路径规划是无人艇实现安全自主航行的核心和关键，现有的无人艇路径规划算法主要为不考虑无人艇运动特性的静态运动路径规划，得到的路径为折线形路线，不适用于狭窄水域自主航行等对精度要求较高的路径规划问题。本文基于无人艇的运动数学模型，考虑无人艇的运动特性，根据出发点、初始航向、目的点及到达目的点的航向要求等约束，尽可能地减少打舵次数，采用一种复合式搜索策略数值算法，事先仿真出无人艇的运动轨迹，直至找到同时满足距离精度和航向精度要求的局部路径规划方案。最后，通过实际的算例仿真，证明了该算法的可行性和可靠性。研究结果为水面无人艇路径规划提供参考，具有重要的工程应用价值。
Path planning is the core and key to the safe and autonomous navigation of unmanned boats. The existing path planning algorithms of unmanned boats are mainly static motion path planning without considering the motion characteristics of unmanned boats. The obtained path is a polygonal path, which is not suitable for path planning problems with high accuracy requirements such as autonomous navigation in narrow waters. In this paper, based on the mathematical model of USV motion, considering the motion characteristics of USV, according to the constraints of starting point, initial heading, destination point and heading requirements of reaching destination point, the number of steering is reduced as much as possible. A composite search strategy numerical algorithm is used to simulate the trajectory of USV in advance until a local path planning scheme that meets the requirements of both distance accuracy and heading accuracy is found. Finally, the feasibility and reliability of the algorithm were proved by the actual example simulation. The research results provide a reference for the path planning of USVs and have important engineering application value.
2024,46(9): 71-75 收稿日期：2023-03-07
DOI：10.3404/j.issn.1672-7649.2024.09.012
分类号：U671.99
作者简介：贾胜伟（1995 – ），男，硕士，研究方向为船舶运动仿真与路径规划
参考文献：
[1] 陈映彬. 无人艇发展现状及其关键技术综述[J]. 科学技术创新, 2019(2): 60-61.
CHEN Ying-bin. Overview of development status and key technologies of unmanned boats[J]. Scientific and Technological Innovation, 2019(2): 60-61.
[2] 杨鑫. 无人艇操纵运动模型参数辨识研究[D]. 武汉:武汉理工大学, 2019.
[3] 玄世龙, 许志远, 孙帅, 等.基于禁忌搜索算法的无人艇路径规划研究[J]. 船舶工程: 1-8. [2022-05-24].
XUAN Shi-Long, XU Zhi-Yuan, SUN Shuai, et al. Path planning of unmanned ship based on tabu search algorithm[J]. Ship Engineering: 1-8[2022-05-24].
[4] FOX D, BURGARD W, THRUN S. The dynamic window approach to collision avoidance[J]. IEEE Robotics &Automation Magazine. 1997, 4(1): 23-33.
[5] SEDIGHI S, NGUYEN D V, KUHNERT K D. Guided hybrid A-star path planning algorithm for valet parking applications[C]//2019 5th international conference on control, automation and robotics (ICCAR). IEEE, 2019: 570-575.
[6] KOZYNCHENKOA IA, KOZYNCHENKOA AS. Applying the dynamic predictive guidance to ship collision avoidance: Crossing case study simulation[J]. Ocean Engineering, 2018, 164: 640-649.
[7] KUMAR S V, JAYAPARVATHY R, PRIYANKA B N. Efficient path planning of AUVs for container ship oil spill detection in coastal areas[J]. Ocean Engineering, 2020, 217: 107932.
[8] TSOU M C. Multi-target collision avoidance route planning under an ECDIS framework[J]. Ocean Engineering, 2016, 121(15): 268-278.
[9] YU Jiabin, DENG Wei, ZHAO Zhiyao, et, al. A hybrid path planning method for an unmanned cruise ship in water quality sampling[J]. IEEE ACESS, 2019, 2925894.
[10] 张国庆. 超恶劣海况下船舶运动简捷鲁棒自适应控制[D]. 大连: 大连海事大学, 2015.
[11] XIE Shuo, CHU Xiumin, LIU Chenguang, et, al. Parameter identification of ship motion model based on multi-innovation methods[J]. Journal of Marine Science and Technology, 2020(25): 162-184.
[12] 张显库, 金一丞. 控制系统建模与数字仿真[M]. 大连: 大连海事大学出版社. 2013.
[13] ELGHANDOUR AESHA N, SALAH AHMED M, ELMASRY YASSER A, et al. An image encryption algorithm based on bisection method and one-dimensional piecewise chaotic map[J]. IEEE ACESS,2021(9): 43411-43421.
[14] ONANAYE, ADENIYI SAMSON. Nonlinear programming: theories and algorithms of some unconstrained optimization methods(Steepest descent and Newton’s method)[J]. International Journal of Engineering and Management Research. 2020(10): 1-12.
