Improved Adaptive Elite Ant Colony Algorithm for Robot Path Planning
Aiming at the basic ant colony algorithm's problems of long path planning time,slow convergence speed,and high number of iterative stabilization in 2D grid maps for mobile robots,an improved adaptive elite ant colony algorithm was proposed.The algorithm improved the heuristic information function by introducing a distance parameter factor,selected the next node by using an adaptive pseudo-random state transfer rule,and also fused the angle guidance factor into the transfer probability to reduce the search blindness,thus shortening the search time.In addition,an adaptive pheromone weight updating strategy was defined to reward the pheromone only for the optimal paths found in the contemporary search,which further improved the convergence speed.The ablation experiments,comparative experiments under different scales and environments showed that the improved algorithm plans better paths and converges faster,verifying the superiority and feasibility of the algorithm.
adaptive elite ant colonypath planningdistance parameter factorangle guidance factor
万方数据
维普
