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dc.contributor.advisorTomás Lozano-Pérez.en_US
dc.contributor.authorZhu, Charlotteen_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.en_US
dc.date.accessioned2017-01-12T18:19:12Z
dc.date.available2017-01-12T18:19:12Z
dc.date.copyright2016en_US
dc.date.issued2016en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/106400
dc.descriptionThesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.en_US
dc.descriptionThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.en_US
dc.descriptionCataloged from student-submitted PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 47-48).en_US
dc.description.abstractIn this thesis, we develop a system for estimating a belief state for a scene over multiple observations of the scene. Given as input a sequence of observed RGB-D point clouds of a scene, a list of known objects in the scene and their pose distributions as a prior, and a black-box object detector, our system outputs a belief state of what is believed to be in the scene. This belief state consists of the states of known objects, walls, the floor, and "stuff" in the scene based on the observed point clouds. The system first segments the observed point clouds and then incrementally updates the belief state with each segmented point cloud.en_US
dc.description.statementofresponsibilityby Charlotte Zhu.en_US
dc.format.extent48 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectElectrical Engineering and Computer Science.en_US
dc.titlePoint cloud segmentation for mobile robot manipulationen_US
dc.typeThesisen_US
dc.description.degreeM. Eng.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.identifier.oclc967705113en_US


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