基于智能物流的AGV路径优化研究

Research on AGV Path Optimization Based on Intelligent Logistics

由于现有的优化方法路径转折次数在3次以上,AGV完成任务的时间久,为此研究基于智能物流的AGV路径优化。结合智能物流的路径结构模型,规划AGV配送路径。采用自适应回归分析方式对物流数据特征进行分配,建立促进性模型。运用基于路径优化模型的A*算法进行路径规划,生成动态加权地图。结合免疫算法和蚁群算法求解最优解,输出结果完成路径优化。实验结果表明,实验组的参数优化后转折次数保持在2次以内能够寻找到最优路径,具有较高避障能力;在不同场景下,AGV完成任务的时间均在15s以下,达到较为快速的路径寻优,达到良好的优化效果。

Since the existing optimization method turns more than 3 times,and the path takes a long time for AGV to complete the task,the AGV path optimization based on intelligent logis-tics is studied.Combincd with thc path structurc modcl of intelligcnt logistics,we plan the AGV distribution path.Adaptive regression analysis was used to assign logistics data characteristics and establish a facilitating logistic model.The A×algorithm based on the path optimization model is used for path planning to generate A dynamic weighted map.Combine the immune algorithm and the ant colony algorithm to solve the optimal solution,and put the output results to com-plete the path optimization.The experimental results show that the optimal path,with high ob-stacle avoidance ability;in different scenarios,the AGV completes the task below 15s,achieving a faster path optimization and achieving good optimization effect.