Path Planning Technologies for Autonomous Underwater Vehicles-A Review

• Published in: IEEE access Vol. 7; pp. 9745 - 9768
• Main Authors: Li, Daoliang, Wang, Peng, Du, Ling
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Autonomous underwater vehicles; AUV; Computational modeling; Heuristic algorithms; model building; Modelling; Obstacle avoidance; Ocean floor; Oceans; Optimization; Path planning; path search; Planning; Search algorithms; Solid modeling; Three-dimensional displays; Water pressure
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2018.2888617

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.