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dc.contributor.authorKök, M.en_US
dc.contributor.authorBarshan, B.en_US
dc.date.accessioned2016-02-08T11:37:04Z
dc.date.available2016-02-08T11:37:04Z
dc.date.issued2008en_US
dc.identifier.urihttp://hdl.handle.net/11693/26829
dc.description.abstractIn this work, a 2D vision-based Simultaneous Localization and Mapping algorithm is developed for an Unmanned Aerial Vehicle flying at a constant altitude. We use visual features of images obtained from an on-board camera to identify different landmarks. Using these landmarks we apply the well-known Extended Kalman Filter to the SLAM problem and present some simulation results. ©2008 IEEE.en_US
dc.language.isoTurkishen_US
dc.source.title2008 IEEE 16th Signal Processing, Communication and Applications Conference, SIUen_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/SIU.2008.4632709en_US
dc.subject2d visionsen_US
dc.subjectConstant altitudesen_US
dc.subjectSimulation resultsen_US
dc.subjectSimultaneous localization and mapping algorithmsen_US
dc.subjectSimultaneous Localization And mappingsen_US
dc.subjectSLAM problemsen_US
dc.subjectUnmanned aerial vehicle]en_US
dc.subjectVisual featuresen_US
dc.subjectCellular radio systemsen_US
dc.subjectConformal mappingen_US
dc.subjectControl theoryen_US
dc.subjectMilitary applicationsen_US
dc.subjectSignal processingen_US
dc.subjectUnmanned aerial vehicles (UAV)en_US
dc.subjectUnmanned vehiclesen_US
dc.title2D simultaneous localization and mapping for unmanned aerial vehiclesen_US
dc.title.alternativeİnsansiz hava araçlari için eşanli konumlandirma ve haritalamaen_US
dc.typeConference Paperen_US
dc.departmentDepartment of Electrical and Electronics Engineering
dc.identifier.doi10.1109/SIU.2008.4632709en_US


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