无人水面艇具备非线性、欠驱动的特点，尤其在外界海浪等的干扰因素作用下仅能确定局部最优路径，不能获取全局最优路径，导致无人水面艇运动控制效果下降，为此提出基于人工势场法和A-star算法的无人水面艇运动控制方法。在人工势场法中引入振荡势场，使无人水面艇能够跳出受力平衡的困境，从而确定局部最优路径。采用A-star算法进行海上运动区域路径搜索，结合局部最优路径以及路径平滑处理确定全局最优路径。根据航行路径规划结果，采用双闭环控制器计算无人水面艇的期望速度和航向角速度，通过差速推进器实现无人水面艇的运动控制。实验结果显示，该方法能有效控制无人水面艇避开障碍物，安全抵达目标点，无人水面艇控制成功率高，实际应用效果好。
Unmanned surface vessels have nonlinear and underactuated characteristics, especially under the interference of external waves, they can only determine the local optimal path and cannot obtain the global optimal path, resulting in a decrease in the motion control effect of unmanned surface vessels. Therefore, a motion control method for unmanned surface vessels based on artificial potential field method and A-star algorithm is proposed. Introducing oscillatory potential field into the artificial potential field method enables unmanned surface vessels to escape the dilemma of force balance and determine the local optimal path. Using the A-star algorithm for path search in maritime motion areas, combined with local optimal paths and path smoothing processing to determine the global optimal path. Based on the navigation path planning results, a dual closed-loop controller is used to calculate the expected speed and heading angular velocity of the unmanned surface vessel, and the motion control of the unmanned surface vessel is achieved through a differential thruster. The experimental results show that this method can effectively control unmanned surface vessels to avoid obstacles and safely reach the target point. The success rate of unmanned surface vessel control is high, and the practical application effect is good.
2025,47(7): 94-98 收稿日期：2025-1-9
DOI：10.3404/j.issn.1672-7649.2025.07.018
分类号：U675.79
基金项目：山东省船舶控制工程与智能系统工程技术研究中心科研开放专项资金资助项目（SSCC20250003）
作者简介：汤华鹏(1986-),男,硕士,讲师,研究方向为船舶智能制造及运动控制
参考文献：
[1] 包涵, 杨林初, 郁家丞, 等. 基于改进灰狼算法的无人船路径规划[J]. 船舶工程, 2024, 46(10): 1-11.
BAO H, YANG L C, YU J C, et al. Path planning for unmanned surface vehicle based on improved grey wolf optimization algorithm[J]. Ship Engineering, 2024, 46(10): 1-11.
[2] 白响恩, 孙广志, 徐笑锋. 基于改进粒子群算法的海流环境下无人水面艇路径规划[J]. 上海海事大学学报, 2023, 44(4): 1-7.
BAI X E, SUN G Z, XU X F. Path planning of unmanned surface vessels in ocean current environment based on improved particle swarm optimization algorithm[J]. Journal of Shanghai Maritime University, 2023, 44(4): 1-7.
[3] ZHANG R , LIU Y , ANDERLINI E. Robust trajectory tracking control for unmanned surface vessels under motion constraints and environmental disturbances:[J]. Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment, 2022, 236(2): 394-411.
[4] 何志强, 专祥涛, 梁杰, 等. 基于区域人工势场的无人船目标跟踪策略研究[J]. 中国造船, 2023, 64(1): 236-245.
HE Z Q, ZHUAN X T LIANG J, et al. Research on target tracking strategy of unmanned surface vessel based on regional artificial potential field[J]. Shipbuilding of China, 2023, 64(1): 236-245.
[5] 舒伟楠, 赵建森, 谢宗轩, 等. 基于改进A*算法的水面无人艇路径规划[J]. 上海海事大学学报, 2022, 43(2): 1-6.
SHU W N, ZHAO J S, XIE Z X, et al. Path planning for unmanned surface vessels based on improved A * algorithm[J]. Journal of Shanghai Maritime University, 2022, 43(2): 1-6.
[6] 支琛博, 张爱军, 杜新阳, 等. 改进A*算法的移动机器人全局路径规划研究[J]. 计算机仿真, 2023, 40(2): 486-491.
ZHI C B, ZHANG A J, DU X Y, et al. Research on global path planning of mobile robot based on improved A * algorithm research on improved A * algorithm based on real-time and security[J]. Computer Simulation, 2023, 40(2): 486-491.
