• DocumentCode
    2684670
  • Title

    A Multi-Element generalized Polynomial Chaos approach to analysis of mobile robot dynamics under uncertainty

  • Author

    Kewlani, Gaurav ; Iagnemma, Karl

  • Author_Institution
    Dept. of Mech. Eng., Massachusetts Inst. of Technol., Cambridge, MA, USA
  • fYear
    2009
  • fDate
    10-15 Oct. 2009
  • Firstpage
    1177
  • Lastpage
    1182
  • Abstract
    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.
  • Keywords
    Monte Carlo methods; chaos; mobile robots; motion estimation; parameter estimation; robot dynamics; uncertain systems; MEgPC approach; generalized Askey polynomial chaos framework; mobile robot dynamics; multielement generalized polynomial chaos approach; parameter estimation; robot dynamics estimation; robot motion analysis; standard Monte Carlo scheme; vehicle parameter uncertainty; Chaos; Mobile robots; Motion estimation; Parameter estimation; Polynomials; Robot motion; Safety; Uncertainty; Vehicle dynamics; Vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Robots and Systems, 2009. IROS 2009. IEEE/RSJ International Conference on
  • Conference_Location
    St. Louis, MO
  • Print_ISBN
    978-1-4244-3803-7
  • Electronic_ISBN
    978-1-4244-3804-4
  • Type

    conf

  • DOI
    10.1109/IROS.2009.5354420
  • Filename
    5354420