An evaluation of path-planning methods for autonomous underwater vehicle based on terrain-aided navigation
| Autor: | Zheng Cong, Ye Li, Yanqing Jiang, Teng Ma, Yusen Gong, Rupeng Wang, Haowei Wu |
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| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: | |
| Zdroj: | International Journal of Advanced Robotic Systems, Vol 16 (2019) |
| Druh dokumentu: | article |
| ISSN: | 1729-8814 17298814 |
| DOI: | 10.1177/1729881419853181 |
| Popis: | 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. |
| Databáze: | Directory of Open Access Journals |
| Externí odkaz: |
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