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dc.contributor.authorNimmo-Smith, Alex
dc.date.accessioned2018-10-29T09:34:54Z
dc.date.issued2018-10-26
dc.identifier.issn0929-5593
dc.identifier.issn1573-7527
dc.identifier.other6
dc.identifier.urihttp://hdl.handle.net/10026.1/12664
dc.description.abstract

Our research concerns the coordination and control of robotic vehicles for upper water-column oceanographic observations. In such an environment, operating multiple vehicles to observe dynamic oceanographic phenomena, such as ocean processes and marine life, from fronts to cetaceans, has required that we design, implement and operate software, methods and processes which can support opportunistic needs in real-world settings with substantial constraints. In this work, an approach for coordinated measurements using such platforms, which relate directly to task outcomes, is presented. We show the use and operational value of a new Artificial Intelligence based mixed-initiative system for handling multiple platforms along with the networked infrastructure support needed to conduct such operations in the open sea. We articulate the need and use of a range of middleware architectures, critical for such deployments and ground this in the context of a field experiment in open waters of the mid-Atlantic in the summer of 2015.

dc.format.extent1555-1574
dc.languageen
dc.language.isoen
dc.publisherSpringer Verlag
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectMixed-initiative control
dc.subjectMarine robotics
dc.subjectControl
dc.subjectArtificial Intelligence
dc.subjectOcean science
dc.subjectOperational oceanography
dc.subjectUpper water-column biology
dc.titleAdvancing multi-vehicle deployments in oceanographic field experiments
dc.typejournal-article
dc.typeJournal Article
plymouth.author-urlhttps://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000474366100016&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=11bb513d99f797142bcfeffcc58ea008
plymouth.issue6
plymouth.volume43
plymouth.publication-statusPublished
plymouth.journalAutonomous Robots
dc.identifier.doi10.1007/s10514-018-9810-x
plymouth.organisational-group/Plymouth
plymouth.organisational-group/Plymouth/Faculty of Science and Engineering
plymouth.organisational-group/Plymouth/Faculty of Science and Engineering/School of Biological and Marine Sciences
plymouth.organisational-group/Plymouth/PRIMaRE Publications
plymouth.organisational-group/Plymouth/REF 2021 Researchers by UoA
plymouth.organisational-group/Plymouth/REF 2021 Researchers by UoA/UoA07 Earth Systems and Environmental Sciences
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
dcterms.dateAccepted2018-10-03
dc.rights.embargodate2019-10-26
dc.identifier.eissn1573-7527
dc.rights.embargoperiodNot known
rioxxterms.versionofrecord10.1007/s10514-018-9810-x
rioxxterms.licenseref.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
rioxxterms.licenseref.startdate2018-10-26
rioxxterms.typeJournal Article/Review


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