一种基于改进势场法的无人艇避障路径规划工程方法

张亚博; 王宏瑞; 张海燕; 肖强; 刘宇鑫

doi:10.11993/j.issn.2096-3920.2025-0030

一种基于改进势场法的无人艇避障路径规划工程方法

doi: 10.11993/j.issn.2096-3920.2025-0030

北京航天发射技术研究所, 北京, 100076

详细信息

作者简介:
张亚博

中图分类号: U664.82; TJ630
计量
- 文章访问数: 10
- HTML全文浏览量: 5
- PDF下载量: 2
- 被引次数: 0
出版历程
- 收稿日期: 2025-02-24
- 修回日期: 2025-03-23
- 录用日期: 2025-03-26
- 网络出版日期: 2025-07-14

An Engineering Approach for Obstacle Avoidance Path Planning of Unmanned Vessel Based on Optimized Artificial Potential Field

Beijing Institute of Space Launch Technology, Beijing 100076, China

摘要

摘要: 针对无人艇避障局部路径规划问题, 依托人工势场架构, 提出了一种基于经纬度坐标水面态势动态构建的避障局部路径规划方法。首先梳理并整理了经纬度坐标系中的基本运算, 进而推导了传统势函数法的引力及斥力函数形式, 阐述了传统势函数法及其改进方法存在的在工程中虚拟目标点不好确定、被控对象轨迹无法准确预测等问题, 设计了依托水面态势动态构建的改进势函数局部路径规划算法。最后对设计的方法进行了仿真验证及海上试验, 仿真及试验结果表明, 所提出的避障路径规划工程方法能够引导无人艇完成避障任务, 具有较强的可靠性和鲁棒性。
- 无人艇 /
- 路径规划 /
- 碰撞规避 /
- 工程方法
Abstract: Aiming at the local path planning problem of obstacle avoidance for unmanned surface vessel, relying on the artificial potential field framework, a local path planning method for obstacle avoidance based on the dynamic construction of the water surface situation in longitude and latitude coordinates is proposed. Initially, the basic operations in the longitude and latitude coordinate system are sorted out and organized, and then the forms of the gravitational and repulsive force functions of the traditional potential function method are 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, are expounded. An improved potential function local path planning algorithm relying on the dynamic construction of the water surface situation is designed. Finally, the designed method is verified by simulation and sea trials. The simulation and test results show that the proposed engineering method of obstacle avoidance path planning can guide the unmanned surface vessel to complete the obstacle avoidance task, and has strong reliability and robustness.
- unmanned surface vessel /
- path planning /
- collision avoidance /
- engineering approach

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图 1 水面态势动态构建示意图

Figure 1. Schematic diagram of dynamic construction of water surface situation

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图 2 单障碍物规避示意图

Figure 2. Schematic diagram of single obstacle avoidance

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图 3 多障碍物规避示意图

Figure 3. Schematic diagram of multi-obstacle avoidance

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图 4 动态避障仿真图

Figure 4. Dynamic obstacle avoidance simulation diagram

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图 5 势场合力-里程图

Figure 5. Resultant force -mileage chart

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图 6 期望航向-里程图

Figure 6. Expected heading-mileage chart

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图 7 避障距离-里程图

Figure 7. Obstacle avoidance distance-mileage chart

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图 8 无人艇区域巡逻避障海试效果

Figure 8. Sea trial effect of unmanned vessel area patrol obstacle avoidance

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图 9 无人艇航线跟踪避障海试效果

Figure 9. Sea trial effect of unmanned vessel route tracking obstacle avoidance

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图 10 无人艇动态目标避障海试效果

Figure 10. Sea trial effect of unmanned vessel dynamic target obstacle avoidance

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表 1 无人艇状态信息

Table 1. State information of unmanned vessel

初始位置	期望位置	$ {R_{{\text{threat}}}} $/m	$ {R_{{\text{turn}}}} $/m	$ k $
[113.000 00, 21.000 00]	[113.030 00, 113.030 00]	50	30	4

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表 2 原始障碍物信息

Table 2. Information of original obstacles

第1次试验	经度/(°)	113.001 38	113.021 65	113.00212	113.00857	113.021 47	113.014 11	113.022 47	113.009 23	113.010 87	113.014 00
	维度/(°)	21.005 86	21.026 33	21.02768	21.01630	21.025 16	21.016 82	21.015 11	21.004 16	21.023 64	21.014 00
	尺寸/m	64.40	61.64	66.00	69.69	58.66	55.38	62.93	59.51	65.60	110.00
第2次试验	经度/(°)	113.011 76	113.021 18	113.001 38	113.020 84	113.001 03	113.022 96	113.014 69	113.021 28	113.020 39	113.014 00
	维度/(°)	21.019 66	21.000 95	21.002 91	21.009 51	21.013 16	21.023 85	21.013 36	21.022 64	21.019 65	21.014 00
	尺寸/m	53.42	55.53	66.46	69.00	57.63	53.73	62.92	55.52	53.25	110.00
第3次试验	经度/(°)	113.011 53	113.008 71	113.024 73	113.010 31	113.027 18	113.007 82	113.012 75	113.005 36	113.017 95	113.014 00
	维度/(°)	21.017 48	21.018 51	21.029 47	21.017 52	21.026 38	21.017 83	21.009 38	21.012 68	21.014 12	21.014 00
	尺寸/m	55.03	55.30	64.60	52.15	66.35	50.45	53.22	51.88	63.91	110.00

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表 3 归并后的障碍物信息

Table 3. Information of merged obstacles

第1次试验	经度/(°)	113.009 23	113.010 87	113.001 38	113.021 56	113.002 12	113.022 47	113.012 11
	维度/(°)	21.004 161	21.023 64	21.005 86	21.025 76	21.027 68	21.015 11	21.015 57
	尺寸/m	59.51	65.60	64.40	125.60	66.00	62.93	445.65
第2次试验	经度/(°)	113.021 47	113.014 18	113.011 77	113.021 18	113.001 39	113.020 84	113.001 03
	维度/(°)	21.021 90	21.013 83	21.019 66	21.000 95	21.002 91	21.009 51	21.013 16
	尺寸/m	327.97	136.75	53.42	55.53	66.46	69.00	57.63
第3次试验	经度/(°)	113.011 54	113.025 97
	维度/(°)	21.014 71	21.027 92
	尺寸/m	733.24	279.46

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参考文献(19)

[1]	熊勇, 余嘉俊, 张加, 等. 无人艇研究进展及发展方向[J]. 船舶工程, 2020, 42(2): 12-19.
[2]	王秀玲, 尹勇, 赵延杰, 等. 无人艇海上搜救路径规划技术综述[J]. 船舶工程, 2023, 45(4): 50-57. WANG X L, YIN Y, ZHAO Y J, et al. Overview of USV maritime search and rescue path planning technology[J]. Ship Engineering, 2023, 45(4): 50-57.
[3]	BAI X, LI B, XU X, et al. A review of current research and advances in unmanned surface vehicles[J]. J. Marine. Sci. Appl, 2022, 21: 47-58. doi: 10.1007/s11804-022-00276-9
[4]	马勇, 王雯琦, 严新平. 水域无人系统平台自主航行及协同控制研究进展[J]. 无人系统技术, 2022, 5(1): 1-16. MA Y, WANG W Q, YAN X P, et al. Research progress on autonomous navigation and cooperative control of water area unmanned system platform[J]. Unmanned Systems Technology, 2022, 5(1): 1-16.
[5]	徐筱波, 叶锴, 王登峰. 无人水面艇关键技术及军事应用[J]. 广东造船, 2023, 42(4): 35-38. XU X B, YE K, WANG D F, et al. Key technologies and military applications of USV[J]. Guangdong Shipbuilding, 2023, 42(4): 35-38.
[6]	XING B, YU M, LIU Z, et al. A review of path planning for unmanned surface vehicles[J]. Journal of Marine Science and Engineering, 2023, 11(8): 1556. doi: 10.3390/jmse11081556
[7]	MAO S, YANG P, GAO D, et al. A motion planning method for unmanned surface vehicle based on improved RRT algorithm[J]. Journal of Marine Science and Engineering, 2023, 11(4): 687. doi: 10.3390/jmse11040687
[8]	周瑞红, 李彩虹, 张耀玉, 等. 基于改进RRT算法的移动机器人路径规划[J]. 山东理工大学学报(自然科学版), 2024, 38(5): 54-60. ZHOU R H, LI C H, ZHANG Y Y, et al. Path planning of mobile robot based on the improved RRT algorithm[J]. Journal of Shandong University of Technology(Natural Science Edition), 2024, 38(5): 54-60.
[9]	张喜超, 尹勇. 基于改进RRT^算法的无人船路径规划[J]. 中国航海, 2023, 46(01): 143-147+154. ZHANG X C, YIN Y. Path planning for unmanned surface vehicle based on improved RRT~ algorithm[J]. Navigation of China, 2023, 46(1): 143-147, 154.
[10]	Dobrevski M, Skočaj D. Dynamic adaptive dynamic window approach[J]. IEEE Transactions on Robotics, 2024, 40: 3068-3081. doi: 10.1109/TRO.2024.3400932
[11]	李忠坤, 姜媛媛, 刘子厚. 基于蚁群算法融合改进动态窗口法的动态路径规划方法[J]. 佳木斯大学学报(自然科学版), 2024, 42(2): 19-23. LI Z K, JIANG Y Y, LIU Z H, et al. Dynamic path planning method based on ant colony algorithm fusion improved dynamic window method[J]. Journal of Jiamusi University(Natural Science Edition), 2024, 42(2): 19-23.
[12]	王征, 杨洋, 周帅, 等. 基于A^*-动态窗口法的无人船动态路径规划算法[J]. 海军工程大学学报, 2024(2): 13-18.
[13]	XIE S R, WU P, PENG Y, et al. The obstacle avoidance planning of USV based on improved artificial potential field[C]//2014 IEEE International Conference on Information and Automation. Hailar, China: IEEE, 2014.
[14]	李家林, 张建强, 李春来. 基于优化人工势场法的无人艇局部路径规划[J]. 舰船科学技术, 2022, 44(16): 69-73. LI J L, ZHANG J Q, LI C L, et al. Local path planning of unmanned boat based on optimized artificial potential field method[J]. Ship Science and Technology, 2022, 44(16): 69-73.
[15]	邱朋, 汪光, 赵理, 等. 采用改进人工势场法的动态无人车路径规划[J]. 机械设计与制造, 2023(3): 291-296. QIU P, WANG G, ZHAO L, et al. Unmanned vehicle path planning based on structured road improved artificial potential field method[J]. Machinery Design & Manufacture, 2023(3): 291-296.
[16]	刘涛. 基于模糊改进人工势场法的无人船路径规划研究[J]. 舰船科学技术, 2022, 44(3): 63-66. LIU T. Research on path planning of unmanned ship based on fuzzy improved artificial potential field method[J]. Ship Science and Technology, 2022, 44(3): 63-66.
[17]	刘琨, 张永辉, 任佳. 基于改进人工势场法的无人船路径规划算法[J]. 海南大学学报(自然科学版), 2016(2): 99-104. LIU K, ZHANG Y H, REN J. Path planning algorithm for unmanned surface vehicle based on an improved artificial potential field method[J]. Natural Science Journal of Hainan University, 2016(2): 99-104.
[18]	姜文, 崔化超, 戚志刚, 等. 基于多目标粒子群-人工势场法的无人艇局部航路规划[J]. 中国电子科学研究院学报, 2023, 18(9): 814-820. JIANG W, CUI H C, QI Z G, et al. Path planning of USV based on MOPSO and APF method[J]. Journal of China Academy of Electronics and Information Technology, 2023, 18(9): 814-820.
[19]	陈凯翔, 周姝婧, 许强, 等. 基于改进人工势场法的无人船动态路径规划算法研究[J]. 舰船电子对抗, 2023, 46(5): 43-48, 97. CHEN K X, ZHOU S J, XU Q, et al. Research into dynamic path planning algorithm of unmanned ship based on improved artificial potential field method[J]. Shipboard Electronic Countermeasure, 2023, 46(5): 43-48, 97.