Printed synaptic transistor–based electronic skin for robots to feel and learn

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 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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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
301728Engineering Fellowships for Growth: Printed Tactile SKINRavinder DahiyaEngineering and Physical Sciences Research Council (EPSRC)EP/R029644/1ENG - Electronics & Nanoscale Engineering
301327`Hetero-print: A holistic approach to transfer-printing for heterogeneous integration in manufacturingPeter SkabaraEngineering and Physical Sciences Research Council (EPSRC)EP/R03480X/1ENG - Electronics & Nanoscale Engineering