Awesome
Dojo
A differentiable physics engine for robotics
- arXiv preprint: https://arxiv.org/abs/2203.00806
- Python interface: https://github.com/dojo-sim/dojopy
- site: https://sites.google.com/view/dojo-sim
- video presentation: https://youtu.be/TRtOESXJxJQ
Update April 2023
- We are no longer actively developing Dojo, but pull requests are always welcome.
- We have updated or removed examples to account for changes since the initial version of Dojo.
- Additional developments on differentiable simulation:
- Differentiable collision detection (Kevin Tracy): capsules, convex primitives
- Single-level contact dynamics + collision detection (Simon Le Cleac'h): Silico
Examples
Simulation
<p float="left"> <img src="docs/src/assets/animations/atlas_drop.gif" width="120"/> <img src="docs/src/assets//animations/astronaut.gif" width="210"/> <img src="docs/src/assets/animations/dzhanibekov.gif" width="180"/> <img src="docs/src/assets/animations/tippetop.gif" width="180"/> </p>Learning and Control
<p float="left"> <img src="docs/src/assets/animations/quadruped.gif" width="275"/> <img src="docs/src/assets/animations/ant_ars.gif" width="275"/> <img src="docs/src/assets/animations/quadrotor.gif" width="175"/> </p>System Identification
<p float="left"> <img src="docs/src/assets/animations/box_learning.gif" width="200"/> <img src="docs/src/assets/animations/cone_learning.gif" width="200"/> <img src="docs/src/assets/animations/box_toss.gif" width="300"/> </p>Interfacing Other Packages
| ReinforcementLearning.jl: DQN | ControlSystems.jl: LQR |
|---|---|
| <img src="docs/src/assets/animations/cartpole_rl.gif" width="250"/> | <img src="docs/src/assets/animations/cartpole_lqr.gif" width="250"/> |
Installation
Dojo can be added via the Julia package manager (type ]):
pkg> add Dojo
For convenience mechanisms and environments, add DojoEnvironments additionally:
pkg> add DojoEnvironments
Citing
@article{howelllecleach2022,
title={Dojo: A Differentiable Physics Engine for Robotics},
author={Howell, Taylor and Le Cleac'h, Simon and Bruedigam, Jan and Kolter, Zico and Schwager, Mac and Manchester, Zachary},
journal={arXiv preprint arXiv:2203.00806},
url={https://arxiv.org/abs/2203.00806},
year={2022}
}
How To Contribute
Please submit a pull request or open an issue. See the docs for contribution ideas.