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A Review of Path Planning Methods for Unmanned Surface Vehicles

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DOI: 10.23977/autml.2025.060202 | Downloads: 6 | Views: 277

Author(s)

Shenao Zhang 1, Huixia Zhang 2, Andrii Obrubov 3, Yaning Xu 1, Jian Ma 2, Liang Zhong 1

Affiliation(s)

1 Makarov College of Marine Engineering, Jiangsu Ocean University, Lianyungang, China
2 School of Ocean Engineering, Jiangsu Ocean University, Lianyungang, China
3 Department of Ship Electrical Power Systems, Admiral Makarov National University of Shipbuilding, Mykolaiv, Ukraine

Corresponding Author

Huixia Zhang

ABSTRACT

Unmanned Surface Vehicles (USVs), as essential platforms for intelligent maritime operations, rely heavily on efficient and reliable path planning to achieve autonomous navigation. This paper systematically reviews major path planning methods for USVs, including global planning approaches based on graph search and intelligent optimization, as well as local planning techniques such as the Dynamic Window Approach, Artificial Potential Field, and Rapidly-Exploring Random Tree. A comparative analysis of these algorithms highlights their respective strengths and limitations, while summarizing key directions of academic improvements. By integrating existing findings, this review provides a structured perspective on the evolution of USV path planning methodologies and their practical implications. Finally, future perspectives are summarized, including AI-driven autonomous learning and generalization, multimodal perception and intelligent decision-making integration, distributed cooperation and large-scale swarm control, etc.

KEYWORDS

Unmanned Surface Vehicle (USV), Path Planning, Autonomous Navigation

CITE THIS PAPER

Shenao Zhang, Huixia Zhang, Andrii Obrubov, Yaning Xu, Jian Ma, Liang Zhong, A Review of Path Planning Methods for Unmanned Surface Vehicles. Automation and Machine Learning (2025) Vol. 6: 11-20. DOI: http://dx.doi.org/10.23977/autml.2025.060202.

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