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dc.contributor.authorSingh, Yen
dc.contributor.authorSharma, Sen
dc.contributor.authorSutton, Ren
dc.contributor.authorHatton, DCen
dc.date.accessioned2018-01-17T09:22:37Z
dc.date.available2018-01-17T09:22:37Z
dc.date.issued2017-11-13en
dc.identifier.issn2168-9873en
dc.identifier.urihttp://hdl.handle.net/10026.1/10602
dc.descriptionOral presentation and print abstract only; no proceedings. Abstract appeared in Journal of Applied Mechanical Engineeringen
dc.description.abstract

Unmanned surface vehicles (USV) are the recent trend in marine robotics due to their diverse application and easy deployment. Navigation of such USV in a real time marine environment is a major challenge and creates a need towards development of intelligent path planners which can increase the system autonomy. Many such intelligent path planning studies have been conducted in the area of mobile robotics but needs a lot more research to be conducted in area of marine robotics. In this study, a well know intelligent path planner A* has been implemented in a real time map using safety distance from obstacle as the criteria towards generating optimal trajectory for a single USV navigation. Different safety distances from obstacles ranging from 10 pixels to 40 pixels have been used to generate optimal trajectory and comparative performance has been analyzed in terms of computational time and path length. In this study, Portsmouth Harbour has been considered as area of study to determine the effectiveness of A* algorithm with different safety distance from obstacle as constraint. Algorithm has been validated on computer-based simulations using C++ and OpenCV libraries.

en
dc.format.extent38 - 38en
dc.language.isoenen
dc.titleUSV Navigation in a Real-Time Map using Intelligent Path Planneren
dc.typeConference Contribution
plymouth.date-start2017-11-13en
plymouth.date-finish2017-11-14en
plymouth.date-finish2017-11-14en
plymouth.issue6, supplementen
plymouth.volume6en
plymouth.conference-nameInternational Conference on Mechatronics, Automation and Smart Materialsen
dc.identifier.doi10.4172/2168-9873-C1-014en
plymouth.organisational-group/Plymouth
plymouth.organisational-group/Plymouth/Faculty of Science and Engineering
plymouth.organisational-group/Plymouth/Faculty of Science and Engineering/School of Engineering, Computing and Mathematics
plymouth.organisational-group/Plymouth/REF 2021 Researchers by UoA
plymouth.organisational-group/Plymouth/REF 2021 Researchers by UoA/UoA12 Engineering
plymouth.organisational-group/Plymouth/Research Groups
plymouth.organisational-group/Plymouth/Research Groups/Marine Institute
plymouth.organisational-group/Plymouth/Users by role
plymouth.organisational-group/Plymouth/Users by role/Academics
dc.publisher.placeParisen
dcterms.dateAccepted2017-06-30en
dc.rights.embargoperiodNot knownen
rioxxterms.versionofrecord10.4172/2168-9873-C1-014en
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserveden
rioxxterms.licenseref.startdate2017-11-13en
rioxxterms.typeConference Paper/Proceeding/Abstracten


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