Planning of JPS algorithm based on direction region priority improvement

In the process of processing large-scale maps with complex environment information, JPS jump point search algorithm has many ineffective expansion nodes, blind search direction and search scope, which leads to long pathfinding time and large memory cost, and so on. The two improved algorithms introduce the definition of standard center vector and constrained region, specify the priority of the jump point to be expanded in the direction according to the degree of deviation between the direction to be expanded and the target direction, and delimit the constrained region to distinguish the expansion priority of the jump point to be expanded in the region, and comprehensively judge the priority order according to the direction priority and regional priority. The simulation results show that the path finding time of the two improved JPS algorithms is significantly shorter than that of the traditional algorithms, and the number of extended invalid jump points is significantly reduced. Therefore, the improved algorithm can significantly improve the efficiency of pathfinding, and it has more application significance than the traditional JPS algorithm.