一种基于改进蚁群算法的AGV小车三维路径规划研究

RESEARCH ON 3D PATH PLANNING OF AGV CAR BASED ON IMPROVED ANT COLONY ALGORITHM

针对智能仓储系统AGV小车拣货作业效率低的问题,提出一种基于改进蚁群算法的AGV小车三维路径规划方法。根据仓库原型构建立体仓库三维模型,并确定多目标三维坐标。根据两目标点的三种不同位置状态,构建AGV小车运行轨迹模型。通过增加禁忌表对基本蚁群算法进行改进,以解决三维折线路径优化问题。对比实验结果表明,改进后的蚁群算法可以避免陷入局部最优,且能够有效提高AGV小车拣货作业效率。

Aimed at the problem of low picking efficiency of the intelligent storage system AGV trolley, a three-dimensional path planning method for the AGV trolley based on an improved ant colony algorithm is proposed. A three-dimensional warehouse model was constructed based on the warehouse prototype, and multi-target three-dimensional coordinates were determined. According to the three different position states of the two target points, an AGV trolley trajectory model was constructed. The basic ant colony algorithm was improved by adding tabu lists to solve the problem of 3 D polyline path optimization. Comparative experimental results show that the improved ant colony algorithm can avoid falling into a local optimum, and can effectively improve the efficiency of AGV trolley picking operations.