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Spectral Subtraction of Robot Motion Noise for Improved Event Detection in Tactile Acceleration Signals
Departmental Papers (MEAM)
  • Katherine J Kuchenbecker, University of Pennsylvania
  • William McMahan, University of Pennsylvania
Document Type
Conference Paper
Date of this Version
6-1-2012
Comments

W. McMahan and K. J. Kuchenbecker. Spectral Subtraction of Robot Motion Noise for Improved Event Detection in Tactile Acceleration Signals. In Proceedings, EuroHaptics, pages 326-337, June 2012. doi: 10.1007/978-3-642-31401-8_30

The final publication is available at www.springerlink.com

Abstract

New robots for teleoperation and autonomous manipulation are increasingly being equipped with high-bandwidth accelerometers for measuring the transient vibrational cues that occur during con- tact with objects. Unfortunately, the robot's own internal mechanisms often generate significant high-frequency accelerations, which we term ego-vibrations. This paper presents an approach to characterizing and removing these signals from acceleration measurements. We adapt the audio processing technique of spectral subtraction over short time windows to remove the noise that is estimated to occur at the robot's present joint velocities. Implementation for the wrist roll and gripper joints on a Willow Garage PR2 robot demonstrates that spectral subtraction significantly increases signal-to-noise ratio, which should improve vibrotactile event detection in both teleoperation and autonomous robotics.

Keywords
  • haptic feedback for teleoperation,
  • vibrations,
  • tactile accelerations,
  • noise suppression
Citation Information
Katherine J Kuchenbecker and William McMahan. "Spectral Subtraction of Robot Motion Noise for Improved Event Detection in Tactile Acceleration Signals" (2012)
Available at: http://works.bepress.com/william_mcmahan/7/