Multi-Agent Coverage Control with Energy Depletion and Repletion

TL;DR

This paper presents a hybrid system model for multi-agent coverage tasks that accounts for energy depletion and repletion, ensuring agents can recharge efficiently while maintaining coverage.

Contribution

It introduces a novel hybrid model with a guard function for energy management and uses IPA to optimize recharging policies in multi-agent coverage scenarios.

Findings

Full recharging policy is shown to be optimal.

The model guarantees agents do not run out of energy during tasks.

A centralized scheduler manages charging contention effectively.

Abstract

We develop a hybrid system model to describe the behavior of multiple agents cooperatively solving an optimal coverage problem under energy depletion and repletion constraints. The model captures the controlled switching of agents between coverage (when energy is depleted) and battery charging (when energy is replenished) modes. It guarantees the feasibility of the coverage problem by defining a guard function on each agent's battery level to prevent it from dying on its way to a charging station. The charging station plays the role of a centralized scheduler to solve the contention problem of agents competing for the only charging resource in the mission space. The optimal coverage problem is transformed into a parametric optimization problem to determine an optimal recharging policy. This problem is solved through the use of Infinitesimal Perturbation Analysis (IPA), with simulation results showing that a full recharging policy is optimal.