Improved Heuristic JPS Algorithm for Path Planning in Intelligent Warehouse Robot

To enhance warehousing efficiency and reduce costs, it is crucial to employ appropriate path planning methods to improve the efficiency of robots performing tasks in intelligent warehouses. The JPS algorithm faces challenges such as frequent interruptions in path planning due to the grid layout of obstacles and an excessive search range, leading to increased time spent on jump point selection and decreased efficiency. This paper presents an improved heuristic JPS algorithm based on the original JPS algorithm, which reduces invalid expansion directions through an angle-based heuristic function and optimizes jump point selection using a dynamic heuristic function, thereby accelerating path planning efficiency. Additionally, buffer zones are established around obstacles, and B-spline smoothing is applied to optimize the path, ensuring the safety and stability of robot navigation. Experimental results demonstrate that the proposed algorithm reduces the search range, increases search efficiency, and produces smoother path planning curves.