Multi-objective Route Planning for Underwater Cleaning Robot in Water Reservoir Tank

Underwater tank cleaning using robotic method is very crucial due to the concern on the diver’s safety in undisrupted water supply operation. A Remotely Operated Underwater Vehicles (ROV) used in the tank cleaning operation however, suffers from a high operational cost due to the lack of systematic...

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Main Authors: Mahmud, Mohd. Saiful Azimi, Zainal Abidin, Mohamad Shukri, Buyamin, Salinda, Emmanuel, Abioye Abiodun, Sahib Hasan, Hameedah
Format: Article
Published: Springer Science and Business Media B.V. 2021
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Online Access:http://eprints.utm.my/id/eprint/96073/
http://dx.doi.org/10.1007/s10846-020-01291-0
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spelling my.utm.960732022-07-03T07:20:32Z http://eprints.utm.my/id/eprint/96073/ Multi-objective Route Planning for Underwater Cleaning Robot in Water Reservoir Tank Mahmud, Mohd. Saiful Azimi Zainal Abidin, Mohamad Shukri Buyamin, Salinda Emmanuel, Abioye Abiodun Sahib Hasan, Hameedah TK Electrical engineering. Electronics Nuclear engineering Underwater tank cleaning using robotic method is very crucial due to the concern on the diver’s safety in undisrupted water supply operation. A Remotely Operated Underwater Vehicles (ROV) used in the tank cleaning operation however, suffers from a high operational cost due to the lack of systematic operator guidance in robot maneuvering. This paper presents a multi-objective approach in designing a Decision Support System (DSS) for underwater cleaning robot. To explore all feasible path, the path alternatives for every cleaning point in the tank is found using Probabilistic Roadmap (PRM). Then, an optimized sequential route are identified using Non-Dominated Sorting Genetic Algorithm using Reference Point Based (NSGA-III). Several objectives such as path length and routing angle are considered to be optimized, while ensuring constraints such as similar deployment point, maximum daily time limit and cable entanglement. To measure the quality of the proposed solution, comparisons have been done based on performance of NSGA-III with Non-Dominated Sorting Genetic Algorithm II (NSGA-II) and Multi-Objective Particle Swarm Optimization (MOPSO) by considering the C-Metric value, execution time and estimated cleaning duration. In addition, comparisons with conventional path by human operator is also conducted to validate the significance of DSS application in underwater tank cleaning. Results have shown that NSGA-III has superiorities with an improvement of 11.11% in cleaning time as compared to NSGA-II and 5.12% improvement compared to MOPSO. Springer Science and Business Media B.V. 2021 Article PeerReviewed Mahmud, Mohd. Saiful Azimi and Zainal Abidin, Mohamad Shukri and Buyamin, Salinda and Emmanuel, Abioye Abiodun and Sahib Hasan, Hameedah (2021) Multi-objective Route Planning for Underwater Cleaning Robot in Water Reservoir Tank. Journal of Intelligent and Robotic Systems: Theory and Applications, 101 (1). ISSN 0921-0296 http://dx.doi.org/10.1007/s10846-020-01291-0
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Mahmud, Mohd. Saiful Azimi
Zainal Abidin, Mohamad Shukri
Buyamin, Salinda
Emmanuel, Abioye Abiodun
Sahib Hasan, Hameedah
Multi-objective Route Planning for Underwater Cleaning Robot in Water Reservoir Tank
description Underwater tank cleaning using robotic method is very crucial due to the concern on the diver’s safety in undisrupted water supply operation. A Remotely Operated Underwater Vehicles (ROV) used in the tank cleaning operation however, suffers from a high operational cost due to the lack of systematic operator guidance in robot maneuvering. This paper presents a multi-objective approach in designing a Decision Support System (DSS) for underwater cleaning robot. To explore all feasible path, the path alternatives for every cleaning point in the tank is found using Probabilistic Roadmap (PRM). Then, an optimized sequential route are identified using Non-Dominated Sorting Genetic Algorithm using Reference Point Based (NSGA-III). Several objectives such as path length and routing angle are considered to be optimized, while ensuring constraints such as similar deployment point, maximum daily time limit and cable entanglement. To measure the quality of the proposed solution, comparisons have been done based on performance of NSGA-III with Non-Dominated Sorting Genetic Algorithm II (NSGA-II) and Multi-Objective Particle Swarm Optimization (MOPSO) by considering the C-Metric value, execution time and estimated cleaning duration. In addition, comparisons with conventional path by human operator is also conducted to validate the significance of DSS application in underwater tank cleaning. Results have shown that NSGA-III has superiorities with an improvement of 11.11% in cleaning time as compared to NSGA-II and 5.12% improvement compared to MOPSO.
format Article
author Mahmud, Mohd. Saiful Azimi
Zainal Abidin, Mohamad Shukri
Buyamin, Salinda
Emmanuel, Abioye Abiodun
Sahib Hasan, Hameedah
author_facet Mahmud, Mohd. Saiful Azimi
Zainal Abidin, Mohamad Shukri
Buyamin, Salinda
Emmanuel, Abioye Abiodun
Sahib Hasan, Hameedah
author_sort Mahmud, Mohd. Saiful Azimi
title Multi-objective Route Planning for Underwater Cleaning Robot in Water Reservoir Tank
title_short Multi-objective Route Planning for Underwater Cleaning Robot in Water Reservoir Tank
title_full Multi-objective Route Planning for Underwater Cleaning Robot in Water Reservoir Tank
title_fullStr Multi-objective Route Planning for Underwater Cleaning Robot in Water Reservoir Tank
title_full_unstemmed Multi-objective Route Planning for Underwater Cleaning Robot in Water Reservoir Tank
title_sort multi-objective route planning for underwater cleaning robot in water reservoir tank
publisher Springer Science and Business Media B.V.
publishDate 2021
url http://eprints.utm.my/id/eprint/96073/
http://dx.doi.org/10.1007/s10846-020-01291-0
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score 13.211869