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dc.contributor.authorWang, Tong
dc.contributor.authorLima, Ricardo
dc.contributor.authorGiraldi, Loic
dc.contributor.authorKnio, Omar
dc.date.accessioned2018-09-03T13:27:46Z
dc.date.available2018-09-03T13:27:46Z
dc.date.issued2018-08-24
dc.identifier.citationWang T, Lima RM, Giraldi L, Knio OM (2018) Trajectory Planning for Autonomous Underwater Vehicles in the Presence of Obstacles and a Nonlinear Flow Field using Mixed Integer Nonlinear Programming. Computers & Operations Research. Available: http://dx.doi.org/10.1016/j.cor.2018.08.008.
dc.identifier.issn0305-0548
dc.identifier.doi10.1016/j.cor.2018.08.008
dc.identifier.urihttp://hdl.handle.net/10754/628492
dc.description.abstractThis paper addresses the time-optimal trajectory planning for autonomous underwater vehicles. A detailed mixed integer nonlinear programming (MINLP) model is presented, explicitly taking into account vehicle kinematic constraints, obstacle avoidance, and a nonlinear flow field to represent the ocean current. MINLP problems pose great challenges because of the combinatorial complexity and nonconvexities introduced by the nature of the flow field. A novel solution approach in an optimization framework is developed to address associated difficulties. The main benefit of the proposed methodology is the ability to find multiple local minima. The contribution of the paper is fourfold: 1) a novel approach to integrate the flow field into the MINLP model; 2) a diversified initialization strategy using multiple waypoints, different solvers and approximated models, namely, a mixed integer linear programming model and the MINLP model with and without the flow field; 3) an algorithm that forces the solver to seek improved solutions; and 4) a parallel computing approach capitalizing on diversified initialization. The performance of the resulting methodology is illustrated on idealized case studies, and the results are used to gain insight into trajectory planning in the presence of flow fields.
dc.description.sponsorshipResearch reported in this publication was supported by research funding from King Abdullah University of Science and Technology (KAUST).
dc.publisherElsevier BV
dc.relation.urlhttps://www.sciencedirect.com/science/article/pii/S0305054818302272
dc.rightsNOTICE: this is the author’s version of a work that was accepted for publication in Computers & Operations Research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computers & Operations Research, [, , (2018-08-24)] DOI: 10.1016/j.cor.2018.08.008 . © 2018. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectOptimal trajectory planning
dc.subjectMINLP
dc.subjectMILP
dc.titleTrajectory Planning for Autonomous Underwater Vehicles in the Presence of Obstacles and a Nonlinear Flow Field using Mixed Integer Nonlinear Programming
dc.typeArticle
dc.contributor.departmentApplied Mathematics and Computational Science Program
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.identifier.journalComputers & Operations Research
dc.eprint.versionPost-print
dc.contributor.institutionCollege of Information Science and Technology, Donghua University, Shanghai, China
kaust.personWang, Tong
kaust.personLima, Ricardo
kaust.personGiraldi, Loic
kaust.personKnio, Omar
refterms.dateFOA2018-09-04T08:20:51Z
dc.date.published-online2018-08-24
dc.date.published-print2019-01


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