印刷车间环境下AGV小车的路径优化研究

Research on Path Optimization of AGV in Printing Workshop

面对当前印刷车间AGV利用率低以及自动化程度不高的现状,提出了一种改进的RRT∗算法以优化AGV的行驶路径,进而提高印刷车间的自动化程度。针对RRT∗算法在AGV路径规划问题中存在的采样范围大,遍历节点数多,搜索效率低且搜索出来的路径用时久的问题,设置了一种目标偏向策略,将人工势场法与RRT∗算法融合应用在AGV的路径规划上,加速AGV向目标点移动,提高路径搜索效率,并通过MATLAB仿真实验将传统RRT∗算法与改进RRT∗算法进行对比。仿真结果表明,本文所提出的改进RRT∗算法,遍历节点数减少,用时更短,在印刷车间环境下找到一条更优化的路径是可行的。

Facing the current situation of low AGV utilization rate and low degree of automation in printing workshop,an improved RRT∗algorithm is proposed to optimize the driving path of AGV,and then improve the automation degree of printing workshop.Aiming at the problems of RRT∗algorithm in AGV path planning,such as large sampling range,large number of traversal nodes,low search efficiency and long time spent on the searched path,we set up a goal-biased strategy,the artificial potential field method and RRT∗algorithm are integrated and applied to the path planning of AGV.In this way,AGV can be accelerated to move to the target point and the path search efficiency can be improved,and the traditional RRT∗algorithm and the improved RRT∗algorithm are compared by MATLAB simulation experiment.The simulation results show that the improved RRT∗algorithm used in this paper reduces the number of traversal nodes,takes less time,and can find a more optimal path in the printing workshop.