摘要
针对水质监测机器人集群编队路径规划求解时,传统的粒子群优化算法(particle swarm optimization,PSO)存在搜索速度慢,容易陷入局部最优等问题,提出了一种混合粒子群优化算法(hybrid particle swarm optimization,HPSO),通过引入遗传算法(genetic algorithm,GA)中的交叉、变异等操作改变PSO中的最优粒子易趋向局部最优性,增加粒子群多样性,避免求解结果陷入局部最优;同时对算法的惯性权重进行调节,加快算法的收敛速度。仿真结果表明,在保证水质监测任务完成的前提下,HPSO相对于传统的GA能够有效的减少路径交叉节点两个,总路径长度缩短53.147 km;而相较传统的PSO而言能够有效的减少路径交叉节点5个,总路径长度缩短133.826 km,优化了编队路径规划策略,提高了算法收敛速度。
Aiming at the problems that the traditional particle swarm optimization algorithm(PSO)has the problem of slow search speed and easy to fall into local optimum when the water quality monitoring robot cluster formation path planning and solving,a hybrid particle swarm optimization algorithm(HPSO)was proposed.optimization,HPSO,by introducing crossover,mutation and other operations in the genetic algorithm(GA),the optimal particles in the PSO tend to tend to local optimality,increase the diversity of particle swarms,and avoid the solution results falling into local optimality;At the same time,the inertia weight of the algorithm is adjusted to speed up the convergence speed of the algorithm.The simulation results show that,on the premise of ensuring the completion of the water quality monitoring task,HPSO can effectively reduce the number of path intersection nodes by 2 compared with the traditional GA,and the total path length is shortened by 53.147 km;compared with the traditional PSO,it can effectively reduce the path There are 5 intersection nodes,and the total path length is shortened by 133.826 km,which optimizes the formation path planning strategy and improves the algorithm convergence speed.
作者
智超群
鲁旭涛
张丽娜
Zhi Chaoqun;Lu Xutao;Zhang Lina(College of Information and Communication Engineering,North University of China,Taiyuan 030051,China;College of Mechatronics Engineering,North University of China,Taiyuan 030051,China)
出处
《国外电子测量技术》
北大核心
2022年第5期15-20,共6页
Foreign Electronic Measurement Technology
基金
山西省重点研发计划(201903D221025)项目资助
关键词
路径规划
粒子群优化算法
遗传算法
编队控制
水质监测器人
path planning
particle swarm optimization algorithm
genetic algorithm
formation control
water quality monitor
作者简介
智超群,硕士研究生,主要研究方向为无线自组网、嵌入式系统等。E-mail:296103487@qq.com;鲁旭涛,博士,副教授,主要研究方向为无线自组网、嵌入式系统等。E-mail:tgzymail@163.com;张丽娜,硕士研究生,主要研究方向为无线自组网、嵌入式系统等。E-mail:2298815723@qq.com
