基于蒙特卡罗方法的多气-水两栖机器人水下目标协同检测

Shuchang Bai, Lichuan Zhang, Lu Liu, Qiaoqiao Zhao, Zixiao Zhu, Wenlong Geng, Chen Zhang, Ziyang Chen
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引用次数: 0

摘要

针对国家海洋相关专业领域的应急探测与搜索问题,研究了一种基于蒙特卡罗方法的多气-水两栖机器人水下目标协同探测方法。首先,建立了一个多水陆两栖机器人协同探测编队,对不同阵列的重叠阴影区域进行了探索,并设置了搜索区域和水陆两栖机器人协同探测编队的条件;通过仿真研究,选取并分配了各多气-水两栖机器人的参数,设计了一套仿真流程来解决该问题。最后,利用该方法模拟了8个编队的探测概率与搜索时间之间的关系。通过对仿真结果的分析,得出可以采用相应的编队对不同的任务和任务的不同阶段进行检测和跟踪,以达到最佳的检测效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Monte-Carlo Method-Based Collaborative Detection of Underwater Targets by Multiple Air-Water Amphibious Robots
Aiming at the problem of emergency detection and search in national marine related professional fields, a Monte-Carlo method based multiple Air-Water Amphibious Robots collaborative detection method for underwater targets is studied in this paper. Firstly, a multiple Air-Water Amphibious Robots cooperative detection formation was established, and the overlapping shadow areas of different arrays were explored, and conditions were set for the search area and the Air-Water Amphibious Robots cooperative detection formation. After simulation research, parameters of each multiple Air-Water Amphibious Robots were selected and assigned, and then a set of simulation process was designed to solve the problem. Finally, the proposed method is used to simulate the relationship between detection probability and search time for 8 formations. Through the analysis of simulation results, it is concluded that the corresponding formation can be adopted to detect and track different tasks and different stages of tasks to achieve the best detection effect.
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