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

TL;DR

This paper introduces a decentralized ergodic control method enabling multiple agents with nonlinear dynamics to collaboratively explore and cover areas based on specified distributions, applicable to terrain mapping and target localization.

Contribution

It develops a decentralized ergodic control policy that integrates consensus for multi-agent area coverage with nonlinear robotic systems.

Findings

Effective for multi-agent terrain mapping

Applicable to target localization tasks

Provides a game-theoretic analysis of ergodic policies

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 multi-agent control policy. Examples are presented to illustrate the applicability of our method for multi-agent terrain mapping as well as target localization. An analysis on ergodic policies as a Nash equilibrium is provided for game theoretic applications.