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dc.contributor.authorFossum, Trygve Olav
dc.contributor.authorEidsvik, Jo
dc.contributor.authorEllingsen, Ingrid H.
dc.contributor.authorAlver, Morten
dc.contributor.authorFragoso, Glaucia Moreira
dc.contributor.authorJohnsen, Geir
dc.contributor.authormendes, renato
dc.contributor.authorLudvigsen, Martin
dc.contributor.authorRajan, Kanna
dc.date.accessioned2018-08-08T11:10:47Z
dc.date.available2018-08-08T11:10:47Z
dc.date.created2018-07-29T05:28:48Z
dc.date.issued2018
dc.identifier.issn1556-4959
dc.identifier.urihttp://hdl.handle.net/11250/2508038
dc.description.abstractEfficient sampling of coastal ocean processes, especially mechanisms such as upwelling and internal waves and their influence on primary production, is critical for understanding our changing oceans. Coupling robotic sampling with ocean models provides an effective approach to adaptively sample such features. We present methods that capitalize on information from ocean models and in situ measurements, using Gaussian process modeling and objective functions, allowing sampling efforts to be concentrated to regions with high scientific interest. We demonstrate how to combine and correlate marine data from autonomous underwater vehicles, model forecasts, remote sensing satellite, buoy, and ship‐based measurements, as a means to cross‐validate and improve ocean model accuracy, in addition to resolving upper water‐column interactions. Our work is focused on the west coast of Mid‐Norway where significant influx of Atlantic Water produces a rich and complex physical–biological coupling, which is hard to measure and characterize due to the harsh environmental conditions. Results from both simulation and full‐scale sea trials are presented.nb_NO
dc.language.isoengnb_NO
dc.publisherWileynb_NO
dc.rightsNavngivelse-Ikkekommersiell 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/deed.no*
dc.titleInformation-driven robotic sampling in the coastal oceannb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionpublishedVersionnb_NO
dc.source.journalJournal of Field Roboticsnb_NO
dc.identifier.doi10.1002/rob.21805
dc.identifier.cristin1598879
dc.description.localcode© 2018 The Authors. Journal of Field Robotics published by Wiley Periodicals, Inc. This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial License.nb_NO
cristin.unitcode194,64,20,0
cristin.unitcode194,63,15,0
cristin.unitcode194,63,25,0
cristin.unitcode194,66,10,0
cristin.unitnameInstitutt for marin teknikk
cristin.unitnameInstitutt for matematiske fag
cristin.unitnameInstitutt for teknisk kybernetikk
cristin.unitnameInstitutt for biologi
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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Navngivelse-Ikkekommersiell 4.0 Internasjonal
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