Improved electronic skin gives robots the human touch

The study, published in Science Robotics, details the development of the flexible, conductive skin, which is easy to fabricate and can be melted down and formed into a wide range of complex shapes. Although the robotic skin is not as sensitive as human skin, it can detect signals from over 860,000 tiny pathways in the material.

Unlike other solutions for robotic touch, which typically work via sensors embedded in specific areas and require different sensors to detect different types of touch, the entirety of the electronic skin is a sensor that can recognise different types of touch and pressure, such as the tap of a finger, a hot or cold surface, damage caused by sharp objects, or multiple points being touched at once.

The researchers used a combination of physical tests and machine learning techniques to help the robotic skin to ‘learn’ which of these pathways matter most, in order to 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.

Dr Thomas George Thuruthel, co-author of the study from UCL Computer Science, said: “We’re not quite at the level where the robotic skin is as good as human skin, but we think it’s better than anything else out there at the moment. Our method is flexible and easier to build than traditional sensors, and we’re able to calibrate it using human touch for a range of tasks.”

Electronic skins work by converting physical information – like pressure or temperature – into electronic signals. In most cases, different types of sensors are needed for different types of touch – one type of sensor to detect pressure, another for temperature, and so on – which are then embedded into soft, flexible materials. However, the signals from these different sensors can interfere with each other, and the materials are easily damaged.

Dr David Hardman, lead author of the study from Cambridge’s Department of Engineering, said: “Having different sensors for different types of touch leads to materials that are complex to make. We wanted to develop a solution that can detect multiple types of touch at once, but in a single material.”

The new technology uses one type of sensor that reacts differently to different types of touch, known as multi-modal sensing. While it’s challenging to separate out the cause of each signal, multi-modal sensing materials are easier to make and more robust.

The researchers melted down a soft, stretchy and electrically conductive gelatine-based hydrogel, and cast it into the shape of a human hand. They tested a range of different electrode configurations to determine which gave them the most useful information about different types of touch. From just 32 electrodes placed at the wrist, they were able to collect over 1.7 million pieces of information over the whole hand, thanks to the tiny pathways in the conductive material.

The skin was then tested on different types of touch. The researchers blasted it with a heat gun, pressed it with their fingers and a robotic arm, gently touched it with their fingers, and even cut it open with a scalpel. The team then used the data gathered during these tests to train a machine learning model so the hand would recognise what the different types of touch meant. 

Dr Hardman added: “We’re able to squeeze a lot of information from these materials – they can take thousands of measurements very quickly. They’re measuring lots of different things at once, over a large surface area.”

In future, the researchers are hoping to improve the durability of the electronic skin, and to carry out further tests on real-world robotic tasks.

The research was supported by Samsung Global Research Outreach Program, the Royal Society, and the Engineering and Physical Sciences Research Council (EPSRC), part of UK Research and Innovation (UKRI).

Links

• Dr Thomas George Thuruthel's academic profile
• UCL Computer Science
• UCL Engineering

Images

• Electronic skin being tested. Credit: University of Cambridge. 

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