Compared with traditional logistics warehouses, many automated warehouses use automatic guided vehicles (AGVs) instead of workers to sort the goods, which changes the working mode from “man to goods” into “goods to man”. This change not only liberates the labor of workers but also combines the mechanization and automation of automated warehouses, greatly improving working efficiency. Path planning is an important part of AGVs in the process of sorting goods in automatic warehouses. For the path planning of AGVs, the traditional A* algorithm is improved because the paths planned by the traditional A* algorithm are too long and not smooth enough and have large turning angles. In view of the above defects, the method of dynamic weighting and changing the search neighborhood is proposed to improve the traditional A* algorithm, which reduces the search nodes and raises the search speed. At the same time, the path planned by the improved A* algorithm is smoothed by higher-order Bessel curves many times, which lowers the number of turning points. Finally, the comparison of three groups of simulation experiments proves that the improvement proposed in this study is of the reference value.