Detail View
Tactile Avatar: Tactile Sensing System Mimicking Human Tactile Cognition
- Department of Electrical Engineering and Computer Science
- Advanced Electronic Devices Research Group(AEDRG) - Jang Lab.
- 1. Journal Articles
- Department of Brain Sciences
- Laboratory of Chemical Senses
- 1. Journal Articles
- Department of Electrical Engineering and Computer Science
- CSP(Communication and Signal Processing) Lab
- 1. Journal Articles
WEB OF SCIENCE
SCOPUS
- Title
- Tactile Avatar: Tactile Sensing System Mimicking Human Tactile Cognition
- Issued Date
- 2021-04
- Citation
- Kim, Kyungsoo. (2021-04). Tactile Avatar: Tactile Sensing System Mimicking Human Tactile Cognition. Advanced Science, 8(7), 2002362. doi: 10.1002/advs.202002362
- Type
- Article
- Author Keywords
- machine learning ; P(VDF-TrFE) ; piezoelectric effect ; tactile avatars
- Keywords
- Digital devices ; Topography ; Electronic device ; Learning structure ; Physical information ; Sliding velocities ; Tactile information ; Tactile perception ; Tactile sensation ; Tactile sensing system ; Deep learning
- ISSN
- 2198-3844
- Abstract
-
As a surrogate for human tactile cognition, an artificial tactile perception and cognition system are proposed to produce smooth/soft and rough tactile sensations by its user's tactile feeling; and named this system as “tactile avatar”. A piezoelectric tactile sensor is developed to record dynamically various physical information such as pressure, temperature, hardness, sliding velocity, and surface topography. For artificial tactile cognition, the tactile feeling of humans to various tactile materials ranging from smooth/soft to rough are assessed and found variation among participants. Because tactile responses vary among humans, a deep learning structure is designed to allow personalization through training based on individualized histograms of human tactile cognition and recording physical tactile information. The decision error in each avatar system is less than 2% when 42 materials are used to measure the tactile data with 100 trials for each material under 1.2N of contact force with 4cm s−1 of sliding velocity. As a tactile avatar, the machine categorizes newly experienced materials based on the tactile knowledge obtained from training data. The tactile sensation showed a high correlation with the specific user's tendency. This approach can be applied to electronic devices with tactile emotional exchange capabilities, as well as advanced digital experiences. © 2021 The Authors. Advanced Science published by Wiley-VCH GmbH
더보기
- Publisher
- John Wiley and Sons Inc
File Downloads
공유
Total Views & Downloads
???jsp.display-item.statistics.view???: , ???jsp.display-item.statistics.download???:
