Please use this identifier to cite or link to this item: https://doi.org/10.1126/scirobotics.aax2198
Title: A neuro-inspired artificial peripheral nervous system for scalable electronic skins
Authors: LEE WANG WEI 
TAN YU JUN 
Yao, Haicheng
LI SI 
SEE HIAN HIAN 
Hon, Matthew
NG KIAN ANN 
Xiong, Betty
HO S Y, JOHN 
TEE CHEE KEONG, BENJAMIN 
Keywords: Science & Technology
Technology
Robotics
TACTILE SIGNALS
PRESSURE
SENSORS
DESIGN
Issue Date: 31-Jul-2019
Publisher: American Association for the Advancement of Science
Citation: LEE WANG WEI, TAN YU JUN, Yao, Haicheng, LI SI, SEE HIAN HIAN, Hon, Matthew, NG KIAN ANN, Xiong, Betty, HO S Y, JOHN, TEE CHEE KEONG, BENJAMIN (2019-07-31). A neuro-inspired artificial peripheral nervous system for scalable electronic skins. Science Robotics 4 (32). ScholarBank@NUS Repository. https://doi.org/10.1126/scirobotics.aax2198
Abstract: The human sense of touch is essential for dexterous tool usage, spatial awareness, and social communication. Equipping intelligent human-like androids and prosthetics with electronic skins—a large array of sensors spatially distributed and capable of rapid somatosensory perception—will enable them to work collaboratively and naturally with humans to manipulate objects in unstructured living environments. Previously reported tactile-sensitive electronic skins largely transmit the tactile information from sensors serially, resulting in readout latency bottlenecks and complex wiring as the number of sensors increases. Here, we introduce the Asynchronously Coded Electronic Skin (ACES)—a neuromimetic architecture that enables simultaneous transmission of thermotactile information while maintaining exceptionally low readout latencies, even with array sizes beyond 10,000 sensors. We demonstrate prototype arrays of up to 240 artificial mechanoreceptors that transmitted events asynchronously at a constant latency of 1 ms while maintaining an ultra-high temporal precision of <60 ns, thus resolving fine spatiotemporal features necessary for rapid tactile perception. Our platform requires only a single electrical conductor for signal propagation, realizing sensor arrays that are dynamically reconfigurable and robust to damage. We anticipate that the ACES platform can be integrated with a wide range of skin-like sensors for artificial intelligence (AI)–enhanced autonomous robots, neuroprosthetics, and neuromorphic computing hardware for dexterous object manipulation and somatosensory perception.
Source Title: Science Robotics
URI: https://scholarbank.nus.edu.sg/handle/10635/167831
ISSN: 2470-9476
DOI: 10.1126/scirobotics.aax2198
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