Global Path Planning for Robots Based on Improved Ant Colony Algorithm
Aiming at the global path planning problem of robots,this paper proposes an improved ant colony algorithm by com-bining the artificial potential field method.Firstly,improving the repulsion function in the artificial potential field method to solve the problems of local optimality and goal unreachability;secondly,the gravitational function in the artificial potential field method is added into the heuristic function of the ant colony algorithm,which can effectively improve the convergence speed of the algorithm;then,in order to improve the searching ability of the algorithm,the improved artificial potential field force and the improved heuris-tic function are added into the state transfer function of the ant colony algorithm;finally,the output of the algorithm is optimized by using the triangular pruning.The effectiveness of the improved algorithm is verified by MATLAB simulation and ROS experiment.
万方数据
维普
