Liu, F. , Deswal, S. , Christou, A., Shojaei Baghini, M. , Chirila, R., Shakthivel, D., Chakraborty, M. and Dahiya, R. (2022) Printed synaptic transistor–based electronic skin for robots to feel and learn. Science Robotics, 7(67), eabl7286. (doi: 10.1126/scirobotics.abl7286) (PMID:35648845)
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Abstract
An electronic skin (e-skin) for the next generation of robots is expected to have biological skin-like multimodal sensing, signal encoding, and preprocessing. To this end, it is imperative to have high-quality, uniformly responding electronic devices distributed over large areas and capable of delivering synaptic behavior with long- and short-term memory. Here, we present an approach to realize synaptic transistors (12-by-14 array) using ZnO nanowires printed on flexible substrate with 100% yield and high uniformity. The presented devices show synaptic behavior under pulse stimuli, exhibiting excitatory (inhibitory) post-synaptic current, spiking rate-dependent plasticity, and short-term to long-term memory transition. The as-realized transistors demonstrate excellent bio-like synaptic behavior and show great potential for in-hardware learning. This is demonstrated through a prototype computational e-skin, comprising event-driven sensors, synaptic transistors, and spiking neurons that bestow biological skin-like haptic sensations to a robotic hand. With associative learning, the presented computational e-skin could gradually acquire a human body–like pain reflex. The learnt behavior could be strengthened through practice. Such a peripheral nervous system–like localized learning could substantially reduce the data latency and decrease the cognitive load on the robotic platform.
| Item Type: | Articles |
|---|---|
| Additional Information: | This work was supported by Engineering and Physical Sciences Research Council (EPSRC) through Engineering Fellowship for Growth - neuPRINTSKIN (EP/R029644/1) and Hetero-print Programme Grant (EP/R03480X/1). |
| Status: | Published |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Deswal, Dr Sweety and Shojaei Baghini, Ms Mahdieh and Shakthivel, Dr Dhayalan and Chirila, Mr Radu-Razvan and Christou, Mr Adamos and Chakraborty, Dr Moupali and Liu, Mr Fengyuan and Dahiya, Professor Ravinder |
| Authors: | Liu, F., Deswal, S., Christou, A., Shojaei Baghini, M., Chirila, R., Shakthivel, D., Chakraborty, M., and Dahiya, R. |
| College/School: | College of Science and Engineering > School of Engineering College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering |
| Journal Name: | Science Robotics |
| Publisher: | American Association for the Advancement of Science |
| ISSN: | 2470-9476 |
| ISSN (Online): | 2470-9476 |
| Published Online: | 01 June 2022 |
| Copyright Holders: | Copyright © 2022 The Authors |
| First Published: | First published in Science Robotics 7(67): eabl7286 |
| Publisher Policy: | Reproduced in accordance with the publisher copyright policy |
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