A Generalized Voronoi Graph based Coverage Control Approach for Non-Convex Environment
This addresses coverage control for multi-robots in complex environments, but it appears incremental as it builds on existing Voronoi-based approaches.
The paper tackles efficient coverage by multi-robot systems in non-convex environments with obstacles by proposing a Generalized Voronoi Graph-based method with load-balancing and collaborative phases, achieving convergence and evaluated performance in simulations.
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.