Pairwise Optimal Discrete Coverage Control for Gossiping Robots

TL;DR

This paper introduces a new distributed graph coverage algorithm for robotic agents that improves performance by using pairwise gossip communication, converging to pairwise-optimal partitions without the need for separate centering and partitioning steps.

Contribution

The paper presents a novel pairwise gossip-based coverage algorithm that outperforms traditional Lloyd methods and converges to a new class of optimal partitions.

Findings

The new algorithm converges to pairwise-optimal partitions.

Numerical comparisons show improved performance over Lloyd-type methods.

The approach requires only pairwise gossip communication between agents.

Abstract

We propose distributed algorithms to automatically deploy a group of robotic agents and provide coverage of a discretized environment represented by a graph. The classic Lloyd approach to coverage optimization involves separate centering and partitioning steps and converges to the set of centroidal Voronoi partitions. In this work we present a novel graph coverage algorithm which achieves better performance without this separation while requiring only pairwise ``gossip'' communication between agents. Our new algorithm provably converges to an element of the set of pairwise-optimal partitions, a subset of the set of centroidal Voronoi partitions. We illustrate that this new equilibrium set represents a significant performance improvement through numerical comparisons to existing Lloyd-type methods. Finally, we discuss ways to efficiently do the necessary computations.