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Path Planning Technologies for Autonomous Underwater Vehicles-A Review

Journal

IEEE ACCESS
Volume 7, Issue -, Pages 9745-9768

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2018.2888617

Keywords

AUV; path planning; model building; path search

Funding

  1. RAMP
  2. D and Demonstration of Intelligent Control Technology Equipment for Large-Scale Freshwater Fish Healthy Breeding [Z171100001517016]
  3. National Natural Science Foundation of China [61571444]
  4. Study on Mechanism and Method of Rapid Detection of Trace Toxic Nitrogen in Aquaculture Water Based on SERS Light [2018QC188]

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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.

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