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Optimization of mobile robot path planning in semi-dynamic environment using genetic algorithm

In an Industry 4.0 framework, mobile robots are designed to perform tasks autonomously, allowing manufacturers to transform their operations which can be carried out through various integrated applications. Manufacturers could improve their productivity by remotely monitoring mobile robots and contr...

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Main Author: Kasim Hawari, Mohd Zarifitri
Format: Thesis
Language:English
English
Published: 2023
Subjects:
T Technology (General)
TJ Mechanical engineering and machinery
Online Access:http://eprints.utem.edu.my/id/eprint/28285/1/Optimization%20of%20mobile%20robot%20path%20planning%20in%20semi-dynamic%20environment%20using%20genetic%20algorithm.pdf
http://eprints.utem.edu.my/id/eprint/28285/2/Optimization%20of%20mobile%20robot%20path%20planning%20in%20semi-dynamic%20environment%20using%20genetic%20algorithm.pdf
http://eprints.utem.edu.my/id/eprint/28285/
https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=124155
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spelling my.utem.eprints.282852024-12-16T08:10:11Z http://eprints.utem.edu.my/id/eprint/28285/ Optimization of mobile robot path planning in semi-dynamic environment using genetic algorithm Kasim Hawari, Mohd Zarifitri T Technology (General) TJ Mechanical engineering and machinery In an Industry 4.0 framework, mobile robots are designed to perform tasks autonomously, allowing manufacturers to transform their operations which can be carried out through various integrated applications. Manufacturers could improve their productivity by remotely monitoring mobile robots and controlling their machines' status. Additionally, path planning for a mobile robot is the key role in the automation industry environment area to ensure the profitability achieved. In some cases, the area's environment always fluctuates according to the situation. It may cause the path for the mobile robot to have a different route to reach the goal destination. Hence, a semi-dynamic obstacle with better optimization solutions is crucial to cope with mobile robots in the industry environment. Thus, this thesis aims to develop a mobile robot for industrial applications by leveraging a genetic algorithm (GA). The main objective is to formulate an improved path planning for mobile robots based on GA considering the different obstacle percentage of each environment in the area. The environment design is based on a 2-D coordinated graph with irregular shapes as the semi-dynamic obstacle and by restructuring the genes to plan a robot path. The proposed method is validated in simulations and proven to work effectively in different environments for different obstacle percentages of each investigation conducted to replicate a semi-dynamic obstacle environment. Finally, the simulation was conducted by implementing a random algorithm to verify the proposed GA in terms of the mobile robot's minimum and maximum path lengths. The environment design for mobile robots' path planning based on industry environment shows excellent combinations with the GA method that generate the optimal path for the mobile robot with a semi-dynamic obstacle. 2023 Thesis NonPeerReviewed text en http://eprints.utem.edu.my/id/eprint/28285/1/Optimization%20of%20mobile%20robot%20path%20planning%20in%20semi-dynamic%20environment%20using%20genetic%20algorithm.pdf text en http://eprints.utem.edu.my/id/eprint/28285/2/Optimization%20of%20mobile%20robot%20path%20planning%20in%20semi-dynamic%20environment%20using%20genetic%20algorithm.pdf Kasim Hawari, Mohd Zarifitri (2023) Optimization of mobile robot path planning in semi-dynamic environment using genetic algorithm. Masters thesis, Universiti Teknikal Malaysia Melaka. https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=124155
institution Universiti Teknikal Malaysia Melaka
building UTEM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknikal Malaysia Melaka
content_source UTEM Institutional Repository
url_provider http://eprints.utem.edu.my/
language English
English
topic T Technology (General)
TJ Mechanical engineering and machinery
spellingShingle T Technology (General)
TJ Mechanical engineering and machinery
Kasim Hawari, Mohd Zarifitri
Optimization of mobile robot path planning in semi-dynamic environment using genetic algorithm
description In an Industry 4.0 framework, mobile robots are designed to perform tasks autonomously, allowing manufacturers to transform their operations which can be carried out through various integrated applications. Manufacturers could improve their productivity by remotely monitoring mobile robots and controlling their machines' status. Additionally, path planning for a mobile robot is the key role in the automation industry environment area to ensure the profitability achieved. In some cases, the area's environment always fluctuates according to the situation. It may cause the path for the mobile robot to have a different route to reach the goal destination. Hence, a semi-dynamic obstacle with better optimization solutions is crucial to cope with mobile robots in the industry environment. Thus, this thesis aims to develop a mobile robot for industrial applications by leveraging a genetic algorithm (GA). The main objective is to formulate an improved path planning for mobile robots based on GA considering the different obstacle percentage of each environment in the area. The environment design is based on a 2-D coordinated graph with irregular shapes as the semi-dynamic obstacle and by restructuring the genes to plan a robot path. The proposed method is validated in simulations and proven to work effectively in different environments for different obstacle percentages of each investigation conducted to replicate a semi-dynamic obstacle environment. Finally, the simulation was conducted by implementing a random algorithm to verify the proposed GA in terms of the mobile robot's minimum and maximum path lengths. The environment design for mobile robots' path planning based on industry environment shows excellent combinations with the GA method that generate the optimal path for the mobile robot with a semi-dynamic obstacle.
format Thesis
author Kasim Hawari, Mohd Zarifitri
author_facet Kasim Hawari, Mohd Zarifitri
author_sort Kasim Hawari, Mohd Zarifitri
title Optimization of mobile robot path planning in semi-dynamic environment using genetic algorithm
title_short Optimization of mobile robot path planning in semi-dynamic environment using genetic algorithm
title_full Optimization of mobile robot path planning in semi-dynamic environment using genetic algorithm
title_fullStr Optimization of mobile robot path planning in semi-dynamic environment using genetic algorithm
title_full_unstemmed Optimization of mobile robot path planning in semi-dynamic environment using genetic algorithm
title_sort optimization of mobile robot path planning in semi-dynamic environment using genetic algorithm
publishDate 2023
url http://eprints.utem.edu.my/id/eprint/28285/1/Optimization%20of%20mobile%20robot%20path%20planning%20in%20semi-dynamic%20environment%20using%20genetic%20algorithm.pdf
http://eprints.utem.edu.my/id/eprint/28285/2/Optimization%20of%20mobile%20robot%20path%20planning%20in%20semi-dynamic%20environment%20using%20genetic%20algorithm.pdf
http://eprints.utem.edu.my/id/eprint/28285/
https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=124155
_version_ 1818839134261739520
score 13.223943

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