ContactImplicitMPC.jl

This repository contains algorithms and examples from our paper: Fast Contact-Implicit Model-Predictive Control.

A collection of examples are pre-generated in notebooks with the package, please try: flamingo, pushbot, hopper, and quadruped. Additional notebooks with examples from the paper can be generated.

Installation

ContactImplicitMPC can be added via the Julia package manager (type ]):

pkg> add ContactImplicitMPC

Flamingo

<img src="animations/flamingo.gif" alt="drawing" width="400"/>

PushBot

<img src="animations/pushbot.gif" alt="drawing" width="400"/>

Hopper Parkour

<img src="animations/hopper_parkour.gif" alt="drawing" width="250"/>

Quadruped with Payload

<img src="animations/quadruped_payload.gif" alt="drawing" width="400"/>

Hopper Monte Carlo

<img src="animations/hopper_monte_carlo.gif" alt="drawing" width="400"/>

Quadruped Monte Carlo

<img src="animations/quadruped_monte_carlo.gif" alt="drawing" width="400"/>

Reference Trajectories

The trajectories we track in the examples are generated using contact-implicit trajectory optimization and can be run here.

Simulator

The differentiable simulator is available as a stand-alone package: RoboDojo.jl.

Citing

If you find ContactImplicitMPC useful in your project, we kindly request that you cite the following paper:

@article{lecleach2021fast,
	title={Fast Contact-Implicit Model-Predictive Control},
	author={Le Cleac'h, Simon  and Howell, Taylor A. and Schwager, Mac and Manchester, Zachary},
	journal={arXiv preprint arXiv:2107.05616},
	year={2021}
}

The article is available under Open Access here.