Electronic skin (e-skin) that can learn from experiencing pain could support a new generation of robots with human-like sensitivity, according to research from the University of Glasgow.
A team of engineers developed the artificial skin, which uses a processing system designed to mimic synaptic transistors, capable of imitating the brain’s neural pathways to learn.
A robot hand equipped with the smart skin reportedly showed a “remarkable ability to learn to react to external stimuli”.
In a new paper published in Science Robotics, the researchers describe how they developed their prototype e-skin and how it differs from current touch-sensitive robotics.
To produce an e-skin capable of a synapse-like response, the researchers printed a grid of 168 synaptic transistors made from zinc-oxide nanowires directly onto a flexible plastic surface.
They then connected the synaptic transistor with the skin sensor covering a robot hand.
When the sensor feels pressure, it registers a change in its electrical resistance – a small change corresponds to a light touch, and harder touch creates a larger change in resistance.
The researchers used a voltage spike with a varying output to teach the robot hand to respond to simulated pain.
Using a threshold of input voltage, the team could create a reaction, from which the hand would recoil, meaning it learned to react to onboard information in a process that replicates the human nervous system.
Professor Ravinder Dahiya, of the University of Glasgow’s James Watt School of Engineering, said: “We all learn early on in our lives to respond appropriately to unexpected stimuli like pain in order to prevent us from hurting ourselves again.
“Of course, the development of this new form of electronic skin didn’t really involve inflicting pain as we know it – it’s simply a shorthand way to explain the process of learning from external stimulus.
“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.
“We believe that this is a real step forward in our work towards creating large-scale neuromorphic printed electronic skin capable of responding appropriately to stimuli.”
The research was supported by funding from the Engineering and Physical Sciences Research Council.
