Multi-target Path Planning Method Based on Fused Ant Colony-A* Algorithm
Traditional ant colony algorithm has problems such as long search time,slow convergence speed,and single consideration factor in two-dimensional grid maps.A fusion algorithm of ant colony and A*was proposed to address the problems.First,the idea of heuristic methods was integrated into ant colony algorithm to optimize its search efficiency.Sec-ond,the max-min ant system was introduced to propose an elite ant pheromone updating rule.Meanwhile,the factors such as number of turns and turning angle were considered to increase a bending suppression operator in the heuristic information to reduce the number of bends and cumulative bending angles,avoiding the algorithm that optimize path length as a single ob-jective.Finally,an improved recall mechanism was propose to address algorithm deadlock issues.Experiments show that in the same map environment,the improved ant colony algorithm significantly reduces path length,path inflection points,and accelerates convergence speed,making it more suitable for complex environments.
ant colony algorithmA.*algorithmmax-min ant systempath planning
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