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dc.contributor.advisorSaranlı, Uluç
dc.contributor.authorÖzaslan, Tolga
dc.date.accessioned2016-01-08T18:15:37Z
dc.date.available2016-01-08T18:15:37Z
dc.date.issued2011
dc.identifier.urihttp://hdl.handle.net/11693/15251
dc.descriptionAnkara : The Department of Computer Engineering and the Graduate School of Engineering and Science of Bilkent University, 2011.en_US
dc.descriptionThesis (Master's) -- Bilkent University, 2011.en_US
dc.descriptionIncludes bibliographical references leaves 77-81.en_US
dc.description.abstractSimultaneous Localization and Mapping (SLAM) for mobile robots has been one of the challenging problems for the robotics community. Extensive study of this problem in recent years has somewhat saturated the theoretical and practical background on this topic. Within last few years, researches on SLAM have been headed towards Visual SLAM, in which camera is used as the primary sensor. Superior to many SLAM application run with planar robots, VSLAM allows us to estimate the 3D model of the environment and 6-DOF pose of the robot. Being applied to robotics only recently, VSLAM still has a lot of room for improvement. In particular, a common issue both in normal and Visual SLAM algorithms is the data association problem. Wrong data association either disturbs stability or result in divergence of the SLAM process. In this study, we propose two outlier elimination methods which use predicted feature location error and optical flow field. The former method asserts estimated landmark projection and its measurement locations to be close. The latter accepts optical flow field as a reference and compares the vector formed by consecutive matched feature locations; eliminates matches contradicting with the local optical flow vector field. We have shown these two methods to be saving VSLAM from divergence and improving its overall performance. We have also described our new modular SLAM library, SLAM++.en_US
dc.description.statementofresponsibilityÖzaslan, Tolgaen_US
dc.format.extentxiv, 81 leaves, illustrations, graphicsen_US
dc.language.isoEnglishen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectVisual Simultaneous Localization and Mapping (SLAM)en_US
dc.subjectOptical flowen_US
dc.subjectOutlier eliminationen_US
dc.subject.lccTJ211.415 .O93 2011en_US
dc.subject.lcshMobile robots.en_US
dc.subject.lcshSLAM (Computer program language)en_US
dc.subject.lcshDigital computer simulation.en_US
dc.subject.lcshRobots--Control systems.en_US
dc.subject.lcshLocalization theory.en_US
dc.subject.lcshMappings (Mathematics)en_US
dc.subject.lcshRobot vision.en_US
dc.titleImproving visual SLAM by filtering outliers with the aid of optical flowen_US
dc.typeThesisen_US
dc.departmentDepartment of Computer Engineeringen_US
dc.publisherBilkent Universityen_US
dc.description.degreeM.S.en_US
dc.identifier.itemidB123607


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