Real-Time Global Optimal Path Planning of Mobile Robots Based on Modified Ant System Algorithm

摘要

A novel method for the real-time global optimal path planning of mobile robots is proposed based on the modified ant system (AS) algorithm. This method includes three steps: the first step is adopting the MAKLINK graph theory to establish the free space model of the mobile robot, the second step is adopting the Dijkstra algorithm to find a sub-optimal collision-free path, and the third step is adopting the modified AS algorithm to adjust and optimize the location of the sub-optimal path so as to generate the global optimal path. The results of simulation experiments confirm that the proposed method is effective and has better performance in convergence speed, solution variation, dynamic convergence behavior, and computation efficiency as compared with the path planning method based on the real-coded genetic algorithm.