Methods For Simultaneous Self-Localization And Mapping For Depth Cameras

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but.event.date27.04.2017cs
but.event.titleStudent EEICT 2017cs
dc.contributor.authorLigocki, Adam
dc.date.accessioned2020-05-07T09:40:27Z
dc.date.available2020-05-07T09:40:27Z
dc.date.issued2017cs
dc.description.abstractThis work deals with the extension of the existing implementation of RGBD Visual SLAM with additional data source from wheel odometry of robot’s chassis, on which RGBD sensor is located. Each of these two position estimation methods has a different character measurement uncertainty. By combining these methods together we could be able to suppress the disadvantages of both approaches, and in the result we would be able to create more accurate model of the robot’s environment, which was unknown at the beginning of the measurement. Also accuracy of position estimation in created model can be improved.en
dc.formattextcs
dc.format.extent193-195cs
dc.format.mimetypeapplication/pdfen
dc.identifier.citationProceedings of the 23st Conference STUDENT EEICT 2017. s. 193-195. ISBN 978-80-214-5496-5cs
dc.identifier.isbn978-80-214-5496-5
dc.identifier.urihttp://hdl.handle.net/11012/187079
dc.language.isoencs
dc.publisherVysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologiícs
dc.relation.ispartofProceedings of the 23st Conference STUDENT EEICT 2017en
dc.relation.urihttp://www.feec.vutbr.cz/EEICT/cs
dc.rights© Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologiícs
dc.rights.accessopenAccessen
dc.subjectSLAMen
dc.subjectVisual SLAMen
dc.subjectOdometryen
dc.subjectKinecten
dc.subject3D Modeen
dc.subjectPosition Estimationen
dc.titleMethods For Simultaneous Self-Localization And Mapping For Depth Camerasen
dc.type.driverconferenceObjecten
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
eprints.affiliatedInstitution.departmentFakulta elektrotechniky a komunikačních technologiícs
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