A Path Planning Method for Indoor Robots Based on Partial a Global A-Star Algorithm

Abstract

Considering the traditional A*algorithm being difficult to satisfy the limitation of the indoor environment space of the robot. A partial and global A-Star (P&G-A*) algorithm based on the motion model of indoor robot is proposed. LIDAR sensing system is employed into P&G-A* algorithm to achieve both local awareness and global optimization. The real environment data is adopted for simulated experiments, and experimental results proved that the path planning time is reduced 13.31% when comparing with traditional algorithm, and actual driving distance decrease by 15.71%. Furthermore, the robot trajectory is more smoothly after P&G-A* is applied.