Adaptive path finding algorithm in dynamic environment for warehouse robot
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Ng, Mun-Kit | - |
dc.contributor.author | Chong, Yung-Wey | - |
dc.contributor.author | Ko, Kwang-man | - |
dc.contributor.author | Park, Young-Hoon | - |
dc.contributor.author | Leau, Yu-Beng | - |
dc.date.available | 2021-02-22T05:35:20Z | - |
dc.date.issued | 2020-09 | - |
dc.identifier.issn | 0941-0643 | - |
dc.identifier.issn | 1433-3058 | - |
dc.identifier.uri | https://scholarworks.sookmyung.ac.kr/handle/2020.sw.sookmyung/2433 | - |
dc.description.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. | - |
dc.format.extent | 17 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | SPRINGER LONDON LTD | - |
dc.title | Adaptive path finding algorithm in dynamic environment for warehouse robot | - |
dc.type | Article | - |
dc.publisher.location | 영국 | - |
dc.identifier.doi | 10.1007/s00521-020-04764-3 | - |
dc.identifier.scopusid | 2-s2.0-85079446146 | - |
dc.identifier.wosid | 000511078100001 | - |
dc.identifier.bibliographicCitation | NEURAL COMPUTING & APPLICATIONS, v.32, no.17, pp 13155 - 13171 | - |
dc.citation.title | NEURAL COMPUTING & APPLICATIONS | - |
dc.citation.volume | 32 | - |
dc.citation.number | 17 | - |
dc.citation.startPage | 13155 | - |
dc.citation.endPage | 13171 | - |
dc.type.docType | Article; Early Access | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Artificial Intelligence | - |
dc.subject.keywordAuthor | Path finding | - |
dc.subject.keywordAuthor | Dynamic obstacle avoidance | - |
dc.subject.keywordAuthor | Warehouse robot | - |
dc.identifier.url | https://link.springer.com/article/10.1007%2Fs00521-020-04764-3 | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
Sookmyung Women's University. Cheongpa-ro 47-gil 100 (Cheongpa-dong 2ga), Yongsan-gu, Seoul, 04310, Korea02-710-9127
Copyright©Sookmyung Women's University. All Rights Reserved.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.