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dc.contributor.authorCunningham, Alexander
dc.contributor.authorIndelman, Vadim
dc.contributor.authorDellaert, Frank
dc.date.accessioned2013-08-23T17:46:01Z
dc.date.available2013-08-23T17:46:01Z
dc.date.issued2013-05
dc.identifier.citationCunningham, A.; Indelman, V.; & Dellaert, F. (2013). "DDF-SAM 2.0: Consistent Distributed Smoothing and Mapping". IEEE International Conference on Robotics and Automation (ICRA 2013), 6-10 May 2013.en_US
dc.identifier.urihttp://hdl.handle.net/1853/48724
dc.description©2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, 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 component of this work in other works.en_US
dc.descriptionPresented at the IEEE International Conference on Robotics and Automation (ICRA 2013), 6-10 May 2013, Karlsruhe, Germany.
dc.description.abstractThis paper presents an consistent decentralized data fusion approach for robust multi-robot SLAM in dan- gerous, unknown environments. The DDF-SAM 2.0 approach extends our previous work by combining local and neigh- borhood information in a single, consistent augmented local map, without the overly conservative approach to avoiding information double-counting in the previous DDF-SAM algo- rithm. We introduce the anti-factor as a means to subtract information in graphical SLAM systems, and illustrate its use to both replace information in an incremental solver and to cancel out neighborhood information from shared summarized maps. This paper presents and compares three summarization techniques, with two exact approaches and an approximation. We evaluated the proposed system in a synthetic example and show the augmented local system and the associated summarization technique do not double-count information, while keeping performance tractable.en_US
dc.language.isoen_USen_US
dc.publisherGeorgia Institute of Technologyen_US
dc.subjectDistributed robot systemsen_US
dc.subjectNetworked robotsen_US
dc.subjectSLAMen_US
dc.titleDDF-SAM 2.0: Consistent Distributed Smoothing and Mappingen_US
dc.typePost-print
dc.typeProceedings
dc.contributor.corporatenameGeorgia Institute of Technology. College of Computingen_US
dc.contributor.corporatenameGeorgia Institute of Technology. School of Interactive Computingen_US
dc.contributor.corporatenameGeorgia Institute of Technology. Center for Robotics and Intelligent Machinesen_US
dc.publisher.originalInstitute of Electrical and Electronics Engineers
dc.embargo.termsnullen_US


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