• DocumentCode
    2651429
  • Title

    A hybrid filtering and Maximum Likelihood approach to SLAM

  • Author

    Conte, Francesco ; Martinelli, Agostino

  • Author_Institution
    Dipt. di Ing. Elettr. e dell´´Inf., Univ. degli Studi dell´´Aquila, L´´Aquila, Italy
  • fYear
    2010
  • fDate
    14-18 Dec. 2010
  • Firstpage
    803
  • Lastpage
    809
  • Abstract
    This paper introduces a new approach to SLAM which combines an Information Filter and a non linear optimizer. The basic idea of the suggested technique is to use the Information Filter when the system non linearities are negligible, and to switch to the use of the non linear optimizer when the non linearities are not negligible. Extensive simulations are provided in order to evaluate the performance of the proposed approach. In particular, a comparison with the Exactly Sparse Delayed-state Filers (ESDF) technique is carried out.
  • Keywords
    SLAM (robots); filtering theory; information filters; maximum likelihood estimation; mobile robots; SLAM; exactly sparse delayed-state filers technique; filtering approach; information filter; maximum likelihood approach; nonlinear optimizer; Cost function; Estimation; Information filters; Linearity; Robot kinematics; Simultaneous localization and mapping;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Robotics and Biomimetics (ROBIO), 2010 IEEE International Conference on
  • Conference_Location
    Tianjin
  • Print_ISBN
    978-1-4244-9319-7
  • Type

    conf

  • DOI
    10.1109/ROBIO.2010.5723429
  • Filename
    5723429