Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/14296
DC FieldValueLanguage
dc.contributor.authorKealy, Allison-
dc.contributor.authorAlam, Nima-
dc.contributor.authorToth, Charles-
dc.contributor.authorMoore, Terry-
dc.contributor.authorGikas, Vassilis-
dc.contributor.authorDanezis, Chris-
dc.contributor.authorRoberts, Gethin Wyn-
dc.contributor.authorRetscher, Guenther-
dc.contributor.authorHasnur-Rabiain, Azmir-
dc.contributor.authorGrejner-Brzezinska, Dorota A.-
dc.contributor.authorHill, Chris-
dc.contributor.authorHide, Christopher D.-
dc.contributor.authorBonenberg, Lukasz Kosma-
dc.date.accessioned2019-07-04T09:04:33Z-
dc.date.available2019-07-04T09:04:33Z-
dc.date.issued2012-11-13-
dc.identifier.citation2012 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2012, Sydney, NSW, Australia, 13 November 2012 through 15 November 2012; Category numberCFP1209J-ARTen_US
dc.identifier.isbn9781467319546-
dc.identifier.urihttps://hdl.handle.net/20.500.14279/14296-
dc.description2012 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2012 - Conference Proceedings 2012, Article number 6418893en_US
dc.description.abstractAn integrated positioning solution termed 'collaborative positioning' employs multiple location sensors with different accuracy on different platforms for sharing of their absolute and relative localizations. Typical application scenarios are dismounted soldiers, swarms of UAV's, team of robots, emergency crews and first responders. The stakeholders of the solution (i.e., mobile sensors, users, fixed stations and external databases) are involved in an iterative algorithm to estimate or improve the accuracy of each node's position based on statistical models. This paper studies the challenges to realize a public and low-cost solution, based on mass users of multiple-sensor platforms. For the investigation field experiments revolved around the concept of collaborative navigation, and partially indoor navigation. For this purpose different sensor platforms have been fitted with similar type of sensors, such as geodetic and low-cost high-sensitivity GNSS receivers, tactical grade IMU's, MEMS-based IMU's, miscellaneous sensors, including magnetometers, barometric pressure and step sensors, as well as image sensors, such as digital cameras and Flash LiDAR, and ultra-wide band (UWB) receivers. The employed platforms in the tests include a train on a building roof, mobile mapping vans, a personal navigator and a foot tracker unit. In terms of the tests, the data from the different platforms are recorded simultaneously. Several field experiments conducted in a week at the University of Nottingham are described and investigated in the paper. The personal navigator and a foot tracker unit moved on the building roof, then trough the building down to where it logged data simultaneously with the vans, all of them moving together and relative to each other. The platforms then logged data simultaneously covering various accelerations, dynamics, etc. over longer trajectories. Promising preliminary results of the field experiments showed that a positioning accuracy on the few meter level can be achieved for the navigation of the different platforms. © 2012 IEEE.en_US
dc.language.isoenen_US
dc.subjectCollaborative navigationen_US
dc.subjectGNSSen_US
dc.subjectINSen_US
dc.subjectMEMS-based sensorsen_US
dc.subjectseamless indoor/outdoor positioningen_US
dc.subjectubiquitous positioningen_US
dc.subjectUWBen_US
dc.titleCollaborative navigation with ground vehicles and personal navigatorsen_US
dc.typeConference Papersen_US
dc.collaborationUniversity of Melbourneen_US
dc.collaborationUniversity of New South Walesen_US
dc.collaborationOhio State Universityen_US
dc.collaborationUniversity of Nottinghamen_US
dc.collaborationNational Technical University Of Athensen_US
dc.collaborationVienna University of Technologyen_US
dc.subject.categoryCivil Engineeringen_US
dc.countryAustraliaen_US
dc.countryUnited Statesen_US
dc.countryUnited Kingdomen_US
dc.countryGreeceen_US
dc.countryChinaen_US
dc.countryAustriaen_US
dc.countryUnited Statesen_US
dc.subject.fieldEngineering and Technologyen_US
dc.publicationPeer Revieweden_US
dc.relation.conferenceInternational Conference on Indoor Positioning and Indoor Navigationen_US
dc.identifier.doi10.1109/IPIN.2012.6418893en_US
dc.identifier.scopus2-s2.0-84874284946-
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/84874284946-
cut.common.academicyear2012-2013en_US
item.fulltextNo Fulltext-
item.cerifentitytypePublications-
item.grantfulltextnone-
item.openairecristypehttp://purl.org/coar/resource_type/c_c94f-
item.openairetypeconferenceObject-
item.languageiso639-1en-
crisitem.author.deptDepartment of Civil Engineering and Geomatics-
crisitem.author.facultyFaculty of Engineering and Technology-
crisitem.author.orcid0000-0002-0248-1085-
crisitem.author.parentorgFaculty of Engineering and Technology-
Appears in Collections:Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation
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