From e4ee00e695eda213e70a97d4a98b34861b918f19 Mon Sep 17 00:00:00 2001 From: Yuval Tassa Date: Thu, 6 Mar 2025 23:15:26 -0800 Subject: [PATCH] Link to `Onshape to robot` converter in top level README. PiperOrigin-RevId: 734426561 Change-Id: I1e5005c97d111204b2277c4b4d1fca9b162d0628 --- README.md | 23 ++++++++++++++--------- 1 file changed, 14 insertions(+), 9 deletions(-) diff --git a/README.md b/README.md index db022581b3..935c80b740 100644 --- a/README.md +++ b/README.md @@ -33,8 +33,9 @@ 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. +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 @@ -54,14 +55,17 @@ running on Google Colab: [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/google-deepmind/mujoco/blob/main/python/tutorial.ipynb) - The **rollout** tutorial shows how to use the multithreaded `rollout` module: [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/google-deepmind/mujoco/blob/main/python/rollout.ipynb) - - The **LQR** tutorial synthesizes a linear-quadratic controller, balancing a humanoid on one leg: + - The **LQR** tutorial synthesizes a linear-quadratic controller, balancing a + humanoid on one leg: [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/google-deepmind/mujoco/blob/main/python/LQR.ipynb) - - The **least-squares** tutorial explains how to use the Python-based nonlinear least-squares solver: + - The **least-squares** tutorial explains how to use the Python-based nonlinear + least-squares solver: [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/google-deepmind/mujoco/blob/main/python/least_squares.ipynb) - The **MJX** tutorial provides usage examples of [MuJoCo XLA](https://mujoco.readthedocs.io/en/stable/mjx.html), a branch of MuJoCo written in JAX: [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/google-deepmind/mujoco/blob/main/mjx/tutorial.ipynb) - - The **differentiable physics** tutorial trains locomotion policies with analytical gradients automatically derived from MuJoCo's physics step: + - The **differentiable physics** tutorial trains locomotion policies with + analytical gradients automatically derived from MuJoCo's physics step: [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/google-deepmind/mujoco/blob/main/mjx/training_apg.ipynb) ## Installation @@ -75,7 +79,7 @@ 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, please note that the commit at +source] section of the documentation. However, note that the commit at the tip of the `main` branch may be unstable. ### Python (>= 3.9) @@ -111,7 +115,8 @@ GitHub [Issues](https://github.com/google-deepmind/mujoco/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. +MuJoCo is the backbone for numerous environment packages. Below we list several +bindings and converters. ### Bindings @@ -139,7 +144,6 @@ These packages give users of various languages access to MuJoCo functionality: - **Java**: [mujoco-java](https://github.com/CommonWealthRobotics/mujoco-java) - **Julia**: [MuJoCo.jl](https://github.com/JamieMair/MuJoCo.jl) - ### Converters - **OpenSim**: [MyoConverter](https://github.com/MyoHub/myoconverter) converts @@ -148,6 +152,8 @@ These packages give users of various languages access to MuJoCo functionality: two-way SDFormat <-> MJCF conversion tool. - **OBJ**: [obj2mjcf](https://github.com/kevinzakka/obj2mjcf) a script for converting composite OBJ files into a loadable MJCF model. +- **onshape**: [Onshape to Robot](https://github.com/rhoban/onshape-to-robot) + Converts [onshape](https://www.onshape.com/en/) CAD assemblies to MJCF. ## Citation @@ -186,7 +192,6 @@ This is not an officially supported Google product. [Getting Started]: https://mujoco.readthedocs.io/en/latest/programming#getting-started [Unity]: https://unity.com/ [releases page]: https://github.com/google-deepmind/mujoco/releases -[GitHub Issues]: https://github.com/google-deepmind/mujoco/issues [mujoco.readthedocs.io]: https://mujoco.readthedocs.io [changelog]: https://mujoco.readthedocs.io/en/latest/changelog.html [Python bindings]: https://mujoco.readthedocs.io/en/stable/python.html#python-bindings