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dc.contributor.authorLatif, Yasir
dc.contributor.authorHuang, Guoquan
dc.contributor.authorLeonard, John Joseph
dc.contributor.authorNeira, José
dc.date.accessioned2020-04-06T13:43:54Z
dc.date.available2020-04-06T13:43:54Z
dc.date.issued2017-04
dc.date.submitted2017-01
dc.identifier.issn0921-8890
dc.identifier.urihttps://hdl.handle.net/1721.1/124489
dc.description.abstractIt is essential for a robot to be able to detect revisits or loop closures for long-term visual navigation. A key insight explored in this work is that the loop-closing event inherently occurs sparsely, i.e., the image currently being taken matches with only a small subset (if any) of previous images. Based on this observation, we formulate the problem of loop-closure detection as a sparse, convexℓ1-minimization problem. By leveraging fast convex optimization techniques, we are able to efficiently find loop closures, thus enabling real-time robot navigation. This novel formulation requires no offline dictionary learning, as required by most existing approaches, and thus allows online incremental operation. Our approach ensures a unique hypothesis by choosing only a single globally optimal match when making a loop-closure decision. Furthermore, the proposed formulation enjoys a flexible representation with no restriction imposed on how images should be represented, while requiring only that the representations are “close” to each other when the corresponding images are visually similar. The proposed algorithm is validated extensively using real-world datasets. Keywords: SLAM; Place recognition; Relocalization; Sparse optimizationen_US
dc.description.sponsorshipMINECO-FEDER project (DPI2015-68905-P)en_US
dc.description.sponsorshipNSF (IIS-1318392)en_US
dc.description.sponsorshipNSF (IIS-15661293)en_US
dc.description.sponsorshipDTRA award HDTRA (1-16-1-0039)en_US
dc.language.isoen
dc.publisherElsevier BVen_US
dc.relation.isversionofhttp://dx.doi.org/10.1016/j.robot.2017.03.016en_US
dc.rightsCreative Commons Attribution-NonCommercial-NoDerivs Licenseen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/en_US
dc.sourcearXiven_US
dc.titleSparse optimization for robust and efficient loop closingen_US
dc.typeArticleen_US
dc.identifier.citationLatif, Yasir et al. "Sparse optimization for robust and efficient loop closing." Robotics and Autonomous Systems 93 (July 2017): 13-26 © 2017 Elsevier B.V.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.relation.journalRobotics and Autonomous Systemsen_US
dc.eprint.versionOriginal manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2019-09-23T11:22:44Z
dspace.date.submission2019-09-23T11:23:21Z
mit.journal.volume93en_US


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