Path Planning Technologies for Autonomous Underwater Vehicles-A Review

被引:121
作者
Li, Daoliang [1 ,2 ]
Wang, Peng [2 ]
Du, Ling [2 ]
机构
[1] China Agr Univ, Coll Informat & Elect Engn, Beijing 100083, Peoples R China
[2] China Agr Univ, Beijing Engn & Technol Res Ctr Internet Things Ag, Beijing 100083, Peoples R China
基金
中国国家自然科学基金;
关键词
AUV; path planning; model building; path search; ANT COLONY OPTIMIZATION; MOBILE-ROBOT NAVIGATION; OBSTACLE AVOIDANCE; COMPLETE COVERAGE; MULTI-AUV; SEARCH ALGORITHM; POTENTIAL-FIELD; SLOCUM GLIDER; UNCERTAIN; ASTERISK;
D O I
10.1109/ACCESS.2018.2888617
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
An autonomous underwater vehicle (AUV) is an economical and safe tool that is well-suited for search, investigation, identification, and salvage operations on the sea floor. Path planning technology, which primarily includes modeling methods and path search algorithms, is an important technology for AUVs. In recent years, the AUV path planning technology has rapidly developed. Compared with land robots, AUVs must endure complex underwater environments and consider various factors, such as currents, water pressure, and topography. Challenges exist in terms of online obstacle avoidance, three-dimensional environment path planning, and the robustness of the algorithms. Adapting a complex environment and finding a suitable path planning method comprise the main problem that must be solved. In this paper, we summarize the principles, advantages, and disadvantages of modeling and path search technologies for AUVs. The most prominent feature of this paper is to summarize the improvement methods of various technical shortcomings and improve the original methods, such as dynamic obstacle avoidance, optimization path, coverage, and processing speed. In addition to summarizing the characteristics of each algorithm, this paper intuitively demonstrates the experimental environment, the real-time nature, the path planning range of the AUV, and so on. We also discuss the application scenarios of various modeling and path search technologies for AUVs. In addition, we discuss the challenges of AUVs and the direction of future research.
引用
收藏
页码:9745 / 9768
页数:24
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