• DocumentCode
    41543
  • Title

    Real-Time Estimate of Velocity and Acceleration of Quasi-Periodic Signals Using Adaptive Oscillators

  • Author

    Ronsse, Renaud ; De Rossi, Stefano M.M. ; Vitiello, Nicola ; Lenzi, T. ; Carrozza, Maria ; Ijspeert, Auke J.

  • Author_Institution
    Center for Res. in Mechatron., Univ. Catholique de Louvain, Louvain-la-Neuve, Belgium
  • Volume
    29
  • Issue
    3
  • fYear
    2013
  • fDate
    Jun-13
  • Firstpage
    783
  • Lastpage
    791
  • Abstract
    Estimation of the temporal derivatives of a noisy position signal is a ubiquitous problem in industrial and robotics engineering. Here, we propose a new approach to get velocity and acceleration estimates of cyclical/periodic signals near to steady-state regime, by using adaptive oscillators. Our method combines the advantages of introducing no delay, and filtering out the high-frequency noise. We expect this method to be useful in control applications requiring undelayed but smooth estimates of velocity and acceleration (e.g., velocity control and inverse dynamics) of quasi-periodic tasks (e.g., active vibration compensation, robot locomotion, and lower-limb movement assistance).
  • Keywords
    adaptive signal processing; filtering theory; oscillators; real-time systems; adaptive oscillators; high-frequency noise; industrial engineering; noisy position signal; periodic signals; quasiperiodic signals; quasiperiodic tasks; real-time acceleration estimation; real-time velocity estimation; robotics engineering; steady-state regime; temporal derivatives; ubiquitous problem; Acceleration; Benchmark testing; Interpolation; Kalman filters; Oscillators; Polynomials; Robots; Calibration and identification; filtering; kinematics; learning and adaptive systems; oscillator;
  • fLanguage
    English
  • Journal_Title
    Robotics, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1552-3098
  • Type

    jour

  • DOI
    10.1109/TRO.2013.2240173
  • Filename
    6428719