An Automated Guided Vehicle Path Planning Algorithm Based on Improved A* and Dynamic Window Approach Fusion

Aimed at the problems of low search efficiency A* algorithm in global path planning, not considering size AGV and too many turns, DWA easily falling into local optimization, an planning based on improved fusion is proposed. To begin, obstacle rate coefficient added to algorithm’s evaluation function build adaptive cost function; safety are increased by improving mode; extracting key nodes, a containing only starting point, endpoints obtained. The then optimized azimuth information from first node. experimental results show that static environment, compared with traditional algorithm, length reduced 1.3% 5.6%, respectively, turning times 62.5% 70%, respectively; ant colony literature, angle 29%. In dynamic running time this 12.6% other hybrid algorithms.