4.8 Article

Tactile Avatar: Tactile Sensing System Mimicking Human Tactile Cognition

期刊

ADVANCED SCIENCE
卷 8, 期 7, 页码 -

出版社

WILEY
DOI: 10.1002/advs.202002362

关键词

machine learning; P(VDF‐ TrFE); piezoelectric effect; tactile avatars

资金

  1. Basic Science Research program through the National Research Foundation of Korea (NRF) - MSIT [2019M3C1B8090840, 2020R1A2C1006295]
  2. National Research Foundation of Korea [2019M3C1B8090840, 2020R1A2C1006295] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

向作者/读者索取更多资源

A research proposes an artificial tactile perception and cognition system named as "tactile avatar", which successfully expresses and recognizes users' tactile sensations with personalized deep learning structure, achieving low decision error rates in experiments.
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.

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