In a riveting invention, a team of researchers led by an Indian-origin engineer in the U.K has created an electronic skin capable of feeling “pain”. According to the researcher, this invention will pave the way to create a new generation of smart robots with human-like sensitivity.
Elaborating on it, professor Ravinder Dahiya, from the University of Glasgow’s James Watt School of Engineering, said the discovery marks a real step forward in work towards creating large-scale neuromorphic printed e-skin capable of responding appropriately to stimuli.
The team led by him at the university invented the artificial skin using a new type of processing system based on synaptic transistors. This process mimics the brain’s neural pathways in order to learn. A robot hand which uses the smart skin is said to show a remarkable ability to learn to react to external stimuli.
“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,” explained Mr Dahiya.
“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,” he added.
In a new paper published on Wednesday named ‘Printed Synaptic Transistors based Electronic Skin for Robots to Feel and Learn’, in the journal ‘Science Robotics’, the Scottish university researchers describe how they built their prototype computational e-skin. They also explain how it improves on the current state of the art in touch-sensitive robotics.
In the area of flexible, stretchable printed surfaces from the University of Glasgow’s Bendable Electronics and Sensing Technologies (BEST) Group, the development of the electronic skin is described as the latest breakthrough.
A member of the BEST group, Fengyuan Liu, who was the co-author of the paper, added: “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.”
The development is considered a result of decades-long perseverance by scientists to build artificial skin with touch sensitivity. A tried process is spreading an array of contact or pressure sensors across the electronic skin’s surface to allow it to detect when it comes into contact with an object.
Data from the sensors is then sent to a computer to be processed and interpreted. The sensors typically produce a large volume of data which can take time to be properly processed and responded to, introducing delays which could reduce the skin’s potential effectiveness in real-world tasks.
The Glasgow University team’s development of electronic skin takes lessons from the human peripheral nervous system and how it interprets signals from the skin in order to eliminate latency and power consumption.
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. That reduction of sensory data allows efficient use of communication channels needed to send the data to the brain, which then responds almost immediately for the body to react appropriately.
To build an electronic 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. Then, they connected the synaptic transistor with the skin sensor present over the palm of a fully-articulated, human-shaped robot hand.
When the sensor is touched, 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. This input is designed to mimic the way sensory neurons work in the human body.
