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 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.

[1]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[2]  Ho-Hwan Chun,et al.  Hydrodynamic design of an underwater hull cleaning robot and its evaluation , 2012 .

[3]  Margarida C. Coelho,et al.  Multi-objective optimization for short distance trips in an urban area: choosing between motor vehicle or cycling mobility for a safe, smooth and less polluted route , 2017 .

[4]  V. R. Lalithambika,et al.  Terrain Based D∗ Algorithm for Path Planning , 2016 .

[5]  Hamidreza Maghsoudlou,et al.  Bi-objective optimization of a three-echelon multi-server supply-chain problem in congested systems: Modeling and solution , 2016, Comput. Ind. Eng..

[6]  Masoud Rabbani,et al.  A stochastic multi-period industrial hazardous waste location-routing problem: Integrating NSGA-II and Monte Carlo simulation , 2019, Eur. J. Oper. Res..

[7]  Zhenyu Yang,et al.  Simplified Modelling and Identification of an Inspection ROV , 2018 .

[8]  Zaharuddin Mohamed,et al.  Solving an Agricultural Robot Routing Problem with Binary Particle Swarm Optimization and a Genetic Algorithm , 2018 .

[9]  Saoussen Krichen,et al.  A multi operator genetic algorithm for solving the capacitated vehicle routing problem with cross-docking problem , 2016, 2016 IEEE Symposium Series on Computational Intelligence (SSCI).

[10]  Voratas Kachitvichyanukul,et al.  Two solution representations for solving multi-depot vehicle routing problem with multiple pickup and delivery requests via PSO , 2015, Comput. Ind. Eng..

[11]  Xiaogang Li,et al.  Multi-objective optimization in ship weather routing , 2017, 2017 Constructive Nonsmooth Analysis and Related Topics (dedicated to the memory of V.F. Demyanov) (CNSA).

[12]  Behnam Vahdani,et al.  Two-stage multi-objective location-routing-inventory model for humanitarian logistics network design under uncertainty , 2018 .

[13]  S. Seyedtabaii,et al.  Robust ROV path following considering disturbance and measurement error using data fusion , 2016 .

[14]  Peter J. Fleming,et al.  Genetic Algorithms for Multiobjective Optimization: FormulationDiscussion and Generalization , 1993, ICGA.

[15]  Olinto César Bassi de Araújo,et al.  Genetic local search algorithm for a new bi-objective arc routing problem with profit collection and dispersion of vehicles , 2018, Expert Syst. Appl..

[16]  Xiaowei Wang,et al.  Path Planning under Constraints and Path Following Control of Autonomous Underwater Vehicle with Dynamical Uncertainties and Wave Disturbances , 2020, J. Intell. Robotic Syst..

[17]  Bing-Hai Zhou,et al.  Multi-objective optimization of material delivery for mixed model assembly lines with energy consideration , 2018, Journal of Cleaner Production.

[18]  Xiaowei Shao,et al.  Multi-type multi-objective imaging scheduling method based on improved NSGA-III for satellite formation system , 2019, Advances in Space Research.

[19]  Yu-Hsien Lin,et al.  The optimal route planning for inspection task of autonomous underwater vehicle composed of MOPSO-based dynamic routing algorithm in currents , 2018, Applied Ocean Research.

[20]  Antonios Tsourdos,et al.  An energy-efficient path planning algorithm for unmanned surface vehicles , 2018, Ocean Engineering.

[21]  Baotong Li,et al.  Topology optimization techniques for mobile robot path planning , 2019, Appl. Soft Comput..

[22]  Panagiotis Tsiotras,et al.  Multiresolution Motion Planning for Autonomous Agents via Wavelet-Based Cell Decompositions , 2012, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[23]  Michihisa Iida,et al.  Multi-objective path planner for an agricultural mobile robot in a virtual greenhouse environment , 2019, Comput. Electron. Agric..

[24]  Andrej Babinec,et al.  Modelling of Mechanical and Mechatronic Systems MMaMS 2014 Path planning with modified A star algorithm for a mobile robot , 2014 .

[25]  Mehdi Rashidnejad,et al.  A bi-objective model of preventive maintenance planning in distributed systems considering vehicle routing problem , 2018, Comput. Ind. Eng..

[26]  Lothar Thiele,et al.  Comparison of Multiobjective Evolutionary Algorithms: Empirical Results , 2000, Evolutionary Computation.

[27]  Hamid Shahbandarzadeh,et al.  Using Pareto-based multi-objective Evolution algorithms in decision structure to transfer the hazardous materials to safety storage centre , 2018 .

[28]  Richard Bellman,et al.  ON A ROUTING PROBLEM , 1958 .

[29]  Lothar Thiele,et al.  Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach , 1999, IEEE Trans. Evol. Comput..

[30]  Pierre Melchior,et al.  Multi-criteria trajectory optimization for autonomous vehicles , 2017 .

[31]  Kostas E. Bekris,et al.  Asymptotically Near-Optimal Planning With Probabilistic Roadmap Spanners , 2013, IEEE Transactions on Robotics.

[32]  Ivan Petrovic,et al.  A visibility graph based method for path planning in dynamic environments , 2011, 2011 Proceedings of the 34th International Convention MIPRO.

[33]  Carlos A. Coello Coello,et al.  THEORETICAL AND NUMERICAL CONSTRAINT-HANDLING TECHNIQUES USED WITH EVOLUTIONARY ALGORITHMS: A SURVEY OF THE STATE OF THE ART , 2002 .

[34]  Ganesan Poonthalir,et al.  A Fuel Efficient Green Vehicle Routing Problem with varying speed constraint (F-GVRP) , 2018, Expert Syst. Appl..

[35]  Marco Laumanns,et al.  Performance assessment of multiobjective optimizers: an analysis and review , 2003, IEEE Trans. Evol. Comput..

[36]  Kalyanmoy Deb,et al.  An Evolutionary Many-Objective Optimization Algorithm Using Reference-Point-Based Nondominated Sorting Approach, Part I: Solving Problems With Box Constraints , 2014, IEEE Transactions on Evolutionary Computation.