Distributed Circumferential Coverage Control in Non-Convex Annulus Environments

TL;DR

This paper introduces a distributed control method for multi-agent coverage in non-convex annulus environments, ensuring workload balance and collision avoidance through a novel Riemannian metric and partition law.

Contribution

It develops a new distributed circumferential coverage control framework with workload balancing and collision avoidance in complex non-convex environments.

Findings

Proves exponential convergence of workload partition.

Demonstrates agents' asymptotic convergence to local optima.

Validates effectiveness through a case study.

Abstract

It has long been a prominent challenge in multi-agent systems to achieve distributed coverage of non-convex annulus environments while ensuring workload equalization among agents. To address this challenge, a distributed circumferential coverage control formulation is developed in this note by constructing a Riemannian metric for the navigation in the non-convex subregion while avoiding collisions with the region boundary. In addition, a distributed partition law is designed to balance the workload on the entire coverage region by endowing each agent with a virtual partition bar that slides along the inner boundary of coverage region. Theoretical analysis is conducted to ensure the exponential convergence of workload partition and asymptotic convergence of each agent towards the local optimum in its subregion. Finally, a case study is presented to demonstrate the effectiveness of the proposed coverage control approach.