摘要
文中针对栅格环境下移动机器人的路径规划问题,提出了一种改进的遗传算法,其主要研究工作和创意点如下:1)使用栅格方法创建实验模拟模型;2)鉴于遗传算法在生成初始种群时的盲目性,对初始化种群算法作出相应改进,从而保障路径的无障碍性;3)改良交叉、变异算子,提高种群多样性。仿真实验结果表明,改进的遗传算法比文献[1]和文献[2]中的算法具有更好的优化效果。
Aiming at the path planning problem of mobile robot in grid environment,an improved genetic algorithm is proposed.The main research work and innovation points of this paper are as follows:l)The grid method is used to establish the experimental simulation model;2)In view of the blindness of the genetic algorithm in generating the initial population,the initial population algorithm is improved so as to ensure the accessibility of the path;3)Improve the crossover and mutation operators to improve the diversity of the population.The simulation results show that the improved genetic algorithm has better optimization effect compared with literature[l]and literature[2].
作者
章学树
杨雁如
陈锡锻
ZHANG Xueshu;YANG Yanru;CHENG Xiduan(Zhejiang Industry and Trade Vocational College,Wenzhou,Zhejiang 325000,China)
出处
《移动信息》
2023年第2期98-100,103,共4页
MOBILE INFORMATION
基金
浙江工贸职业技术学院2022年度第一期教师科技创新活动计划项目(纵20220005)
2021年温州市基础性工业科技项目(G20210044)。
关键词
移动机器人
改进遗传算法
栅格法
路径规划
Mobile robot
Improved genetic algorithm
Grid method
Path planning