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dc.contributor.authorChoudhary, Siddharth
dc.contributor.authorTrevor, Alexander J. B.
dc.contributor.authorChristensen, Henrik I.
dc.contributor.authorDellaert, Frank
dc.date.accessioned2015-08-12T19:38:06Z
dc.date.available2015-08-12T19:38:06Z
dc.date.issued2014-09
dc.identifier.citationChoudhary, 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.urihttp://hdl.handle.net/1853/53723
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.descriptionDOI: 10.1109/IROS.2014.6942683
dc.description.abstractObject 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.language.isoen_USen_US
dc.publisherGeorgia Institute of Technologyen_US
dc.subjectLoop closure detectionen_US
dc.subjectObject discoveryen_US
dc.subjectObject modelingen_US
dc.subjectRoboticsen_US
dc.subjectSimultaneous localization and mappingen_US
dc.subjectSLAMen_US
dc.titleSLAM with Object Discovery, Modeling and Mappingen_US
dc.typeProceedingsen_US
dc.contributor.corporatenameGeorgia Institute of Technology. Institute for Robotics and Intelligent Machinesen_US
dc.contributor.corporatenameGeorgia Institute of Technology. College of Computingen_US
dc.contributor.corporatenameGeorgia Institute of Technology. School of Interactive Computingen_US
dc.publisher.originalInstitute of Electrical and Electronics Engineers
dc.identifier.doi10.1109/IROS.2014.6942683
dc.embargo.termsnullen_US


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