An Automated Guided Vehicle Path Planning Algorithm Based on Improved A* and Dynamic Window Approach Fusion
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Published:2023-09-14
Issue:18
Volume:13
Page:10326
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ISSN:2076-3417
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Container-title:Applied Sciences
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language:en
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Short-container-title:Applied Sciences
Author:
Guo Tao1ORCID, Sun Yunquan2, Liu Yong1, Liu Li1, Lu Jing1
Affiliation:
1. School of Automation and Information Engineering, Sichuan University of Science & Engineering, Yibin 644000, China 2. Academy for Engineering & Technology, Fudan University, Shanghai 200000, China
Abstract
Aimed at the problems of low search efficiency of the A* algorithm in global path planning, not considering the size of AGV and too many turns, and the DWA algorithm easily falling into local optimization, an AGV path planning algorithm based on improved A* and DWA fusion is proposed. To begin, the obstacle rate coefficient is added to the A* algorithm’s evaluation function to build an adaptive cost function; the search efficiency and path safety are increased by improving the search mode; by extracting key nodes, a global path containing only the starting point, key nodes, and endpoints is obtained. The DWA algorithm’s evaluation function is then optimized and the starting azimuth is optimized based on information from the first key node. The experimental results show that in a static environment, compared with the traditional A* algorithm and the improved A* algorithm, the path length is reduced by 1.3% and 5.6%, respectively, and the turning times are reduced by 62.5% and 70%, respectively; compared with the improved ant colony algorithm in the literature, the turning angle is reduced by 29%. In the dynamic environment, the running time of this fusion algorithm is reduced by 12.6% compared with the other hybrid algorithms.
Funder
Key Research and Development Project of Sichuan
Subject
Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science
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