|本期目录/Table of Contents|

[1]杨理驰,史圣哲,杨静雷,等.基于改进A*算法的无人船自动靠泊路径规划[J].集美大学学报(自然科学版),2026,31(5):552-565.
 YANG Lichi,SHI Shengzhe,YANG Jinglei,et al.Autonomous Berthing Path Planning of Unmanned Vessels Based on an Enhanced A* Algorithm[J].Journal of Jimei University,2026,31(5):552-565.
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基于改进A*算法的无人船自动靠泊路径规划(PDF)
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《集美大学学报(自然科学版)》[ISSN:1007-7405/CN:35-1186/N]

卷:
第31卷
期数:
2026年第5期
页码:
552-565
栏目:
船海与交通运输工程
出版日期:
2026-09-28

文章信息/Info

Title:
Autonomous Berthing Path Planning of Unmanned Vessels Based on an Enhanced A* Algorithm
作者:
杨理驰1; 史圣哲2; 杨静雷1; 俞万能1; 廖卫强1
(1.集美大学轮机工程学院,福建 厦门 361021;2.中航工业集团特种飞行器研究所,湖北 荆门 448035)
Author(s):
YANG Lichi1; SHI Shengzhe2; YANG Jinglei1; YU Wanneng1; LIAO Weiqiang1
(1.School of Marine Engineering,Jimei University,Xiamen 361021,China;2.AVIC Special Vehicle Research Institute,Jinmen 448035,China)
关键词:
无人船; 自动靠泊; 改进A*算法; 姿态约束; 路径平滑
Keywords:
unmanned vessel; automatic berthing; improved A* algorithm; attitude constraints; path smoothing
分类号:
-
DOI:
-
文献标志码:
A
摘要:
针对传统A*算法在无人船自动靠泊路径规划中存在的冗余节点多、路径转折突兀以及终点航向难以满足靠泊姿态要求等问题,提出一种基于改进A*算法的靠泊路径规划方法。该方法在全局规划阶段引入 JPS 跳点机制与优化启发函数,以减少冗余节点扩展并提升搜索效率;在路径优化阶段结合贝塞尔曲线平滑处理与自适应末端控制点调整,实现靠泊末端航向的精确约束。仿真结果显示,在满足避障安全距离的前提下,与传统启发函数相比,新方法扩展节点数减少约35%,搜索时间缩短约18.5%,路径平滑度提升59.1%,靠泊终点航向角偏差由53.9°显著降低至5°以内,有效满足了无人船精确靠泊的姿态要求。实验结果验证了该方法在复杂港口环境中的适用性与鲁棒性。
Abstract:
To address the issues of redundant nodes,abrupt path turns,and the difficulty of meeting berthing orientation requirements in traditional A* algorithms for unmanned surface vehicle automatic berthing,this paper proposes an improved A* path planning method.At the global planning stage,the jump point search mechanism and an optimized heuristic function are introduced to reduce redundant node expansion and enhance search efficiency.At the path optimization stage,Bézier curve smoothing is combined with adaptive terminal control point adjustment to achieve precise constraints on the final berthing heading.Simulation results demonstrate that,while maintaining a safe obstacle avoidance distance,the proposed method reduces the number of expanded nodes by at least 35% and search time by approximately 18.5% compared to the traditional heuristic.Furthermore,path smoothness is improved by 59.1%,and the final berthing heading angle deviation is significantly reduced from 53.9° to within 5°,effectively meeting the attitude requirements for precise USV berthing.Experimental results verify the applicability and robustness of the proposed method in complex port environments.

参考文献/References:

相似文献/References:

[1]张丰,廖卫强,乔中飞,等.基于改进人工势场法的无人船路径规划[J].集美大学学报(自然科学版),2023,28(2):150.
 ZHANG Feng,LIAO Weiqiang,QIAO Zhongfei,et al.Path Planning of Unmanned Ship Based on Improved Artificial Potential Field Method[J].Journal of Jimei University,2023,28(5):150.

备注/Memo

备注/Memo:
更新日期/Last Update: 2026-11-01