Electronic skin built by British scientists that ‘can feel pain’.

British researchers have developed an electronic skin that can feel “pain”.

They believe it could help create a new generation of intelligent robots with human-like sensibilities and the ability to learn from painful mistakes.

A team of engineers from Glasgow University developed the artificial skin using a novel processing system based on ‘synaptic transistors’, which mimics the brain’s neural pathways to learn.

A robotic hand using the smart skin shows a remarkable ability to learn to respond to external stimuli.

The researchers describe how they built their prototype computational electronic skin (e-skin) and how they improve on the current state of the art in touch-sensitive robotics.

Scientists have been working for decades to build artificial skin that is sensitive to touch.

One widely explored method is to spread an array of contact or pressure sensors across the surface of the electronic skin so it can detect when it makes contact with an object.

Data from the sensors is then sent to a computer for processing and interpretation.

The sensors typically generate a large amount of data that can take time to process and respond properly, resulting in delays that could reduce the skin’s potential effectiveness in real-world tasks.

The Glasgow team’s new form of electronic skin takes inspiration from how the human peripheral nervous system interprets signals from the skin to eliminate latency and power consumption.

Once human skin receives an input, the peripheral nervous system begins to process it at the point of contact, reducing it to just the vital information before sending it to the brain.

This reduction in sensory data allows for efficient use of the communication channels needed to send the data to the brain, which then responds almost immediately to cause the body to respond appropriately.

To build an electronic skin capable of a computationally efficient synapse-like response, the researchers printed a grid of 168 synaptic transistors from zinc oxide nanowires directly onto the surface of a flexible plastic sheet.

They then connected the synaptic transistor to the skin sensor located over the palm of a fully articulated, human-like robotic hand.

When the sensor is touched, it registers a change in its electrical resistance – a small change corresponds to a light touch, a harder touch produces a larger change in resistance.

This input is designed to mimic how sensory neurons work in the human body.

In previous generations of electronic skins, this input data was sent to a computer for processing. Instead, a circuit built into the skin acts as an artificial synapse, reducing the input to a simple voltage spike whose frequency varies with the amount of pressure applied to the skin, speeding up the response process.

The team used the differential output of this voltage spike to teach the skin appropriate responses to simulated pain that would prompt the robotic hand to respond.

By setting a threshold of input voltage to trigger a response, the team was able to make the robotic hand recoil from a sharp jab in the center of its palm.

In other words, it learned to move away from a source of simulated ailments through an onboard information-processing process that mimics how the human nervous system works.

The development of the electronic skin is the latest breakthrough in flexible, stretchable printed surfaces by the University of Glasgow’s Bendable Electronics and Sensing Technologies (BEST) Group, led by Professor Ravinder Dahiya.

Professor Dahiya, of the university’s James Watt School of Engineering, said: “We all learn early in life to respond appropriately to unexpected stimuli, such as pain, in order to avoid injuring ourselves again.

“Of course, the development of this new form of electronic skin wasn’t really about inflicting pain as we know it – it’s just shorthand to explain the process of learning from external stimuli.

“Through this process, we were able to create an electronic skin that enables distributed learning at the hardware level and does not need to send messages back and forth to a central processor before taking action.

“Instead, it greatly speeds up the process of responding to touch by reducing the amount of computation required.

“We believe this is a real advance in our work to create large-scale neuromorphic printed electronic skins capable of appropriately responding to stimuli.”

Fengyuan Liu, member of the BEST group and co-author of the paper, added: “In the future, this research could be the basis for a more advanced electronic skin that will allow robots to explore and interact with the world in new ways, or the construction of prosthetics capable of reaching near-human levels of touch sensitivity.

The team’s paper, entitled “Printed Synaptic Transistors based Electronic Skin for Robots to Feel and Learn,” was published in Science Robotics.

The research was supported by funding from the Engineering and Physical Sciences Research Council (EPSRC).

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