Research On Multiagent-based Regional Differentiated Dynamic Coverage Algorithm

Multi-agent systems have been widely applied in tasks such as swarm behavior,leader tracking,continuous monitoring,and area coverage.Area coverage is a coordination task that relies on environmental factors and requires a group of intelligent agents to be deployed in a designated area to collect information or perform tasks.As robotics technology advances and task requirements become more complex,it is necessary to design more diverse area coverage algorithms to address various task environments.Different task environments typically require different area coverage requirements and strategies.For example,in the case of an oil spill at sea,intelligent agents would need to focus on covering the area with the highest oil density.Multi-agent systems need to flexibly adjust coverage range and methods based on task environments.In this way,intelligent agent systems can effectively allocate resources,provide optimal coverage,and increase the success rate of coverage tasks.Therefore,designing differentiated coverage algorithms is crucial for rapid response and resource optimization.This paper aims to propose a multi-agentbased differentiated area coverage algorithm to improve the coverage efficiency and robustness of the system,ensure adequate coverage of key areas,and improve coverage quality.The algorithm is applicable to different task environments and area coverage requirements,such as disaster response scenarios like oil spills at sea and fires.The algorithm has the advantage of flexibly adjusting coverage range and methods to provide the best coverage approach for multi-agent systems and improve task success rates.The main research content is as follows:(1)The concept of differentiated coverage is elaborated,and a multiagent-based regional differentiated coverage algorithm is proposed to achieve differentiated coverage of key areas.The effectiveness and performance advantages of the algorithm are verified through simulation and experimental results.(2)To address the problem of maximizing coverage in non-key areas,a solution is proposed that includes improving the update strategy of virtual navigation agents and implementing the extreme search coverage algorithm.The feasibility and excellent performance of the extreme search coverage algorithm are demonstrated through simulation and experimental analysis.(3)The problem of differentiated coverage in dynamic environments is studied,including differentiated coverage of dynamic key areas and avoidance of collision with dynamic obstacles.The regional differentiated coverage algorithm is optimized to effectively handle continuously changing situations,ensuring differentiated coverage of key areas while ensuring safe and efficient system operation.