Research on path planning of storage robot based on the improved ant colony optimization algo-rithms
With the rapid development of the logistics industry,warehousing robots have become an impor-tant part of the logistics industry.In response to the blind nature,long search paths and waste of search re-sources of traditional ant colony algorithms in the early stages of warehousing robots,this paper proposes a fusion algorithm.Firstly,the particle swarm optimization algorithm is used to optimize the main parameters of the ant colony algorithm according to different standards,and the optimal parameter combination of the ant colony algorithm is obtained,avoiding the initial blindness of the algorithm.Secondly,a virtual target method is proposed to address the problem of long paths in semi enclosed maps.Finally,the fusion of ant colony algorithm and slime mold algorithm solved the waste of search resources.By comparing with different algorithms,our algorithm outperforms other algorithms in terms of path length,number of deadlock ants,and efficiency.
万方数据
维普
