Mobile Robot Path Planning Based on an Improved A^* Algorithm

Aiming at the problems of A^* algorithm in the large scene, such as large memory overhead and long computation time, an improved A^* algorithm is proposed based on A^* algorithm and jump point search algorithm. The algorithm expands by selecting jump points until the final path is generated. During the expansion process, a lot of unnecessary nodes in A^* algorithm which are added to OpenList and ClosedList can be replaced by jump points to reduce computation. In order to prove the validity of the improved A^* algorithm, the simulation is carried out in 2D grid map of different sizes. The simulation result shows that the improved A^* algorithm expands fewer nodes in the pathfinding process, and the pathfinding speed is faster. The acceleration effect becomes more apparent with the increase of environment map. Finally, the improved A^* algorithm is implemented on the mobile robot Turtlebot2 to conduct comparative experiments. The experimental result shows that the improved A^* algorithm can speed up by about 200% compared with the A^* algorithm when generating the same path, and it can meet the requirements of path planning for mobile robots.