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Abstract
This paper demonstrates an artificial tactile sensor system mimicking the human somatosensory system. The system uses a semivolatile carbon nanotube transistor to function as both sensory neurons and a perceptual synaptic network. It can differentiate temporal features of tactile patterns, and its accuracy improves through iterative learning. A circuit model provides quantitative analysis and feasibility for product development, suggesting potential applications in robotics and prosthetics.
Publisher
NPG Asia Materials
Published On
Authors
Sungho Kim, Yongwoo Lee, Hee-Dong Kim, Sung-Jin Choi
Tags
artificial tactile sensor
somatosensory system
carbon nanotube transistor
tactile patterns
robotics
prosthetics
iterative learning
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