• DocumentCode
    1797705
  • Title

    A sliding parameter estimation method based on UKF for agricultural tracked robot

  • Author

    Jun Jiao ; Li Sun ; Wen Kong ; Youhua Zhang ; Yan Qiao ; Chenchen Yuan

  • Author_Institution
    Coll. of Inf. & Comput., Anhui Agric. Univ., Hefei, China
  • fYear
    2014
  • fDate
    15-17 Nov. 2014
  • Firstpage
    277
  • Lastpage
    282
  • Abstract
    As the sliding parameter of track is hard-to-measure when Agricultural Tracked Robot (ATR) is moving in complicated farmland environment, an estimation method for sliding parameters of ATR based on UKF is proposed. A kinematics equation and a measurement equation of ATR are deduced by kinematics principle, and then the precision position parameters of ATR is calculated. Sliding parameters which cannot be measured directly may be reconstructed through this estimation method. The simulation and experimental results suggest that the estimation system is able to provide reliable and high update rate sliding information, which can provide some theoretical guidance for studying the control accuracy of ATR at a high speed in complicated farmland.
  • Keywords
    Kalman filters; agriculture; mobile robots; nonlinear filters; parameter estimation; UKF; agricultural tracked robot; farmland; kinematics equation; kinematics principle; measurement equation; sliding parameter estimation method; unscented Kalman filters; Educational institutions; Equations; Estimation; Mathematical model; Robots; Tracking; Trajectory; Agricultural Tracked Robot(ATR); Sliding parameter; Unscented Kalman Filter(UKF);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems and Informatics (ICSAI), 2014 2nd International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4799-5457-5
  • Type

    conf

  • DOI
    10.1109/ICSAI.2014.7009299
  • Filename
    7009299