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.
关键词
自适应精英蚁群/路径规划/距离参数因子/角度引导因子
Key words
adaptive elite ant colony/path planning/distance parameter factor/angle guidance factor
维普
万方数据