• DocumentCode
    582434
  • Title

    Cubature MCL: Mobile robot Monte Carlo Localization based on Cubature Particle Filter

  • Author

    Li Qingling ; Song Yu

  • Author_Institution
    Sch. of Mech. Electron. & Inf. Eng., China Univ. of Min. & Technol., Beijing, China
  • fYear
    2012
  • fDate
    25-27 July 2012
  • Firstpage
    5141
  • Lastpage
    5145
  • Abstract
    Particle Filter is the key issue in mobile robot MCL (Monte Carlo Loclaization, MCL). To overcome particle set degeneracy phenomenon of the traditional MCL algorithm, a new Cubature MCL algorithm is proposed in this paper. The proposed Cubature MCL algorithm utilizes Cubature Kalman filter to generate more accuracy proposal distribution, which introduce most recent measurements into Sequential Importance Sampling (SIS) routine of the particle filter. The performance of the Cubature MCL algorithm is presented and analyzed in simulations. The results verify the effectiveness of the proposed Cubature MCL algorithm. The Cubature MCL provides a valuable reference for the mobile robot localization algorithm research.
  • Keywords
    Kalman filters; importance sampling; mobile robots; particle filtering (numerical methods); Cubature Kalman filter; Cubature MCL algorithm; Cubature particle filter; SIS; mobile robot MCL; mobile robot Monte Carlo localization; particle set degeneracy phenomenon; sequential importance sampling routine; Educational institutions; Electronic mail; Mobile robots; Monte Carlo methods; Particle filters; Robustness; Cubature rule; Gaussian weighted integral; Mobile robot; Monte Carlo localization; Particle filter;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Conference (CCC), 2012 31st Chinese
  • Conference_Location
    Hefei
  • ISSN
    1934-1768
  • Print_ISBN
    978-1-4673-2581-3
  • Type

    conf

  • Filename
    6390833