Decentralized Ergodic Control: Distribution-Driven Sensing and Exploration for Multiagent Systems

Abstract

We present a decentralized ergodic control policy for time-varying area coverage problems for multiple agents with nonlinear dynamics. Ergodic control allows us to specify distributions as objectives for area coverage problems for nonlinear robotic systems as a closed-form controller. We derive a variation to the ergodic control policy that can be used with consensus to enable a fully decentralized multiagent control policy. Examples are presented to illustrate the applicability of our method for multiagent terrain mapping as well as target localization. An analysis on ergodic policies as a Nash equilibrium is provided for game theoretic applications.