Hand-Arm Motion Prediction for Electrostatic Haptic Presentation on a Planar Display

Abstract

In this study, we propose a rendering method using finger motion prediction to enhance the effectiveness of tactile presentation to a finger using electrostatic adsorption on a flat display. A recursive neural network is used for motion prediction, and the future two-dimensional position of the fingertip touching the display is predicted using the trajectories of the three-dimensional positions of four points on the hand and arm as input. In this paper, we report the results of the electrostatic tactile presentation which compensates the effect of delay by calculating the stimulus based on the hand motion prediction.