基于改进蚁群算法的机器人全局路径规划

Global Path Planning for Robots Based on Improved Ant Colony Algorithm

针对机器人的全局路径规划问题,结合人工势场法提出一种改进蚁群算法。首先改进人工势场法中的斥力函数,解决局部最优和目标不可达的问题;其次在蚁群算法的启发函数中加入人工势场法中的引力函数,有效提高算法的收敛速度;然后为提高算法的搜索能力,在蚁群算法的状态转移函数中加入改进后的人工势场合力和改进后的启发函数;最后算法输出结果采用三角剪枝法进行优化。通过MATLAB仿真和ROS实验验证了改进算法的有效性。

Aiming at the global path planning problem of robots,this paper proposes an improved ant colony algorithm by combining 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 heuristic 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.