Multi-Agent Control Using Coverage Over Time-Varying Domains

TL;DR

This paper introduces a scalable control law for multi-agent coverage in dynamic, time-varying domains, ensuring exponential convergence and validated through simulations and real robot experiments.

Contribution

It proposes a novel control strategy that handles time-varying domains and densities, simplifying multi-robot coverage control regardless of system size.

Findings

Control law guarantees exponential convergence.

Method is scalable and system-agnostic.

Validated through simulations and real-world experiments.

Abstract

Multi-agent coverage control is used as a mechanism to influence the behavior of a group of robots by introducing time-varying domain. The coverage optimization problem is modified to adopt time-varying domains, and the proposed control law possesses an exponential convergence characteristic. Cumbrous control for many robots is simplified by deploying distribution and behavior of the robot team as a whole. In the proposed approach, the inputs to the multi-agent system, i.e., time-varying density and time-varying domain, are agnostic to the size of the system. Analytic expressions of surface and line integrals present in the control law are obtained under uniform density. The scalability of the proposed control strategy is explained and verified via numerical simulation. Experiments on real robots are used to test the proposed control law.