Path Planning for Autonomous Underwater Vehicles With Simultaneous Arrival in Ocean Environment

Path Planning for Autonomous Underwater Vehicles With Simultaneous Arrival in Ocean Environment
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同时到达海洋环境的自主水下航行器路径规划

DOI:
10.1109/jsyst.2019.2937346
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发表时间:
2020-09
影响因子:
4.4
通讯作者:
Zhu Qian
Zhu Qian
中科院分区:
计算机科学2区
文献类型:
--
作者:
Yao Peng;Zhao Zhiyao;Zhu Qian

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研究了海洋环境中具有同时到达约束的自治水下机器人(AUV)的时间最短路径规划问题。整个框架可以分为两个连续的模块,和他们都是解决偏最小共识(BMC)的方法,它引入了边的重量标准的最小共识协议。第一模块根据BMC协议分别规划AUV的路径,使AUV能够沿着路径避开障碍物,以最短的时间通过海流到达目的地。第二部分考虑同时到达的合作约束,选择航行时间最长的AUV路径作为基准,采用BMC方法对其他AUV路径进行重划,直到它们对应的航行时间近似等于基准。各种场景下的仿真结果表明了该方法的适用性和有效性。
This article focuses on the time-minimum path planning problem of autonomous underwater vehicles (AUVs) with the constraint of simultaneous arrival in an ocean environment. The overall framework can be divided into two successive modules, and both of them are solved by the biased min-consensus (BMC) method, which introduces the edge weight into the standard min-consensus protocol. The first module plans each AUV's path under the BMC protocol, respectively, along which the AUV will avoid obstacles and navigate to the destination with the minimum time through the ocean current. Incorporating the cooperative constraint of simultaneous arrival, the second part chooses the AUV path with the maximal voyage time as a benchmark, and replans other AUVs' paths using the BMC method until their corresponding voyage time is approximately equal to the benchmark. The simulation results in various scenarios demonstrate the strong applicability and high effectiveness of our method.
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