• DocumentCode
    398020
  • Title

    Sensor integration for mobile robot position determination

  • Author

    Azizi, F. ; Houshangi, Nasser

  • Author_Institution
    Dept. of Eng., Purdue Univ. Calumet, Hammond, IN, USA
  • Volume
    2
  • fYear
    2003
  • fDate
    5-8 Oct. 2003
  • Firstpage
    1136
  • Abstract
    The objective of the work presented is to determine an accurate position and orientation for mobile robots based on information received from multiple sensors. The approach taken in this paper is to integrate the information from odometry with the inertial system using Unscented Kalman Filter (UKF). The UKF is the newest extension of widely used estimation method, Kalman Filter. The UKF is more accurate and simpler than the extended Kalman filter applied to nonlinear systems.
  • Keywords
    Kalman filters; distance measurement; inertial systems; mobile robots; nonlinear systems; sensor fusion; UKF; Unscented Kalman Filter; inertial system; mobile robot position determination; multiple sensors; nonlinear systems; odometry; orientation determination; sensor integration; Accelerometers; Gyroscopes; Mobile robots; Nonlinear optics; Nonlinear systems; Optical filters; Optical sensors; Robot sensing systems; Vehicles; Wheels;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man and Cybernetics, 2003. IEEE International Conference on
  • ISSN
    1062-922X
  • Print_ISBN
    0-7803-7952-7
  • Type

    conf

  • DOI
    10.1109/ICSMC.2003.1244564
  • Filename
    1244564