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Stochastic resonance aided tactile sensing

Published online by Cambridge University Press:  01 July 2009

Masahiro Ohka*
Affiliation:
Department of Complex Systems Science, Graduate School of Information Science, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, 464-8601, Japan
Shingo Kondo
Affiliation:
Mitsubishi Electric Corporation, 2-7-3, Marunouchi, Chiyoda-ku, Tokyo, 100-8310, Japan
*
*Corresponding author: E-mail: [email protected]

Summary

Stochastic resonance (SR) is one of the basic principles intrinsically possessed by any living thing to highly adapt to complicated environments including various disturbances. Although a noise is inevitably mixed by contact with an object and a sensor's movement on it in tactile sensing, a human being can evaluate the several micrometers of unevenness on the object surface by means of SR. We intend to apply SR to tactile sensing and to develop a tactile sensing system capable of measuring an object surface with high precision in not only a controlled environment like a precision measurement room but also in a living environment. First, we investigate the SR characteristic possessed by a Hodgkin–Huxley model capable of emulating squid's neuron activities. According to the simulation results, we develop a new electronic circuit capable of generating the SR. We perform the object surface scan using a linear stage equipped with a tactile sensor and the circuit. A series of object surface scanning tests is repeated while changing the intensity of applied noise, and the signal to noise ratio (SNR, hereafter) is calculated from the obtained measurement data to check the effect of the SR. In the experiment, striped textures with a height of δ = 5 ~ 30 μm are used as specimens. The SNR changes depending on the noise intensity, and the local maximum appears under a proper noise. It is found that the sensing accuracy is improved according to the aforementioned SR theory. Therefore, SR, which is usually applied to noisy environments, is effective for a tactile sensing system.

Type
Article
Copyright
Copyright © Cambridge University Press 2008

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