Vision-Based Autonomous Landing of a Quadrotor on the Perturbed Deck of an Unmanned Surface Vehicle
dc.contributor.author | Polvara, R | |
dc.contributor.author | sharma, sanjay | |
dc.contributor.author | Wan, Jian | |
dc.contributor.author | Manning, Andrew | |
dc.contributor.author | Sutton, R | |
dc.date.accessioned | 2018-04-20T10:59:06Z | |
dc.date.issued | 2018-04-14 | |
dc.identifier.issn | 2504-446X | |
dc.identifier.issn | 2504-446X | |
dc.identifier.other | ARTN 15 | |
dc.identifier.uri | http://hdl.handle.net/10026.1/11309 | |
dc.description.abstract |
<jats:p>Autonomous landing on the deck of an unmanned surface vehicle (USV) is still a major challenge for unmanned aerial vehicles (UAVs). In this paper, a fiducial marker is located on the platform so as to facilitate the task since it is possible to retrieve its six-degrees of freedom relative-pose in an easy way. To compensate interruption in the marker’s observations, an extended Kalman filter (EKF) estimates the current USV’s position with reference to the last known position. Validation experiments have been performed in a simulated environment under various marine conditions. The results confirmed that the EKF provides estimates accurate enough to direct the UAV in proximity of the autonomous vessel such that the marker becomes visible again. Using only the odometry and the inertial measurements for the estimation, this method is found to be applicable even under adverse weather conditions in the absence of the global positioning system.</jats:p> | |
dc.format.extent | 15-15 | |
dc.language | en | |
dc.language.iso | en | |
dc.publisher | MDPI AG | |
dc.subject | unmanned aerial vehicle | |
dc.subject | position control | |
dc.subject | computer vision | |
dc.subject | image processing | |
dc.title | Vision-Based Autonomous Landing of a Quadrotor on the Perturbed Deck of an Unmanned Surface Vehicle | |
dc.type | journal-article | |
dc.type | Journal Article | |
plymouth.author-url | https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000646332800001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=11bb513d99f797142bcfeffcc58ea008 | |
plymouth.issue | 2 | |
plymouth.volume | 2 | |
plymouth.publication-status | Published online | |
plymouth.journal | Drones | |
dc.identifier.doi | 10.3390/drones2020015 | |
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 | |
dcterms.dateAccepted | 2018-04-11 | |
dc.rights.embargodate | 2018-6-15 | |
dc.identifier.eissn | 2504-446X | |
dc.rights.embargoperiod | Not known | |
rioxxterms.versionofrecord | 10.3390/drones2020015 | |
rioxxterms.licenseref.uri | http://www.rioxx.net/licenses/all-rights-reserved | |
rioxxterms.licenseref.startdate | 2018-04-14 | |
rioxxterms.type | Journal Article/Review |