Adaptive Centroidal Voronoi Tessellation With Agent Dropout and Reinsertion for Multi-Agent Non-Convex Area Coverage

Abstract

Voronoi diagrams are widely used for area partitioning and coverage control. However, their application in non-convex domains typically requires additional computational procedures, such as the application of diffeomorphism, geodesic distance calculations, or incorporation of local markers. These techniques tend to be challenging to extend across diverse non-convex domains. This paper introduces the adaptive centroidal Voronoi tessellation (αCVT) algorithm, integrating iterative centroidal Voronoi tessellation (iCVT) with a novel agent dropout and reinsertion strategy to enhance area coverage control in non-convex domains. This approach demonstrates versatility across varied environments without requiring complex computational processes. The algorithm's efficacy is validated through a series of simulations encompassing non-convex domains with disjoint target areas, obstacles, and shape constraints for both homogeneous and heterogeneous agents. Additionally, the αCVT algorithm is extended for real-time coverage control scenarios. Performance metrics are employed to gauge the distribution of partitioned Voronoi regions and the overall coverage of the target areas, and the results show improved performance compared to the method without adopting the agent dropout and reinsertion strategy.INDEX TERMS Area partitioning, non-convex area coverage control, multi-agent system, Voronoi tessellation.