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dc.contributor.authorPolvara, R
dc.contributor.authorsharma, sanjay
dc.contributor.authorWan, Jian
dc.contributor.authorManning, Andrew
dc.contributor.authorSutton, R
dc.date.accessioned2019-04-04T11:49:28Z
dc.date.available2019-04-04T11:49:28Z
dc.date.issued2017-09
dc.identifier.isbn9781538610961
dc.identifier.urihttp://hdl.handle.net/10026.1/13635
dc.description.abstract

This paper propose an autonomous landing method for unmanned aerial vehicles (UAVs), aiming to address those situations in which the landing pad is the deck of a ship. Fiducial marker are used to obtain the six-degrees of freedom (DOF) relative-pose of the UAV to the landing pad. In order to compensate interruptions of the video stream, an extended Kalman filter (EKF) is used to estimate the ship's current position with reference to its last known one, just using the odometry and the inertial data. Due to the difficulty of testing the proposed algorithm in the real world, synthetic simulations have been performed on a robotic test-bed comprising the AR Drone 2.0 and the Husky A200. The results show the EKF performs well enough in providing accurate information to direct the UAV in proximity of the other vehicle such that the marker becomes visible again. Due to the use of inertial measurements only in the data fusion process, this solution can be adopted in indoor navigation scenarios, when a global positioning system is not available.

dc.format.extent1-6
dc.language.isoen
dc.publisherIEEE
dc.titleTowards autonomous landing on a moving vessel through fiducial markers
dc.typeconference
dc.typeConference Proceeding
plymouth.author-urlhttps://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000426455100018&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=11bb513d99f797142bcfeffcc58ea008
plymouth.date-start2017-09-06
plymouth.date-finish2017-09-08
plymouth.conference-name2017 European Conference on Mobile Robots (ECMR)
plymouth.publication-statusPublished
plymouth.journal2017 European Conference on Mobile Robots (ECMR)
dc.identifier.doi10.1109/ecmr.2017.8098671
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/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/UoA07 Earth Systems and Environmental Sciences
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
plymouth.organisational-group/Plymouth/Users by role/Researchers in ResearchFish submission
dc.rights.embargoperiodNot known
rioxxterms.versionofrecord10.1109/ecmr.2017.8098671
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserved
rioxxterms.typeConference Paper/Proceeding/Abstract


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