基于改进麻雀搜索算法的搬运机器人路径规划

Path Planning of Handling Robot Based on Improved Sparrow Search Algorithm

针对基本麻雀搜索算法用于搬运机器人进行路径规划问题,提出一种改进的麻雀搜索算法。建立反向学习机制,优化麻雀的初始群体;引入动态搜索因子,扩大种群搜索范围;引入柯西变异,避免出现局部最优。采用栅格法构建工作环境地图,利用Matlab仿真软件,将改进算法与基本算法在不同的栅格地图下进行仿真实验,实验结果表明,改进后的算法在路径规划方面拥有更好的效果,证明了改进算法的优势和可行性。

Aiming at the problem that the basic sparrow search algorithm is used for path planning of handling robots,an improved sparrow search algorithm is proposed.Firstly,a reverse learning mechanism is established to optimize the initial population of sparrows.Secondly,the dynamic search factor is introduced to expand the population search range.Finally,cauchy mutation is introduced to avoid local optimality.The grids method is used to build the work environment map.Matlab simulation software is utilized.The simulation experiment is carried out with the improved algorithm and the basic algorithm in the grids map.The experimental results show that the improved algorithm has better effect in path planning,