基于改进麻雀搜索算法的USV路径规划  

USV path planning based on hybrid improved sparrow search algorithm

作　　者：李君恩 丁天明 韩喜红 刘虎 LI Junen;DING Tianming;HAN Xihong;LIU Hu(School of Ship and Maritime Transport,Zhejiang Ocean University,Zhoushan 316022,China)

机构地区：[1]浙江海洋大学船舶与海运学院,浙江舟山316022

出　　处：《舰船科学技术》2025年第5期153-158,共6页Ship Science and Technology

基　　金：浙江省自然科学基金资助项目(LY21E090005);舟山市科技计划项目(2021C21010)。

摘　　要：针对解决无人水面艇(Unmanned Surface Vehicle,USV)路径规划的问题,提出一种改进的麻雀搜索算法。因原始麻雀搜索算法存在种群初始化方式简单,同时算法缺少变异机制,迭代后期种群多样性变差,易陷入局部最优等问题。提出混合改进策略,分别为佳点集初始化种群、螺旋搜索策略更新发现者、Tent混沌扰动策略更新跟随者,莱维飞行策略更新警戒者。实验结果表明,在测试函数中算法性能良好,收敛速度快、精度高,在仿真对比实验中规划出的路径质量高。研究成果对USV及其他领域路径规划问题具有借鉴意义。An improved sparrow search algorithm is proposed to solve the path planning problem of unmanned surface vehicle(USV).Because the original sparrow search algorithm has a simple population initialization method,and the al-gorithm lacks a mutation mechanism,the population diversity becomes worse in the later iteration,and it is easy to fall into local optimum.A hybrid improvement strategy is proposed,which initializes the population for the good point set,updates the discoverer for the spiral search strategy,updates the follower for the Tent chaotic disturbance strategy,and updates the alerter for the Levy flight strategy.The experimental results show that the algorithm has good performance,fast convergence speed and high precision in the test function,and the path quality planned in the simulation comparison experiment is high.The research results have reference significance for the research of path planning problems in USV and other fields.

关 键 词：无人水面艇 全局路径规划 麻雀搜索算法 混合改进策略 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]