基于视觉引导多AGV系统的改进A*路径规划算法

Improved A*path planning algorithm for vision-guided multi-AGV system

研究基于视觉引导自动引导车(AGV)的改进A*路径规划算法.首先,设计一种包含导航、定位和任务信息的图形编码标志方法,AGV通过识别位于车身前方网格型路径中有序排布的编码标志进行快速定位和下一位置预判,为多AGV规划奠定基础;其次,根据网格型路径构成的动态随机网络,提出一种改进A*算法,将AGV在运动时产生的动态时间耗费作为参考指标,以实现多AGV在路径网络中的路径规划和冲突避让策略,提高固定路网资源的利用效率;最后,对多AGV在网格型路径中协同工作的场景进行仿真,实验结果表明,所提出的改进算法可以有效应用于多AGV系统,并且提升整体系统的工作效率.

This paper mainly focuses on an improved A*path planning algorithm for vision-guided automated guided vehicles(AGVs).A type of graphic coded mark method is firstly designed,which includes navigation,positioning as well as task information and ensures that the AGV can recognize the orderly arranged coded marks in the path to quickly locate and predict the next position,which lays the foundation for multi-AGV planning.Then,an improved A*algorithm considering the dynamic time cost is proposed to guarantee the path planning and collision avoidance strategy of multiAGV in the path network,and effectively improve the utilization efficiency of path network resources.Finally,numerical simulation results show that the proposed improved algorithm can be effectively applied to the multi-AGV system and improve the entire work efficiency.