【摘要】 针对传统A*算法在物流分拣机器人路径规划中存在搜索范围大、转折多、路径平滑度低等缺点，对A*算法进行评价函数改进优化。并且考虑到实际车身的体积，设计安全距离，防止车身与障碍物发生碰撞。通过Matlab对自动引导车（Automated Guided Vehicle,AGV）的路径规划进行仿真实验，与传统A*算法相比，路径转折幅度减少了51.7%，转折次数减少了28.6%，遍历节点数减少了48.5%，路径距离也略微减少。与此同时，将改进后的A*算法与动态窗口法相结合，提出了改进融合算法，该算法在保证路径达到全局最优的同时实现局部优化，使AGV安全快速的达到目标点。更多还原

【Abstract】 Aiming at the shortcomings of traditional A* algorithm in the path planning of logistics sorting robot,such as large search range,multiple turning points and low path smoothness,the evaluation function of A* algorithm was improved and optimized. In addition,considering the actual volume of the body,the safety distance is designed to prevent the collision between the body and obstacles. The simulation experiment of Automated Guided Vehicle(AGV) path planning is carried out by Matlab.Compared with the traditional A* algorithm,the path turning amplitude is reduced by 51.7%,the number of turning times is reduced by 28.6%,the number of traversing nodes is reduced by 48.5%,and the path distance is also slightly reduced. At the same time,the improved fusion algorithm is proposed by combining the improved A* algorithm with the dynamic window method. The algorithm can ensure the global optimal path and achieve local optimization at the same time,so that the AGV can reach the target point safely and quickly.更多还原