MJX
flybody Google DeepMind, HHMI Janelia Research Campus 102 Apache-2.0 ✖️

Miscellaneous.

Name Maker DoFs License MJX
D435i Intel Realsense 0 Apache-2.0 ✖️

Citing Menagerie

If you use Menagerie in your work, please use the following citation:

@software{menagerie2022github,
  author = {Zakka, Kevin and Tassa, Yuval and {MuJoCo Menagerie Contributors}},
  title = {{MuJoCo Menagerie: A collection of high-quality simulation models for MuJoCo}},
  url = {http://github.com/google-deepmind/mujoco_menagerie},
  year = {2022},
}

Acknowledgments

The models in this repository are based on third-party models designed by many talented people, and would not have been possible without their generous open-source contributions. We would like to acknowledge all the designers and engineers who made MuJoCo Menagerie possible.

We'd like to thank Pedro Vergani for his help with visuals and design.

The main effort required to make this repository publicly available was undertaken by Kevin Zakka, with help from the Robotics Simulation team at Google DeepMind.

License and Disclaimer

XML and asset files in each individual model directory of this repository are subject to different license terms. Please consult the LICENSE files under each specific model subdirectory for the relevant license and copyright information.

All other content is Copyright 2022 DeepMind Technologies Limited and licensed under the Apache License, Version 2.0. A copy of this license is provided in the top-level LICENSE file in this repository. You can also obtain it from https://www.apache.org/licenses/LICENSE-2.0.

This is not an officially supported Google product.

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