Dynamic Path Planning for Forklift AGV Based on Smoothing A and Improved DWA Hybrid Algorithm

• Published in: Sensors (Basel, Switzerland) Vol. 22; no. 18; p. 7079
• Main Authors: Wu, Bin, Chi, Xiaonan, Zhao, Congcong, Zhang, Wei, Lu, Yi, Jiang, Di
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 19.09.2022; MDPI
• Subjects: Algorithms; Efficiency; forklift AGV; Heuristic; hybrid algorithms; improved A algorithm; improved DWA; Obstacle avoidance; Path planning; Planning; Robots; forklift AGV; improved DWA; path planning; hybrid algorithms; improved A algorithm
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s22187079

FAGV is a kind of heavy equipment in the storage environment. Its path needs to be simple and smooth and should be able to avoid sudden obstacles in the process of driving. According to the environmental characteristics of intelligent storage and the task requirements of FAGV, this paper proposed a hybrid dynamic path planning algorithm for FAGV based on improved A* and improved DWA. The improved A* algorithm can plan the global optimal path more suitable for FAGV. The improved evaluation function of DWA can ensure that the local path of FAGV is closer to the global path. DWA combines the rolling window method for local path planning to avoid sudden unknown static and dynamic obstacles. In addition, this paper verifies the effectiveness of the algorithm through simulation. The simulation results show that the algorithm can avoid obstacles dynamically without being far away from the global optimal path.