数字孪生驱动的车间自动导引车路径规划

AGV path planning method for workshop driven by digital twin

针对车间物流配送中的自动导引车(AGV)路径规划问题,以某企业自动化总装车间为研究对象,提出一种数字孪生驱动的AGV路径规划方法。建立了车间数字孪生环境模型,设计了基于环境地图孪生模型的无冲突路径规划算法。对于车间内实时到达的配送任务订单,采用改进的A^(*)算法结合环境地图孪生模型中的动态邻接矩阵和时间窗矩阵,按任务优先级顺序为相应的AGV规划无冲突路径,并实时更新孪生模型中的数据。所提方法使AGV配送的任务完成时间和冲突调整时间分别平均减少13.4%和17.54%。

Intelligent logistics is one of the five core industries for intelligent manufacturing,in which the workshop logistics distribution is an essential part.To solve the Automated Guided Vehicle AGV path planning problem in an automatic assembly workshop,an AGV path planning method driven by digital twin was proposed.An environment twin model of workshop was established,and then the conflict-free path planning algorithm based on the environment map twin model was designed.The twin model data is updated timely.With regard to delivery task orders arriving in real time,the improved A^(*)algorithm combined with the dynamic adjacency matrix and time window matrix in the environment map twin model was used to plan conflict-free paths for the corresponding AGV in order of task priority.The simulation results of the proposed method proved that the time cost of task completion and conflict adjustment were reduced by 13.4%and 17.54%respectively.