• DocumentCode
    3290625
  • Title

    A non-inertial acceleration suppressor for low cost inertial measurement unit attitude estimation

  • Author

    Valenti, Roberto G. ; Dryanovski, Ivan ; Jizhong Xiao

  • Author_Institution
    Electr. Eng. Dept., City Coll. of New York, New York, NY, USA
  • fYear
    2013
  • fDate
    12-14 Dec. 2013
  • Firstpage
    639
  • Lastpage
    644
  • Abstract
    This paper presents a method to evaluate the attitude of a rigid body under condition of high non-gravitational acceleration. Most of the attitude estimation algorithms based on data from low cost Inertial Measurement Units (IMU), assume that the total acceleration perceived by the accelerometer be gravity or at most small variations of it. When the actual conditions are far away from such assumption, the attitude estimation results in wrong evaluations. We propose a method that uses an external RGB-D camera to measure The non-inertial linear acceleration. Such acceleration is subtracted to the total acceleration reading of the accelerometer in order to obtain a truthful gravity direction that will be fed into the fusion algorithm. Performance of our attitude estimation has been evaluated empirically under non-gravitational acceleration. We compare our results against the output of a commercially avalaible IMU sensor based on a Kalman Filter algorithm as well as the estimation of a recently developed fusion algorithm based on a gradient descent algorithm, showing significant improvement.
  • Keywords
    Kalman filters; accelerometers; attitude measurement; inertial navigation; units (measurement); Kalman filter algorithm; external RGB-D camera; fusion algorithm; high nongravitational acceleration; low cost inertial measurement unit attitude estimation; noninertial acceleration suppressor; rigid body; Acceleration; Accelerometers; Cameras; Estimation; Gravity; Noise; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Robotics and Biomimetics (ROBIO), 2013 IEEE International Conference on
  • Conference_Location
    Shenzhen
  • Type

    conf

  • DOI
    10.1109/ROBIO.2013.6739531
  • Filename
    6739531