A Generalized Voronoi Graph based Coverage Control Approach for Non-Convex Environment

TL;DR

This paper introduces a two-phase coverage control method using Generalized Voronoi Graphs for multi-robot systems in complex non-convex environments, improving load balancing and coverage efficiency.

Contribution

It presents a novel GVG-based approach with a weighted load-balancing algorithm and a new control strategy, enhancing coverage in non-convex regions with obstacles.

Findings

The method converges reliably in simulations.

It achieves better load distribution among robots.

Coverage performance improves in complex environments.

Abstract

To address the challenge of efficient coverage by multi-robot systems in non-convex regions with multiple obstacles, this paper proposes a coverage control method based on the Generalized Voronoi Graph (GVG), which has two phases: Load-Balancing Algorithm phase and Collaborative Coverage phase. In Load-Balancing Algorithm phase, the non-convex region is partitioned into multiple sub-regions based on GVG. Besides, a weighted load-balancing algorithm is developed, which considers the quality differences among sub-regions. By iteratively optimizing the robot allocation ratio, the number of robots in each sub-region is matched with the sub-region quality to achieve load balance. In Collaborative Coverage phase, each robot is controlled by a new controller to effectively coverage the region. The convergence of the method is proved and its performance is evaluated through simulations.