A Path Planning Method for Indoor Robots Based on Partial a Global A-Star Algorithm
Kang‐Le Wang, ShuWen Dang, Fajiang He, Cheng Peng-zhan · 2017
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.