Real-Time Multi-Contact Model Predictive Control via ADMM

TL;DR

This paper introduces a real-time control algorithm for systems involving contact with the environment, leveraging ADMM for fast reasoning and parallelization, validated through numerical and physical experiments.

Contribution

It presents a novel hybrid model predictive control method, C3, that efficiently handles contact initiation and breaking in real-time using ADMM and consensus formulation.

Findings

Enables real-time multi-contact control with high-speed reasoning.

Parallelizes contact scheduling for improved computational efficiency.

Successfully validated on numerical and physical multi-contact systems.

Abstract

We propose a hybrid model predictive control algorithm, consensus complementarity control (C3), for systems that make and break contact with their environment. Many state-of-the-art controllers for tasks which require initiating contact with the environment, such as locomotion and manipulation, require a priori mode schedules or are so computationally complex that they cannot run at real-time rates. We present a method, based on the alternating direction method of multipliers (ADMM), capable of highspeed reasoning over potential contact events. Via a consensus formulation, our approach enables parallelization of the contact scheduling problem. We validate our results on three numerical examples, including two frictional contact problems, and physical experimentation on an underactuated multi-contact system.