부산대학교 도서관

In order to maximize the efficiency of combined surface and underwater search in typical sea areas, ant colony optimization principle is used to study the planning method of heterogeneous Unmanned Underwater Vehicles (in short, UUV) &Unmanned surface vehicle (in short, USV) cooperative search mission. Decomposes the multi-UUV & USV collaborative area coverage search problem into two sub-problems, namely multi-UUV task area allocation and UUV path planning problems. Based on the UUV path planning problem, the ant colony algorithm is improved, the adaptive transfer probability factor is designed, and the heuristic update model and the local pheromone update model are proposed. By designing several typical simulation cases, the algorithm of the ant colony is verified and improved in the multi-UUV &USV collaborative area exploration, and the comprehensive performance of the UUV &USV collaborative task planning and scheme are evaluated from the aspects of energy consumption, task completion time, and communication time for the large-scale regional search operation requirements.