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dc.contributor.authorKlečka, Jan
dc.date.accessioned2019-03-04T10:05:52Z
dc.date.available2019-03-04T10:05:52Z
dc.date.issued2018cs
dc.identifier.citationProceedings of the 24th Conference STUDENT EEICT 2018. s. 358-362. ISBN 978-80-214-5614-3cs
dc.identifier.isbn978-80-214-5614-3
dc.identifier.urihttp://hdl.handle.net/11012/138256
dc.description.abstractThis paper is aimed at utilizing of an Unscented Kalman filter (UKF) for application on non-odometry SLAM problem. Non-odometry SLAM problem lacks state transitions function for part of state vector so theoretical part of the paper describes the derivation of three proposed modifications. The experimental part then shows experiments which evaluate modifications performance in reference to Extended Kalman filter. Experiments are based on simulation of monocular photogrammetry reconstruction problem.en
dc.formattextcs
dc.format.extent358-362cs
dc.format.mimetypeapplication/pdfen
dc.language.isoencs
dc.publisherVysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologiícs
dc.relation.ispartofProceedings of the 24th Conference STUDENT EEICT 2018en
dc.relation.urihttp://www.feec.vutbr.cz/EEICT/cs
dc.rights© Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologiícs
dc.subjectUnscented Kalman filteren
dc.subjectUKFen
dc.subjectSLAMen
dc.subjectRecurrent estimationen
dc.titleComparison Of Different Approaches To Adaptation Of Unscented Kalman Filter For Non-Odometry Slamen
eprints.affiliatedInstitution.departmentFakulta elektrotechniky a komunikačních technologiícs
but.event.date26.04.2018cs
but.event.titleStudent EEICT 2018cs
dc.rights.accessopenAccessen
dc.type.driverconferenceObjecten
dc.type.statusPeer-revieweden
dc.type.versionPublishers's versionen


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