文章基本信息

标题：An evaluation of path-planning methods for autonomous underwater vehicle based on terrain-aided navigation
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作者：Zheng Cong ; Ye Li ; Yanqing Jiang 等
期刊名称：International Journal of Advanced Robotic Systems
印刷版ISSN：1729-8806
电子版ISSN：1729-8814
出版年度：2019
卷号：16
期号：3
页码：1-8
DOI：10.1177/1729881419853181
出版社：SAGE Publications
摘要：This article presents a comparison of different path-planning algorithms for autonomous underwater vehicles using terrain-aided navigation. Four different path-planning methods are discussed: the genetic algorithm, the A* algorithm, the rapidly exploring random tree* algorithm, and the ant colony algorithm. The goal of this article is to compare the four methods to determine how to obtain better positioning accuracy when using terrain-aided navigation as a means of navigation. Each algorithm combines terrain complexity to comprehensively consider the motion characteristics of the autonomous underwater vehicles, giving reachable path between the start and end points. Terrain-aided navigation overcomes the challenges of underwater domain, such as visual distortion and radio frequency signal attenuation, which make landmark-based localization infeasible. The path-planning algorithms improve the terrain-aided navigation positioning accuracy by considering terrain complexity. To evaluate the four algorithms, we designed simulation experiments that use real-word seabed bathymetry data. The results of autonomous underwater vehicle navigation by terrain-aided navigation in these four cases are obtained and analyzed.
关键词：Autonomous underwater vehicle ; terrain-aided navigation (TAN) ; path-planning ; genetic algorithm (GA)