动态融合蚁群算法与遗传算法的路径规划方法研究

车健波,唐东林,何媛媛,胡远遥,卢炳盛,张俊辉

Research on path planning method based on dynamic fusion of ant colony optimization and genetic algorithm

Jianbo CHE,Donglin TANG,Yuanyuan HE,Yuanyao HU,Bingsheng LU,Junhui ZHANG

表6 不同环境下各算法的路径规划性能对比

Table 6 Comparison of path planning performance of various algorithms in different environments

性能指标 算法 仿真地图 1 2 3 4 路径长度 Dijkstra 32.142 32.723 34.042 31.556 A* 30.385 31.556 32.142 30.971 PSO 29.799 30.385 31.971 28.627 DACO-GA 28.641 29.594 30.027 27.800 转弯次数 Dijkstra 6 6 10 5 A* 7 9 6 6 PSO 7 7 6 8 DACO-GA 4 3 3 2 总转弯角度/(°) Dijkstra 270.000 270.000 540.000 225.000 A* 315.000 450.000 270.000 315.000 PSO 315.000 315.000 315.000 360.000 DACO-GA 137.361 137.064 143.973 26.565 平滑度 Dijkstra 0.175 0.175 0.096 0.203 A* 0.153 0.113 0.175 0.154 PSO 0.153 0.154 0.154 0.137 DACO-GA 0.294 0.295 0.285 0.683