| Project/Area Number |
22656043
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| Research Category |
Grant-in-Aid for Challenging Exploratory Research
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| Allocation Type | Single-year Grants |
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| Research Field |
Design engineering/Machine functional elements/Tribology
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| Research Institution | Nagoya University |
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Principal Investigator |
OOKA Masahiro 名古屋大学, 情報科学研究科, 教授 (50233044)
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| Co-Investigator(Renkei-kenkyūsha) |
MIYAOKA Tetsu 静岡理工科大学, 理工学部, 教授 (00111815)
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| Project Period (FY) |
2010 – 2011
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| Project Status |
Completed (Fiscal Year 2011)
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| Budget Amount *help |
¥3,450,000 (Direct Cost: ¥3,000,000、Indirect Cost: ¥450,000)
Fiscal Year 2011: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
Fiscal Year 2010: ¥1,500,000 (Direct Cost: ¥1,500,000)
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| Keywords | 複雑系科学 / 触覚 / 確率共鳴 / 心理物理学 / ソフトコンピューティング / 知能機械 / 心理学物理 |
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| Research Abstract |
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 robotics. Psychophysical experiments are conducted based on the Parameter Estimation by Sequential Testing(PEST) method. 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. Based on the abovementioned results, 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 extracts the morphology and distinguishes the wave amplitude of the fine texture.
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