Distributed Multi-Coverage for Robot Swarms

TL;DR

This paper introduces a distributed algorithm enabling robot swarms to maintain multicoverage of assets with varying importance, ensuring redundancy despite limited communication and potential failures.

Contribution

It proposes the first distributed multicoverage algorithm tailored for robot swarms with local sensing and communication, addressing practical deployment constraints.

Findings

Algorithm achieves reliable multicoverage with limited communication.

Supports varying coverage requirements based on asset importance.

Operates effectively despite robot failures and local sensing limitations.

Abstract

Autonomous drone swarms deployed for surveillance, environmental monitoring, and infrastructure inspection must maintain reliable coverage of critical assets despite robot failures. This requires multicoverage: each asset must be observed by multiple robots for redundancy, with coverage requirements varying by asset importance. While recent work has solved the centralized problem optimally using integer programming, practical deployments face constraints that demand distributed solutions: robots operate with limited communication ranges, onboard computation restricts global planning, and partial system failures must not cause mission abort. We present a distributed multicoverage algorithm for robot swarms operating with local sensing, local communication, and no global coordination.