基于改进蚁群算法的移动机器人路径规划研究

In this paper, the global path planning, based on improved ant colony optimization, which is used for mobile robot is proposed. The traditional ant colony algorithm not only has the deficiency of slow convergence speed, but also tend to fall into local optimum solution. The design of local heuristic function in this paper can greatly increase the convergence speed. When it comes to pheromone update, the article just update relative path shorter part of the pheromone trails and carry on the dynamic adjustment for the amount of information based on local path information. It not only solve the problem of the pheromone concentration in convergence rate, but also ensure algorithm optimization ability and avoid premature phenomenon. The best parameter combination of the improved ant colony algorithm can be gained by conducting the simulation experiment. At the end of the article, it is proved that the efficiency of path planning is improved greatly.