Abstract: To address issues such as excessive turning points and suboptimal paths in traditional JPS(Jump Point Search) algorithms, an improved jump point search algorithm is proposed. First, based on the feasibility of the map, the obstacles are adaptively expanded to ensure a safe distance. Then, an improved heuristic function based on directional factor is integrated. And a key point extraction strategy is proposed to optimize the initial planned path, significantly reducing the number of expanded nodes and turning points while ensuring the shortest path. The experimental results show that compared to traditional JPS algorithms, the proposed ensures a shorter path length and fewer corners, while reducing the number of extended nodes by an average of 19% and improving search speed by an average of 21. 8%. 

Key words:  jump point search algorithm, obstacles expansion, directionality, key node extraction