基于改进蚁群算法的移动机器人路径规划研究

doi:10.16180/j.cnki.issn1007-7820.2019.09.002

Abstract

Abstract:

In order to solve the problem that the traditional Ant Colony (AC) algorithm had a slow convergence speed and was easy to fall into a local optimal solution, an improved AC algorithm was proposed and applied to the path planning problem of mobile robots. This method built the environment using the grid model, and the obstacles were expanded to effectively reduce the possibility of the moving mobile robot colliding with obstacles. By constructing the heuristic function, the length of the ant colony search path was reduced. The pheromone diffusion algorithm was used to improve the global search ability of the algorithm in the initial stage, so as to accelerate the late convergence speed of the algorithm. The simulation results showed that the proposed improved AC algorithm could plan the optimal path. Besides, compared to the traditional method, the proposed improved AC algorithm doubled convergence speed.

Key words: grid map, ant colony algorithm, pheromone diffusion, heuristic function, path planning, move robot

CLC Number:

TP242.6

LIU Xuefang,ZENG Guohui,HUANG Bo,LU Dunke. Research on Path Planning of Mobile Robot Based on Improved Ant Colony Algorithm[J].Electronic Science and Technology, 2019, 32(9): 5-9.

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地图模型	性能指标	传统蚁群算法	改进蚁群算法
20×20	最优路径长度	34.870	28.627
	最佳迭代次数	44	18
30×30	最优路径长度	52.426	43.941
	最佳迭代次数	38	23

Research on Path Planning of Mobile Robot Based on Improved Ant Colony Algorithm

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