Abstract: To solve the problems of using traditional A^* algorithm for AGV path planning,such as multiple search nodes,redundant and uneven paths,and inability to handle random obstacles in complex environments,a real-time path planning and obstacle avoidance method for Automated Guided Vehicles (AGVs) was designed by integrating improved A^* algorithm and Dynamic Window Approach (DWA) algonthm. Firstly,an adaptive evaluation function was designed based on the traditional A^* algorithm evaluation function,allowing the algorithm to adaptively adjust according to the surrounding environment during the search process,thereby improving the speed and flexibility of the algorithm. Secondly,in response to the problem of redundant nodes in the path,the Floyd algorithm was used for bidirectional smoothness path optimization,deleting redundant nodes to retain key turning points,reducing the number of turns,effectively improving path smoothness,and fully ensuring the stability of AGV operation. Finally,the improved A^* algorithm was combined with the DWA algorithm to achieve effective integration of global optimization and dynamic obstacle avoidance in path planning. This comprehensive method not only enhances the path planning ability of AGV in complex environments,but also improves obstacle avoidance performance,providing a more reliable solution for the practical application of AGV.

Key words: A^* algorithm, Dynamic Window Approach (DWA) algorithm, fusion algorithm, Automated Guided Vehicle (AGV), real-time path planning, dynamic obstacle avoidance