In the present research, human tactile stochastic resonance (SR) capable of enhancing sensitivity by superimposing proper noise upon undetectable weak signals is utilized to enhance the tactile processing method for social robotics. We develop an experimental apparatus composed of a piezoelectric actuator and its controller, and generate a step several microns high mixed with noise to perform a series of psychophysical experiments. Since psychophysical experiments are conducted based on the Parameter Estimation by Sequential Testing (PEST) method, we produce a PEST program that generates a stimuli sequence based on PEST. The experimental result shows that variation in the difference threshold (Difference Limen; DL) has a local minimum point in the relationship between DL and noise. Therefore, the tactile sensation's just noticeable difference (JND) is decreased by appropriate external noise. Since JND denotes the scale divisions of sensation in the human mind, the present result shows that precise tactile sensations are enhanced by the appropriate external noise. Finally, we introduce a neural network model composed of nonlinear neurons with the bi-stable equilibrium condition to explain this result. Although original sensor data do not represent the morphology of the fine texture, the neural network model Japan extracts the morphology and distinguishes the wave amplitude of the fine texture.

No abstract

Tactile sensors and their data processing are very important in enabling robots to handle objects. With information processing by biological organisms, stochastic resonance (SR) can enhance sensitivity by superimposing proper noise upon undetectable weak signals to detect the target signal. To investigate the SR of human tactile sensation and elucidate the mechanism of tactile SR for the development of a new tactile sensor, we performed a series of psychophysical experiments using tangential vibration with 2.5‐mm and 8‐mm‐sized stimulus points. We examined the difference threshold (difference limen; DL) variation obtained from these experiments to clarify which conditions of vibration direction and stimulus size cause the strongest SR. The experimental results show that neither normal nor tangential DL is significantly affected by stimulus point size. Moreover, tactile sensing precision is enhanced by appropriate noise. The characteristics of SR, with normal vibration obtained from our prior study is quite different from that with tangential vibration

In this paper, we review the influence of external noise on human tactile sensation as outlined in prior and current studies. In the last few decades, researchers have found that, although noise is always considered detrimental, it provides the benefit of stochastic resonance (SR) phenomena. Based on previous studies, we investigate the effect of the SR phenomenon on human tactile sensation. In this context, we developed a system consisting of an experimental apparatus and a computer program, and performed a series of psychophysical experiments using different types of stimulus with normal vibration. The experimental results show that tactile sensation precision can be enhanced by an appropriate level of external noise. Furthermore, we introduce a neural network model composed of nonlinear neurons with a bi-stable equilibrium condition to clarify the result. Finally, we perform a sequence of psychophysical experiments with tangential vibration to clarify which conditions of vibration direction and stimulus size cause the strongest SR. The results show that the normal difference limen (DL) is significantly affected by stimulus point size. On the other hand, neither normal nor tangential DL is significantly affected by stimulus point size. Moreover, the characteristics of SR with normal vibration are quite different from those with tangential vibration.

Abstract-Stochastic Resonance (SR) is