Insider Brief
- Researchers from the University of Cambridge and UCL have developed a meltable, flexible electronic skin capable of sensing and processing multiple types of physical contact across its entire surface.
- The skin detects over 860,000 conductive pathways, enabling it to recognize taps, pressure, temperature changes, and physical damage, using machine learning to identify the most relevant signals.
- Potential applications include humanoid robotics, prosthetics, automotive systems, and disaster relief, with findings published in the journal Science Robotics.
PRESS RELEASE – The researchers, from the University of Cambridge and University College London (UCL), developed the flexible, conductive skin, which is easy to fabricate and can be melted down and formed into a wide range of complex shapes. The technology senses and processes a range of physical inputs, allowing robots to interact with the physical world in a more meaningful way.
Unlike other solutions for robotic touch, which typically work via sensors embedded in small areas and require different sensors to detect different types of touch, the entirety of the electronic skin developed by the Cambridge and UCL researchers is a sensor, bringing it closer to our own sensor system: our skin.
Although the robotic skin is not as sensitive as human skin, it can detect signals from over 860,000 tiny pathways in the material, enabling it to recognise different types of touch and pressure – like the tap of a finger, a hot or cold surface, damage caused by cutting or stabbing, or multiple points being touched at once – in a single material.
The researchers used a combination of physical tests and machine learning techniques to help the robotic skin ‘learn’ which of these pathways matter most, so it can sense different types of contact more efficiently.
In addition to potential future applications for humanoid robots or human prosthetics where a sense of touch is vital, the researchers say the robotic skin could be useful in industries as varied as the automotive sector or disaster relief. The results are reported in the journal Science Robotics.
