Abstract
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.
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Acknowledgements
The authors are grateful to the Universiti Teknologi Malaysia and the Ministry of Higher Education (MOHE), for their partial financial support through their research funds, Vote No. R.J130000.7851.4L710, Q.J130000.2651.17J53 and R.J130000.7351.4B428.
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Mahmud, M.S.A., Abidin, M.S.Z., Buyamin, S. et al. Multi-objective Route Planning for Underwater Cleaning Robot in Water Reservoir Tank. J Intell Robot Syst 101, 9 (2021). https://doi.org/10.1007/s10846-020-01291-0
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DOI: https://doi.org/10.1007/s10846-020-01291-0