Decentralized Adaptive Control for Collaborative Manipulation

Abstract

This paper presents a design for a decentralized adaptive controller that allows a team of agents to manipulate a common payload in $mathbb{R}^2$ or $mathbb{R}^3$. The controller requires no communication between agents and requires no textit{a priori} knowledge of agent positions or payload properties. The agents can control the payload to track a reference trajectory in linear and angular velocity with center-of-mass measurements, in angular velocity using only local measurements and a common frame, and can stabilize its rotation with only local measurements. The controller is designed via a Lyapunov-style analysis and has proven stability and convergence. The controller is validated in simulation and experimentally with four robots manipulating an object in the plane.