基于多AUV间任务协作的水下多目标探测路径规划

Underwater Targets Tracking Path Planning Based on Task Cooperation of Multiple AUVs

利用自主式水下航行器(Autonomous Underwater Vehicle,AUV)对水下多目标进行协同探测是目前海洋技术领域的研究热点。主要研究在水下三维区间内的多AUV任务分配与协作探测路径规划机制,建立了以每个AUV能量耗费与能耗均衡为约束条件的水下三维空间中的多旅行商MTSP(Multiple Traveling Salesman Problem)问题模型,利用遗传算法GA(Genetic Algorithm)对该NP-Complete问题进行启发式求解,同时设计了考虑巡航总路径及访问目标数的适应度函数以提高多AUV间的能耗均衡性,实现多个AUV对多个水下目标的优化协同探测。最后本文利用MATLAB R2014a软件对多AUV任务协作与多目标探测路径规划机制进行了仿真,仿真结果验证了本文方法能均衡多AUV多目标探测问题的能量消耗,进而提高巡航速度和生命周期。

Cooperative detection on multiple underwater targets with Autonomous Underwater Vehicles（AUVs）is one of research highlights in the field of marine technology. Multiple AUVs task allocation and multiple targets cooperative path planning mechanism in three-dimensional underwater region are mainly discussed. According to the actual situation of underwater region,a multiple traveling salesman（MTSP）model with constraints of energy consumption and balance rate of each AUV is established. Moreover,cruise distance and target number of each AUV in MTSP are used to improve energy balance between multiple AUVs. Furthermore,GA（Genetic Algorithm）is introduced to solve this NP-complete problem in a heuristic manner,so as to realize optimization cooperative detection of multiple targets using multiple AUVs. Finally,this paper uses MATLAB 2014a software to simulate multiple AUVs task cooperation and multiple targets detection path planning mechanism. Simulation results verify that the proposed method can balance energy consumption between AUVs,and as a result,it can improve cruise speed and lifetime of AUV team effectively.