Path Planning of Storage and Logistics Mobile Robot Based on ACA-E Algorithm

• Published in: Journal of sensors Vol. 2022; pp. 1 - 7
• Main Author: Zhao, Yue
• Format: Journal Article
• Language: English
• Published: New York Hindawi 13.07.2022; John Wiley & Sons, Inc
• Subjects: Algorithms; Ant colony optimization; Consumption; Disaster relief; Industrialized nations; Logistics; Obstacle avoidance; Path planning; Planning; Research methodology; Robots; Sensors; Strategy; Warehouses; United States > US; China; Europe
• ISSN: 1687-725X; 1687-7268; 1687-7268
• DOI: 10.1155/2022/5757719

In this paper, warehouse logistics robot as the research object, starting from the reality of modern e-commerce logistics industry, proposed a warehousing logistics mobile robot path planning method. Ant colony algorithm is used to plan the forward path of mobile robot in static and dynamic environment of warehouse logistics. The results show that the elite-based strategy improves the global search capability of ACA and eliminates redundant nodes in the path, and the path length of the obtained plan is significantly better than that of traditional ACA, which is reduced by 3.46% and 5.90%, respectively, indicating that the elite-based strategy and the central-point-based smoothing method play their roles. The path length of the robot’s final operation is larger than that of the global path planning, which increases by 1, accounting for 6.67% of the original path length. Therefore, the storage and logistics mobile robot based on ACA-E algorithm has short driving distance and superior obstacle avoidance ability.