Path Planning For A Mobile Robot Using The Chessboard Method And Gray Wolf Optimization Algorithm In Static And Dynamic Environments
The Grey Wolf Optimization (GWO) algorithm, a computational optimization method inspired by the social behavior of wolves, has recently been effectively used to solve optimization and routing problems. This paper proposes a metaheuristic approach named Grey Wolf Optimization (GWO) inspired by grey w...
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University of Qom
2024-09-01
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| Series: | مدیریت مهندسی و رایانش نرم |
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| Online Access: | https://jemsc.qom.ac.ir/article_3049_8a6b08777d793f067521895429c17dda.pdf |
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| _version_ | 1832577541110497280 |
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| author | Ali Hatami Zadeh Javad Sharifi Meysam Yadegar |
| author_facet | Ali Hatami Zadeh Javad Sharifi Meysam Yadegar |
| author_sort | Ali Hatami Zadeh |
| collection | DOAJ |
| description | The Grey Wolf Optimization (GWO) algorithm, a computational optimization method inspired by the social behavior of wolves, has recently been effectively used to solve optimization and routing problems. This paper proposes a metaheuristic approach named Grey Wolf Optimization (GWO) inspired by grey wolves. Four types of grey wolves, namely alpha, beta, delta, and omega, are employed to simulate the leadership hierarchy. Additionally, three main stages of hunting—searching for prey, encircling prey, and attacking prey—are implemented. Overall, this paper examines how the combination of the chessboard method and the Grey Wolf Optimization algorithm can optimize the path planning of a mobile robot in both static and dynamic environments. The objective of this research is to shorten the path, minimize the final position to the target, avoid collisions, and prevent local minima. This paper investigates the Grey Wolf Optimization algorithm as an effective method for solving the routing problem. Simulation results demonstrate that using this algorithm leads to significant improvements in the robot's efficiency and enhanced path-planning performance in complex and dynamic environments |
| format | Article |
| id | doaj-art-8208292596bf4555b47f22a80b46956e |
| institution | Kabale University |
| issn | 2538-6239 2538-2675 |
| language | fas |
| publishDate | 2024-09-01 |
| publisher | University of Qom |
| record_format | Article |
| series | مدیریت مهندسی و رایانش نرم |
| spelling | doaj-art-8208292596bf4555b47f22a80b46956e2025-01-30T20:19:19ZfasUniversity of Qomمدیریت مهندسی و رایانش نرم2538-62392538-26752024-09-01101679110.22091/jemsc.2024.11127.11893049Path Planning For A Mobile Robot Using The Chessboard Method And Gray Wolf Optimization Algorithm In Static And Dynamic EnvironmentsAli Hatami Zadeh0Javad Sharifi1Meysam Yadegar2Msc Student of Qom University of Technology, Faculty of Electrical and computer engineering. Email: ali.hatami72@yahoo.comAssistant Professor of Qom University of Technology, Faculty of Electrical and computer engineering. Email: sharifi@qut.ac.irAssistant Professor of Qom University of Technology, Faculty of Electrical and Computer Engineering. Email: yadegar@qut.ac.irThe Grey Wolf Optimization (GWO) algorithm, a computational optimization method inspired by the social behavior of wolves, has recently been effectively used to solve optimization and routing problems. This paper proposes a metaheuristic approach named Grey Wolf Optimization (GWO) inspired by grey wolves. Four types of grey wolves, namely alpha, beta, delta, and omega, are employed to simulate the leadership hierarchy. Additionally, three main stages of hunting—searching for prey, encircling prey, and attacking prey—are implemented. Overall, this paper examines how the combination of the chessboard method and the Grey Wolf Optimization algorithm can optimize the path planning of a mobile robot in both static and dynamic environments. The objective of this research is to shorten the path, minimize the final position to the target, avoid collisions, and prevent local minima. This paper investigates the Grey Wolf Optimization algorithm as an effective method for solving the routing problem. Simulation results demonstrate that using this algorithm leads to significant improvements in the robot's efficiency and enhanced path-planning performance in complex and dynamic environmentshttps://jemsc.qom.ac.ir/article_3049_8a6b08777d793f067521895429c17dda.pdfpath planningdynamic environmentgrey wolf optimization algorithmmobile robot |
| spellingShingle | Ali Hatami Zadeh Javad Sharifi Meysam Yadegar Path Planning For A Mobile Robot Using The Chessboard Method And Gray Wolf Optimization Algorithm In Static And Dynamic Environments مدیریت مهندسی و رایانش نرم path planning dynamic environment grey wolf optimization algorithm mobile robot |
| title | Path Planning For A Mobile Robot Using The
Chessboard Method And Gray Wolf Optimization
Algorithm In Static And Dynamic Environments |
| title_full | Path Planning For A Mobile Robot Using The
Chessboard Method And Gray Wolf Optimization
Algorithm In Static And Dynamic Environments |
| title_fullStr | Path Planning For A Mobile Robot Using The
Chessboard Method And Gray Wolf Optimization
Algorithm In Static And Dynamic Environments |
| title_full_unstemmed | Path Planning For A Mobile Robot Using The
Chessboard Method And Gray Wolf Optimization
Algorithm In Static And Dynamic Environments |
| title_short | Path Planning For A Mobile Robot Using The
Chessboard Method And Gray Wolf Optimization
Algorithm In Static And Dynamic Environments |
| title_sort | path planning for a mobile robot using the chessboard method and gray wolf optimization algorithm in static and dynamic environments |
| topic | path planning dynamic environment grey wolf optimization algorithm mobile robot |
| url | https://jemsc.qom.ac.ir/article_3049_8a6b08777d793f067521895429c17dda.pdf |
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