| Budget Amount *help |
¥4,680,000 (Direct Cost: ¥3,600,000、Indirect Cost: ¥1,080,000)
Fiscal Year 2019: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2018: ¥2,470,000 (Direct Cost: ¥1,900,000、Indirect Cost: ¥570,000)
Fiscal Year 2017: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
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| Outline of Final Research Achievements |
This work proposed a new food texture estimation method by using a robot system. By imitating human's oral mechanism, a robotic mastication simulator was developed. Biting and tongue pressure distribution measured during mastication was processed as a series of image frames. Using a convolutional neural network, the value of human sensory evaluation of texture was estimated. Through experimental validation, it was shown that the proposed method has a potential ability of estimating texture with higher accuracy than that of human.
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