Artificial skin can detect nearby objects without even touching them

Skin made of two layers of electrodes around an ion-implanted sponge is better at sensing than human skin.

To chris stokel walker

Artificial skin is superior to human skin in object sensing, as it can detect and identify items that have not yet been touched.

“Human skin has to touch something to tell you what’s there,” says Yifan Wang of Singapore’s Nanyang Technological University. “Human skin can only judge the softness and hardness of an object. We wanted artificial skin to have more functions.”

Wang and his colleagues’ artificial skin can sense whether an object is nearby and discern clues about the type of material it’s made of without even touching it. You can tell if it’s a piece, if it’s plastic, if it’s a biomaterial,” he says.

The skin consists of two outer layers of nickel-coated conductive fabric that act as electrodes. These surround a porous sponge soaked in an ionic liquid, a salt in its liquid state that acts as a conduit for electricity. The two layers act as capacitors, storing electrical energy in the electric field.

The ions in the sponge enhance the performance of the capacitor, effectively measuring how much the distance between the two layers of electrodes changes. The ability to detect small changes is behind how artificial skin detects when it touches something.

The detection performance of the capacitor, Wang claims, is 10 to 100 times more sensitive than a standard capacitor, meaning it can detect very small changes in the electric field around the skin, even when an object is nearby. can detect that there is In addition, these subtle changes help us identify what kind of material nearby objects are made of.

In tests, the skin detected and successfully classified a series of objects brought close to either polymer, metal, or skin, indicated by specific changes in capacitor readings.

“The process is relatively simple. As the components approach the contact, they enter the edge of the electric field of the capacitive structure,” says Jonathan Aitken of the University of Sheffield, UK. “There are some interesting future avenues,” he says, but for now the skin relies on machine learning techniques to identify how detected objects compare to data from known materials. increase.

Wang believes this skin will work on robotic fingers, helping robots in factories better understand which objects to pick up and leave without grabbing, as well as for prosthetic limbs. .