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Intelligent Path Planning Technologies of Underwater Vehicles: a Review

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Abstract

Underwater vehicles are important tools for marine resource exploration and exert important effects in civil and military fields. Path planning is an important part in the field of underwater vehicle control. At present, graph searching-type algorithms, sampling-based algorithms, and potential field-based algorithms have been widely used in the field of path planning. However, traditional methods exhibit poor adaptability to a dynamically unstructured environment. With the rapid development of artificial intelligence, artificial intelligence methods centering on machine learning have been gradually applied to the field of path planning and have shown advantages in terms of adaptability to an unstructured environment. The emphasis laid on the intelligent path planning technologies and the characteristics of these technologies or algorithms used in the present underwater vehicle path planning were introduced in detail in this work. The collaborative and coverage path planning technology of underwater vehicles were summarized. Aiming at the problems existing in current path planning of underwater vehicles, the final development direction of them is prospected.

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Acknowledgements

This work was supported by national key research and development program, the research on key technologies of intelligent model and precise control of aquaculture facilities under grant 2017YFD0701702.

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  1. Yizhuo Mu and Yaqian Wang contributed equally to this work.

Authors and Affiliations

  1. National Innovation Center for Digital Fishery, China Agricultural University, Beijing, 100083, China

    Dong An, Yizhuo Mu, Yaqian Wang, Baoke Li & Yaoguang Wei

  2. Key Laboratory of Smart Farming Technologies for Aquatic Animal and Livestock, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing, 100083, China

    Dong An, Yizhuo Mu, Yaqian Wang, Baoke Li & Yaoguang Wei

  3. Beijing Engineering and Technology Research Center for Internet of Things in Agriculture, China Agricultural University, Beijing, 100083, China

    Dong An, Yizhuo Mu, Yaqian Wang, Baoke Li & Yaoguang Wei

  4. College of Information and Electrical Engineering, China Agricultural University, 17 Tsinghua East Road, Beijing, 100083, China

    Dong An, Yizhuo Mu, Yaqian Wang, Baoke Li & Yaoguang Wei

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  1. Dong An
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An, D., Mu, Y., Wang, Y. et al. Intelligent Path Planning Technologies of Underwater Vehicles: a Review. J Intell Robot Syst 107, 22 (2023). https://doi.org/10.1007/s10846-022-01794-y

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