The Path Planning of Mobile Robot Based on Improved Ant Colony Algorithm
Aiming at the shortcomings of the ant colony algorithm,which is slow to converge and easy to fall into the local opti-mal solution,this paper proposes a new improved algorithm,first,the relationship between the current node of the ant and the node to be selected at the next moment is introduced into the heuristic function,and then changes the pheromone update rules.Using two different grid maps to simulate the traditional ant colony algorithm and improved algorithm in Matlab.In the complex map environment,the simulation results show that the basic ant colony algorithm has 15 iterations and the shortest path is 31.21,while the improved algorithm in this paper converges faster,with 9 iterations and 28.63.The improved algorithm not only im-proves the convergence speed,but also avoids the traditional ant colony algorithm easily falling into the local optimal solution.
Ant Colony AlgorithmMobile RobotPath PlanningHeuristic Function
NETL
NSTL
万方数据
维普
