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A Multi-Element Generalized Polynomial Chaos Approach to Analysis of Mobile Robot Dynamics under Uncertainty
MIT, USA.
MIT, USA.
2009 (English)In: IROS 2009: 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, Piscataway, N.J.: IEEE Robotics and Automation Society, 2009, 1177-1182 p.Conference paper, Published paper (Refereed)
Abstract [en]

The ability of mobile robots to quickly and accurately analyze their dynamics is critical to their safety and efficient operation. In field conditions, significant uncertainty is associated with terrain and/or vehicle parameter estimates, and this must be considered in an analysis of robot motion. Here a Multi-Element generalized Polynomial Chaos (MEgPC) approach is presented that explicitly considers vehicle parameter uncertainty for long term estimation of robot dynamics. It is shown to be an improvement over the generalized Askey polynomial chaos framework as well as the standard Monte Carlo scheme, and can be used for efficient, accurate prediction of robot dynamics. © 2009 IEEE.

Place, publisher, year, edition, pages
Piscataway, N.J.: IEEE Robotics and Automation Society, 2009. 1177-1182 p.
Keyword [en]
Accurate prediction, Generalized polynomial chaos, In-field, Long-term estimation, Mobile robot dynamics, Monte carlo schemes, Multi-element, Polynomial chaos, Robot dynamics, Robot motion, Vehicle parameters
National Category
Robotics
Identifiers
URN: urn:nbn:se:hh:diva-20754DOI: 10.1109/IROS.2009.5354420ISI: 000285372900197Scopus ID: 2-s2.0-76249089015OAI: oai:DiVA.org:hh-20754DiVA: diva2:586835
Conference
2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2009, St. Louis, MO, USA, 11-15, 2009
Available from: 2013-01-13 Created: 2013-01-12 Last updated: 2013-01-29Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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  • Other style
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Language
  • de-DE
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Output format
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  • asciidoc
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