摘要
为提高无人船在执行水质采样任务时的路径规划效率,提出一种结合蚁群算法和萤火虫算法的路径规划算法。首先,在构建最短采水路径网络时,将转向角代价启发函数引入传统蚁群算法,减少路径搜索结果中的频繁转向;其次,剔除搜索结果中的冗余结点,进一步减少无人船转向次数,使所求得路径更适用于无人船实际航行。最后,在求解最优采样顺序时,基于随机修正的方式设计了一种改进的萤火虫算法,提升了算法的收敛速度。仿真实验结果表明,本文所设计算法能够完成水质采样任务路径规划任务,相比传统算法,搜索效率更高,有效缩短了总路径长度。
In order to improve the path planning efficiency of unmanned ships when performing water sampling tasks,a path planning algorithm combining ant colony algorithm and firefly algorithm is proposed.Firstly,when constructing the shortest path network,the steering angle cost heuristic function is introduced into the traditional ant colony algorithm to reduce frequent turns in the path search results.Then,redundant nodes in the search results are removed to further reduce the number of turns of the unmanned ship,so that the obtained path is more suitable for the unmanned ship.Finally,when solving the optimal sampling order,an improved firefly algorithm is designed based on random correction,which improves the convergence speed of the algorithm.The simulation results show that the algorithm designed in this paper can complete the path planning task of water sampling task.Compared with the traditional algorithm,the search efficiency is higher and the total path length is effectively shortened.
作者
何世鹏
金世俊
He Shipeng;Jin Shijun(School of Instrument Science and Engineering,Southeast University,Nanjing 210096,China)
出处
《电子测量技术》
北大核心
2023年第19期82-86,共5页
Electronic Measurement Technology
关键词
蚁群算法
萤火虫算法
无人船
路径规划
ant colony algorithm
firefly algorithm
unmanned ship
path planning
作者简介
何世鹏,硕士研究生,主要研究方向为无人船路径规划与路径跟踪。E-mail:heshipengsjz@qq.com;通信作者:金世俊,副教授,硕士研究生导师,主要研究方向为服务机器人的环境检测及信息融合、路径规划、地图创建、图像分析、运行控制,水声测试用系统及装备。E-mail:jinsj@seu.edu.cn
