SLAM with Object Discovery, Modeling and Mapping

dc.contributor.author Choudhary, Siddharth
dc.contributor.author Trevor, Alexander J. B.
dc.contributor.author Christensen, Henrik I.
dc.contributor.author Dellaert, Frank
dc.contributor.corporatename Georgia Institute of Technology. Institute for Robotics and Intelligent Machines en_US
dc.contributor.corporatename Georgia Institute of Technology. College of Computing en_US
dc.contributor.corporatename Georgia Institute of Technology. School of Interactive Computing en_US
dc.date.accessioned 2015-08-12T19:38:06Z
dc.date.available 2015-08-12T19:38:06Z
dc.date.issued 2014-09
dc.description © 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. en_US
dc.description DOI: 10.1109/IROS.2014.6942683
dc.description.abstract Object discovery and modeling have been widely studied in the computer vision and robotics communities. SLAM approaches that make use of objects and higher level features have also recently been proposed. Using higher level features provides several benefits: these can be more discriminative, which helps data association, and can serve to inform service robotic tasks that require higher level information, such as object models and poses. We propose an approach for online object discovery and object modeling, and extend a SLAM system to utilize these discovered and modeled objects as landmarks to help localize the robot in an online manner. Such landmarks are particularly useful for detecting loop closures in larger maps. In addition to the map, our system outputs a database of detected object models for use in future SLAM or service robotic tasks. Experimental results are presented to demonstrate the approach’s ability to detect and model objects, as well as to improve SLAM results by detecting loop closures. en_US
dc.embargo.terms null en_US
dc.identifier.citation Choudhary, S.; Trevor, A.J.B.; Christensen, H.I.; & Dellaert, F. (2014). "SLAM With Object Discovery, Modeling and Mapping". IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2014), 14-18 September 2014, pp. 1018-1025. en_US
dc.identifier.doi 10.1109/IROS.2014.6942683
dc.identifier.uri http://hdl.handle.net/1853/53723
dc.language.iso en_US en_US
dc.publisher Georgia Institute of Technology en_US
dc.publisher.original Institute of Electrical and Electronics Engineers
dc.subject Loop closure detection en_US
dc.subject Object discovery en_US
dc.subject Object modeling en_US
dc.subject Robotics en_US
dc.subject Simultaneous localization and mapping en_US
dc.subject SLAM en_US
dc.title SLAM with Object Discovery, Modeling and Mapping en_US
dc.type Text
dc.type.genre Proceedings
dspace.entity.type Publication
local.contributor.author Christensen, Henrik I.
local.contributor.author Dellaert, Frank
local.contributor.corporatename Institute for Robotics and Intelligent Machines (IRIM)
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relation.isAuthorOfPublication dac80074-d9d8-4358-b6eb-397d95bdc868
relation.isOrgUnitOfPublication 66259949-abfd-45c2-9dcc-5a6f2c013bcf
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