关键词: 惯性蚁群算法, 路径规划, 信息素挥发系数

Abstract: Ant colony algorithm for mobile robot under grid environment is defective in slow running, many broken lines, frequent turning points and local optimum. In order to obtain optimum path, this paper presents the inertia ant algorithm. Based on the initial path planned by traditional ant colony algorithm, the inertia principle is used to traverse all the nodes on initial path, deleting intermediate node when there is no obstacle existing between the two nodes and changing for optimum path. On the basis of path information, dynamically adjusting the pheromone evaporation coefficient, it can improve environmental adaptation performance of ant colony algorithm. The simulation results show that the inertia ant algorithm can quicker find the optimum path, and it can effectively optimize path quality.

Key words: inertia ant algorithm, path planning, pheromone evaporation coefficient