Researchers Create 'E-Skin' Capable of Feeling 'Pain' - Video

CC BY 2.0 / PublicDomainPictures / 17907 / White skin
White skin - Sputnik International, 1920, 02.06.2022
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For decades, scientists have been working to build touch-sensitive robotics with artificial skin. The Glasgow University team’s new form of electronic skin (e-skin) draws inspiration from how the human peripheral nervous system interprets signals from skin in order to eliminate latency and power consumption.
In pursuit of creating a new generation of smart robots with human-like sensitivity, a team of researchers led by an Indian-origin engineer in the UK has created an electronic skin (e-skin) capable of feeling ''pain''.
Professor Ravinder Dahiya from the University of Glasgow's James Watt School of Engineering, told news agency PTI that the discovery marks a real step forward in work towards creating large-scale neuromorphic printed e-skin capable of responding appropriately to stimuli.
His team at the university developed a prototype computational e-skin with a new type of processing system based on synaptic transistors, which mimics the brain’s neural pathways in order to learn.
The researchers published a new paper ‘Printed Synaptic Transistors based Electronic Skin for Robots to Feel and Learn’, in ‘Science Robotics’ journal on Wednesday explaining a robot hand with a smart e-skin showing a remarkable ability to learn to react to external stimuli.
The video posted on the YouTube channel of Bendable Electronics and Sensing Technologies (BEST) shows that as soon as human skin receives an input, the peripheral nervous system begins processing it at the point of contact, reducing it to only the vital information before it is sent to the brain.
To build an e-skin capable of a computationally efficient, synapse-like response, the researchers printed a grid of 168 synaptic transistors made from zinc-oxide nanowires directly onto the surface of a flexible plastic surface.
''What we’ve been able to create through this process is an electronic skin capable of distributed learning at the hardware level, which doesn’t need to send messages back and forth to a central processor before taking action. Instead, it greatly accelerates the process of responding to touch by cutting down the amount of computation required,” Dahiya said.
Fengyuan Liu, a member of the BEST group and a co-author of the paper, said: ''In the future, this research could be the basis for a more advanced electronic skin which enables robots capable of exploring and interacting with the world in new ways, or building prosthetic limbs which are capable of near-human levels of touch sensitivity.''
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