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.
Tactile sensors mimicking the human sense of touch have been studied and various technologies for the sensing of external stimuli have been suggested as well. Humans detect certain external stimuli and become aware of related sensations, such as roughness or smoothness. Among the various physical parameters, surface information is the most informative type of perception to impart these sensations onto an electromechanical system, such as an android robot or a smart phone. Here, an array sensor, which uses a sliding method for the precise perception of surface information, such as shapes and structures, is demonstrated. The suggested array sensor design with the excellent dynamic response of a piezoelectric material results in enhanced spatial resolutions with sliding motions and detects variable sliding speeds. A soft material was employed to the sensor to enhance the capability of shape distinction. Color mapping was applied to translate surface patterns into visual images. The reconfigured surface information had high accuracy compared to actual information. The demonstrated sliding speed, pattern detection, and shape detection capabilities as well as the higher spatial resolutions allow the sensor to be utilized as an artificial tactile sensor.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.