Path Planning of a Large-scale Underwater Glider Swarm Area Coverage Detection
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摘要: 在水下滑翔机集群执行搜索任务时, 通过合理设定各平台的搜索路径, 能够有效提高集群的探测效能, 从而实现利用最少平台的最大化探测区域覆盖。为解决大规模集群任务规划中计算量巨大的问题, 文中在栅格法的基础上, 通过几何划定有效覆盖区域并反演栅格序数的方法, 构建了评价覆盖能力的高精度布尔模型, 并以此为支撑, 利用群智能方法实现了大规模集群对广域海区的快速路径规划。在此基础上, 利用序贯思想, 提出了以较小计算量解决集群平台数量最小化的方法。通过仿真试验验证了该方法的可行性。文中的方法可为大规模水下滑翔机集群的探测任务规划提供支持。Abstract: When search tasks in an underwater glider swarm are conducted, the detection efficiency of the swarm can be improved effectively by setting the search path of each platform reasonably, thereby maximizing the coverage of the detection area with the least platform. To solve the problem of large calculations in large-scale swarm mission planning, this study constructs a high-precision Boolean model based on the grid method to evaluate the coverage ability of an underwater glider swarm by delimiting the effective coverage area geometrically and inverting the grid number. With this as a support, a swarm intelligence algorithm can then be used to realize fast path planning of a large-scale swarm in a wide sea area. Accordingly, this research proposes a method for solving the minimum number of swarm platforms with only few calculations by using sequential thought. The feasibility of this method is verified through a simulation experiment. The proposed method can support mission planning for large-scale underwater glider swarms.
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Key words:
- underwater glider swarm /
- detection /
- mission planning /
- area coverage
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