Perception-Based Data Reduction for Haptic Force-Feedback Signals Using Velocity-Adaptive Deadbands

Abstract

In telepresence and teleaction (TPTA) systems, the transmission of haptic signals puts high demands on the applied signal processing and communication procedures. When running a TPTA session across a packet-based communication network (e.g., the Internet), minimizing the end-to-end delay results in packet rates of up to the applied sampling rate of the local control loops at the human system interface and the teleoperator. The perceptual deadband data reduction approach for haptic signals successfully addresses the challenge of high packet rates in networked TPTA systems and satisfies the strict delay constraints. In this paper, we extend the underlying perceptual model of the deadband approach by incorporating psychophysical findings on human force-feedback discrimination during operators' relative hand movements. By applying velocity-dependent perception thresholds to the deadband approach, we observe further improvement in efficiency and performance due to improved adaption to human haptic perception thresholds. The psychophysical experiments conducted reveal improved data reduction performance of our proposed haptic perceptual coding scheme without impairing the user experience. Our results show a high data reduction ability of up to 96% without affecting system transparency or the operator's task performance.