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Adaptive path finding algorithm in dynamic environment for warehouse robot

Authors
Ng, Mun-KitChong, Yung-WeyKo, Kwang-manPark, Young-HoonLeau, Yu-Beng
Issue Date
Sep-2020
Publisher
SPRINGER LONDON LTD
Keywords
Path finding; Dynamic obstacle avoidance; Warehouse robot
Citation
NEURAL COMPUTING & APPLICATIONS, v.32, no.17, pp.13155 - 13171
Journal Title
NEURAL COMPUTING & APPLICATIONS
Volume
32
Number
17
Start Page
13155
End Page
13171
URI
https://scholarworks.sookmyung.ac.kr/handle/2020.sw.sookmyung/2433
DOI
10.1007/s00521-020-04764-3
ISSN
0941-0643
Abstract
Warehouse robots have been widely used by manufacturers and online retailer to automate good delivery process. One of the fundamental components when designing a warehouse robot is path finding algorithm. In the past, many path finding algorithms had been proposed to identify the optimal path and improve the efficiency in different conditions. For example, A* path finding algorithm is developed to obtain the shortest path, while D* obtains a complete coverage path from source to destination. Although these algorithms improved the efficiency in path finding, dynamic obstacle that may exist in warehouse environment was not considered. This paper presents AD* algorithm, a path finding algorithm that works in dynamic environment for warehouse robot. AD* algorithm is able to detect not only static obstacle but also dynamic obstacles while operating in warehouse environment. In dynamic obstacle path prediction, image of the warehouse environment is processed to identify and track obstacles in the path. The image is pre-processed using perspective transformation, dilation and erosion. Once obstacle has been identified using background subtraction, the server will track and predict future path of the dynamic object to avoid the obstacle.
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공과대학 (소프트웨어학부)
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