AGV Path Planning based on Improved A-star Algorithm
Tao Zheng, Yanqiang Xu, Da Wei Zheng · 2019
With the wide application of Automated Guided Vehicle (Hereinafter referred to as AGV) in modern manufacturing, logistics and transportation industries, improving the work efficiency of AGV has become a major focus of the industry research. In order to reduce the limitation of two factors - AGV optimal running path search and path search speed on the efficiency of AGV, this paper based on the A-star algorithm uses the characteristics of jump point search to improve the node search mode and the search speed, and adds the angle evaluation cost function to the cost function of A-star algorithm to find the path with the least inflection point, so as to quickly find the optimal path. And the simulation experiments in this paper show that the optimized A-star algorithm can search for the optimal path, of which path search speed is faster than that of the A-star algorithm.