• 中国科技核心期刊
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Volume 33 Issue 5
Oct  2025
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Article Contents
ZHANG Yabo, WANG Hongrui, ZHANG Haiyan, XIAO Qiang, LIU Yuxin. Method for Obstacle Avoidance Path Planning of Unmanned Surface Vessel Based on Improved Artificial Potential Field Method[J]. Journal of Unmanned Undersea Systems, 2025, 33(5): 875-882. doi: 10.11993/j.issn.2096-3920.2025-0030
Citation: ZHANG Yabo, WANG Hongrui, ZHANG Haiyan, XIAO Qiang, LIU Yuxin. Method for Obstacle Avoidance Path Planning of Unmanned Surface Vessel Based on Improved Artificial Potential Field Method[J]. Journal of Unmanned Undersea Systems, 2025, 33(5): 875-882. doi: 10.11993/j.issn.2096-3920.2025-0030

Method for Obstacle Avoidance Path Planning of Unmanned Surface Vessel Based on Improved Artificial Potential Field Method

doi: 10.11993/j.issn.2096-3920.2025-0030
  • Received Date: 2025-02-24
  • Accepted Date: 2025-03-26
  • Rev Recd Date: 2025-03-23
  • Available Online: 2025-07-14
  • To solve the problem of local path planning for obstacle avoidance of unmanned surface vessels, an artificial potential field framework was proposed, and a local path planning method for obstacle avoidance based on the dynamic construction of the water surface situation in longitude and latitude coordinates was proposed. Initially, the basic operations in the longitude and latitude coordinate system were sorted out and organized, and then the gravitational and repulsive force functions of the traditional potential function method were derived. The problems existing in the traditional potential function method and its improved methods, such as the difficulty in determining the virtual target point in the project and the inability to accurately predict the trajectory of the controlled object, were expounded. An improved potential function local path planning algorithm relying on the dynamic construction of the water surface situation was designed. Finally, the designed method was verified by simulation and sea trials. The results show that the proposed engineering method for obstacle avoidance path planning can guide the unmanned surface vessel to complete the obstacle avoidance task and has strong reliability and robustness.

     

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