Research on Path Planning for Dense Storage Systems Based on an Improved Orthogonal Jump Point Search Algorithm

Jump Point Search (JPS) algorithm is one of the fastest pathfinding algorithms currently. It only needs to traverse search on jump points, greatly reducing the number of nodes to be traversed. Especially when the scale of the map is large enough, it tests the efficiency of the algorithm. Based on the adoption of JPS, this article redefines the definition and rules of jump points and forced neighbor nodes in JPS for situations with large map scale and many vehicles. Through experiments, it is verified that the improved neighbor nodes of the JPS algorithm reduce the calculation time by about 82.79% compared to the A* algorithm. In comparison, the improved JPS algorithm is more efficient in terms of calculation time, and the length of the optimal path is close. Considering the application scenarios of AGV, the straight paths of the improved JPS algorithm better fit the motion characteristics of AGV, making it more feasible in scenarios such as dense warehousing systems.