Path planning for mobile robot based on fast convergence ant colony algorithm

Abstract

Classical ant colony algorithm have problems such as slowness of convergence rate and liable to trap into local minimum, in order to slove these problems, a path planning for mobile robot based on fast convergence ant colony algorithm is proposed. First, the algorithm improves heuristic factor to make ants seeking towards goals instead of seeking blindly. Then, the algorithm builds an adaptive model, pheromone coefficient adjust self-adaptive is achieved, it avoids ants from trapping into local minimum, improves the pheromone updating rule, accelerates convergence rate of ant colony algorithm. Finally, the algorithm reduce searching time by removing redundant path. Comparing with the classical algorithm in simulation, the effectiveness and practicability of algorithm is proved.