Author(s)

Tianxiang Yang ¹, Liping Wen ², Yiming Jia ¹

Affiliation(s)

¹ School of Ocean Engineering, Jiangsu Ocean University, Lianyungang, 222005, China
² School of Innovation and Entrepreneurship, Jiangsu Ocean University, Lianyungang, 222005, China

Corresponding Author

Tianxiang Yang

ABSTRACT

This paper presents a global path planning algorithm for unmanned surface vehicle (USV) based on an A*–fuzzy hybrid approach that integrates fuzzy collision-avoidance reasoning. To address path planning challenges in real-world scenarios, the proposed method first processes actual satellite imagery through image preprocessing and binarization to generate a grid-based navigable map. The grid map is then scaled to physical dimensions, and obstacle boundaries are dilated according to the USV minimum safety radius to ensure navigational clearance. Subsequently, the A* algorithm is employed for initial path search, while a Takagi-Sugeno (T-S) fuzzy inference model is applied to refine node selection near obstacles, enhancing local decision-making under uncertainty. Finally, the generated trajectory is simplified by retaining only critical waypoints, significantly reducing data storage requirements without compromising path quality. Simulation results demonstrate that the proposed algorithm improves both redundancy and safety in USV navigation, maintains high computational efficiency, and offers a practical solution for autonomous maritime decision-making. The approach effectively balances path optimality, obstacle avoidance capability, and memory efficiency, providing valuable support for safe USV operations.

KEYWORDS

Improved A* algorithm, T-S fuzzy inference, Map binary segmentation, Global path planning method, Safety margin

CITE THIS PAPER

Tianxiang Yang, Liping Wen, Yiming Jia. Design and Application of an A*–Fuzzy Path Planning Algorithm for Unmanned Surface Vehicle. Automation and Machine Learning (2026). Vol. 7, No. 1, 9-23. DOI: http://dx.doi.org/10.23977/autml.2026.070102.

REFERENCES

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