Zero‐Biased Bionic Fingertip E‐Skin with Multimodal Tactile Perception and Artificial Intelligence for Augmented Touch Awareness

Electronic skins (E-Skins) are crucial for future robotics and wearable devices to interact with and perceive the real world. Prior research faces challenges in achieving comprehensive tactile perception and versatile functionality while keeping system simplicity for lack of multimodal sensing capability in a single sensor. Two kinds of tactile sensors, transient voltage artificial neuron (TVAN) and sustained potential artificial neuron (SPAN), featuring self-generated zero-biased signals are developed to realize synergistic sensing of multimodal information (vibration, material, texture, pressure, and temperature) in a single device instead of complex sensor arrays. Simultaneously, machine learning with feature fusion is applied to fully decode their output information and compensate for the inevitable instability of applied force, speed, etc, in real applications. Integrating TVAN and SPAN, the formed E-Skin achieves holistic touch awareness in only a single unit. It can thoroughly perceive an object through a simple touch without strictly controlled testing conditions, realize the capability to discern surface roughness from 0.8 to 1600 µm, hardness from 6HA to 85HD, and correctly distinguish 16 objects with temperature variance from 0 to 80 °C. The E-skin also features a simple and scalable fabrication process, which can be integrated into various devices for broad applications.

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Publication Details

Journal
Advanced Materials
Published
2024-08-11
DOI
https://doi.org/10.1002/adma.202406778
Citations
92
Primary Topic
Advanced Sensor and Energy Harvesting Materials
Type
article
Field-Weighted Citation Impact
16.97

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article

Zero‐Biased Bionic Fingertip E‐Skin with Multimodal Tactile Perception and Artificial Intelligence for Augmented Touch Awareness

Yao Zhu, Zhongda Sun, Xinge Guo, Chengkuo Lee
92 citations
Advanced Materials
Advanced Sensor and Energy Harvesting Materials
16.97
article

Zero‐Biased Bionic Fingertip E‐Skin with Multimodal Tactile Perception and Artificial Intelligence for Augmented Touch Awareness

Yao Zhu, Zhongda Sun, Xinge Guo, Chengkuo Lee
article en
92 citations

Abstract

Electronic skins (E-Skins) are crucial for future robotics and wearable devices to interact with and perceive the real world. Prior research faces challenges in achieving comprehensive tactile perception and versatile functionality while keeping system simplicity for lack of multimodal sensing capability in a single sensor. Two kinds of tactile sensors, transient voltage artificial neuron (TVAN) and sustained potential artificial neuron (SPAN), featuring self-generated zero-biased signals are developed to realize synergistic sensing of multimodal information (vibration, material, texture, pressure, and temperature) in a single device instead of complex sensor arrays. Simultaneously, machine learning with feature fusion is applied to fully decode their output information and compensate for the inevitable instability of applied force, speed, etc, in real applications. Integrating TVAN and SPAN, the formed E-Skin achieves holistic touch awareness in only a single unit. It can thoroughly perceive an object through a simple touch without strictly controlled testing conditions, realize the capability to discern surface roughness from 0.8 to 1600 µm, hardness from 6HA to 85HD, and correctly distinguish 16 objects with temperature variance from 0 to 80 °C. The E-skin also features a simple and scalable fabrication process, which can be integrated into various devices for broad applications.

Advanced MaterialsVol. 36(39)
Agency for Science, Technology and Research (SG), National University of Singapore (SG), Institute of Microelectronics (SG), Suzhou Research Institute (CN)
National Research Foundation Singapore
Openalex Percentile: Top 0%
Advanced Sensor and Energy Harvesting Materials
16.97
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Zero‐Biased Bionic Fingertip E‐Skin with Multimodal Tactile Perception and Artificial Intelligence for Augmented Touch Awareness — Yao Zhu, Zhongda Sun, et al. · Advanced Materials (2024) | TGRS Research Map | TGRS