• DocumentCode
    2603783
  • Title

    A simulation study of sensor data fusion using UKF for bucket wheel reclaimer localization

  • Author

    Zhao, Shi ; Lu, Tien-Fu ; Koch, Ben ; Hurdsman, Alan

  • Author_Institution
    Sch. of Mech. Eng., Univ. of Adelaide, Adelaide, SA, Australia
  • fYear
    2012
  • fDate
    20-24 Aug. 2012
  • Firstpage
    1192
  • Lastpage
    1197
  • Abstract
    Bucket Wheel Reclaimers (BWRs) normally travel on a rail among stockpiles to perform stacking and reclaiming operations. Currently, the position accuracy of the bucket wheel at the end of boom measured by the onboard encoder system is limited to 30cm. To maintain such accuracy, calibrated points have to be placed along the rail, which is inefficient and costly. This paper proposes a simulation study using Unscented Kalman Filter (UKF) algorithm to fuse DGPS and encoder data for BWR localization. The results obtained indicate that the errors in positional accuracy are better than 15cm and UKF is an objective technology that can be applied to localize such large scaled machine.
  • Keywords
    Kalman filters; conveyors; position control; sensor fusion; BWR localization; DGPS; UKF algorithm; bucket wheel reclaimer localization; onboard encoder system; position accuracy; reclaiming operation; sensor data fusion; stacking operation; unscented Kalman filter; Australia; Global Positioning System; Marine vehicles; Measurement uncertainty; Noise; Resistance; Silicon compounds;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Automation Science and Engineering (CASE), 2012 IEEE International Conference on
  • Conference_Location
    Seoul
  • ISSN
    2161-8070
  • Print_ISBN
    978-1-4673-0429-0
  • Type

    conf

  • DOI
    10.1109/CoASE.2012.6386509
  • Filename
    6386509