| 海洋自主航行器多海湾区域完全遍历路径规划 |
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| 引用本文： | 苗润龙,庞硕,姜大鹏,董早鹏.海洋自主航行器多海湾区域完全遍历路径规划[J].测绘学报,2019,48(2):256-264. |
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| 作者姓名： | 苗润龙 庞硕 姜大鹏 董早鹏 |
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| 作者单位： | 哈尔滨工程大学船舶工程学院水下机器人技术重点实验室,黑龙江 哈尔滨,150001;武汉理工大学交通学院,湖北 武汉,430063 |
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| 基金项目： | 国家自然科学基金（51209051；61175095；51579022） |
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| 摘 要： | 海洋自主航行器在对海底地形测绘和水文信息搜集过程中,简单锯齿形完全遍历路径规划算法对多海湾海底地形探测易出现重复区域和遗漏区域的问题。本文提出了遗漏海湾和重复海湾及其进入点、退出点和门户的路径规划环境表达概念,并将其应用在基于行为的锯齿形完全遍历路径规划改进算法中,有效地减少了海洋自主航行器全覆盖地形测绘的重复区域和遗漏区域。在网格化定常流场海域内,对某一阻力特性已知的自主水下机器人进行了完全遍历路径规划仿真,验证了基于重复和遗漏海湾搜索行为的完全遍历路径规划算法的遍历性和不重复性,并降低了区域全覆盖地形测绘任务的耗能。最终,通过小型无人艇湖试验证了算法在完全遍历路径规划中的节能性和实用性。
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| 关 键 词： | 海洋自主航行器 海底地形测绘 完全遍历路径规划 重复海湾搜索行为 遗漏海湾搜索行为 |
| 收稿时间： | 2018-08-16 |
| 修稿时间： | 2018-10-17 |
Complete coverage path planning for autonomous marine vehicle used in multi-bay areas |
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| MIAO Runlong,PANG Shuo,JIANG Dapeng,DONG Zaopeng.Complete coverage path planning for autonomous marine vehicle used in multi-bay areas[J].Acta Geodaetica et Cartographica Sinica,2019,48(2):256-264. |
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| Authors: | MIAO Runlong PANG Shuo JIANG Dapeng DONG Zaopeng |
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| Institution: | 1. National Key Laboratory of Autonomous Underwater Vehicle, College of Shipbuilding Engineering, Harbin Engineering University, Harbin 150001, China;
2. School of Transportation, Wuhan University of Technology, Wuhan 430063, China |
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| Abstract: | When using autonomous marine vehicles (AMVs) collecting seabed or hydrologicaldata, the algorithm of simple zigzag complete traversal path planning easily leads to repeated search regions and missed search regions in multi-bay ocean environment. This paper presents the environment expression concepts of repeated bay and missed bay with their points of entry, exit, and gateway. By modifying the simple zigzag complete traversal path planning algorithm using repeated-bay searching behavior and missed-bay searching behavior based on the those environment expression concepts, the new algorithm effectively reduces the area of the repeated search regions and the missed search regions for AMVs in complete traversal tasks. The efficiency and low energy consumption of the modified algorithms were tested for complete traversal path planning by computer simulation, which simulated an autonomous underwater vehicle (AUV) with known resistance characteristic in a gridding search area with a constant current velocity and flow distribution. Finally, the energy saving property and practicability of the modified algorithm were tested for complete traversal path planning on an unmanned surface vehicle (USV) in the lake. |
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| Keywords: | autonomous marine vehicle seabed topographic mapping complete traversal path planning repeated-bay searching behavior missed-bay searching behavior |
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