• DocumentCode
    31246
  • Title

    UKF for Integrated Vision and Inertial Sensors Based on Three-View Geometry

  • Author

    Fang, Qing ; Huang, Sheng Xin

  • Author_Institution
    Mobile Robot Navigation and Vision Based Techniques, National University of Defense Technology, Changsha, China
  • Volume
    13
  • Issue
    7
  • fYear
    2013
  • fDate
    Jul-13
  • Firstpage
    2711
  • Lastpage
    2719
  • Abstract
    An unscented Kalman filter (UKF) is derived for integrating vision with inertial measurements from gyros and accelerometers sensors based on three-view geometry. The main goal of the proposed method is to provide better estimations compared to the implicit extended Kalman filter introduced by Indelman . The UKF uses a selected set of points to more accurately map the probability distribution of the measurement model than the linearization of the extended Kalman filter, leading to faster convergence from inaccurate initial conditions in estimation problems. The proposed method is validated using a statistical study based on simulated navigation and synthetic images data.
  • Keywords
    Unscented Kalman filter (UKF); implicit extended Kalman filter (IEKF); sensors; three-view geometry; vision;
  • fLanguage
    English
  • Journal_Title
    Sensors Journal, IEEE
  • Publisher
    ieee
  • ISSN
    1530-437X
  • Type

    jour

  • DOI
    10.1109/JSEN.2013.2259228
  • Filename
    6506954