Autonomous Detection and Coverage of Unknown Target Areas by Multi-Agent Systems
This addresses the challenge of efficient and safe coverage in applications like surveillance or environmental monitoring, representing an incremental improvement by combining existing techniques for enhanced autonomy.
The paper tackles the problem of enabling multi-agent systems to autonomously detect and cover unknown target areas without prior knowledge, achieving full coverage through a novel algorithm that integrates density-driven attraction with Centroidal Voronoi Tessellation and Control Barrier Functions.
This paper presents a novel coverage control algorithm for multi-agent systems, where each agent has no prior knowledge of the specific region to be covered. The proposed method enables agents to autonomously detect the target area and collaboratively achieve full coverage. Once an agent detects a part of the target region within its sensor range, a dynamically constructed density function is generated to attract nearby agents. By integrating this density-driven mechanism with Centroidal Voronoi Tessellation (CVT), the agents are guided to achieve optimal spatial distribution. Additionally, Control Barrier Functions (CBFs) are employed to ensure collision avoidance and maintain non-overlapping sensor coverage, enhancing both safety and efficiency. Simulation results verify that agents can independently locate and effectively cover the target area.