一种改进工业自动导引车路径规划算法

An Improved Industrial Automated Guided Vehicle Path Planning Algorithm

为了解决当前工业自动导引车(automated guided vehicle,AGV)栅格地图下路径规划算法存在路径转弯较多、弯曲度较大、搜路时间较长且距离障碍物近等问题,基于A^(*)算法提出了一种改进路径规划算法。首先,通过在全局地图中设置路径关键节点,生成关键点拓扑地图,并利用Floyd算法进行最短路径规划,输出路径节点集合;其次,利用A^(*)算法对集合中相邻节点进行路径规划,并将生成的路径进行拼接;最后,通过引入贝塞尔曲线对拼接路径进行平滑处理,以获取全局路径。实验结果表明:本文算法规划的路径转弯更少、弯曲度更小、搜索时间更短且能完全避开障碍物行走,更符合工业AGV的应用环境。

In order to solve problems of the most industrial automated guided vehicle(AGV)path planning algorithms under the grid map,such as more turns,greater curvature,longer search time,and proximity to obstacles,an improved path planning algorithm which is based on the A^(*) path planning algorithm was proposed.Firstly,the key point topology map was generated by setting path key nodes in the global map,and the corresponding path node set were outputted by introducing the Floyd algorithm to plan the shortest path.Secondly,the A^(*) algorithm was used to plan the adjacent node in the set,and the planning routes was spliced.Finally,the splicing path was smoothed by introducing the Bezier curve,and the global route was obtained.The experimental results show that the path planned by the improved algorithm has fewer turns,smaller curvature and shorter search time.And by using the planned path,it can completely avoid obstacle,which is more in line with the application environment of industrial AGV.