If you’re receptive to theories about robots eventually making humans redundant, here’s a little something to elevate your paranoia: Researchers in Singapore have developed electronic skin with a sense of touch that could respond faster to stimuli than human skin. In addition to boosting a robot’s ability to feel objects and adapt accordingly, the Asynchronous Coded Electronic Skin (ACES) developed by National University of Singapore (NUS) scientists could also improve the performance of prosthetic devices. But you knew they would say that to lull us into a sense of complacency, right?
“Humans use our sense of touch to accomplish almost every daily task, such as picking up a cup of coffee or making a handshake. Without it, we will even lose our sense of balance when walking,” explained Assistant Professor Benjamin Tee from NUS Materials Science and Engineering. “Similarly, robots need to have a sense of touch in order to interact better with humans, but robots today still cannot feel objects very well,” said Tee, who has been working on electronic skin technologies for more than a decade in hopes of giving robots and prosthetic devices a better sense of touch.
|Assistant Professor Benjamin Tee (left) and his team from Materials Science and Engineering at the National University of Singapore.|
Tee and his team spent a year and a half developing a sensor system that detects signals in a manner similar to the human sensor nervous system. Unlike the nerve bundles in the human skin, however, the ACES system is made up of a network of sensors connected via a single electrical conductor. Moreover, it deviates from existing electronic skins that have interlinked wiring systems, making them sensitive to damage and difficult to scale up.
ACES can detect touches more than 1,000 times faster than the human sensory nervous system, according to the researchers. For example, it is capable of differentiating physical contact between different sensors in less than 60 nanoseconds—the fastest time ever achieved by an electronic skin technology—even with large numbers of sensors. ACES-enabled skin can accurately identify the shape, texture and hardness of objects within 10 milliseconds, ten times faster than the blinking of an eye.
The ACES platform also is more robust than existing artificial systems. Unlike current systems used to interconnect sensors in electronic skins, all the sensors in ACES can be connected to a common electrical conductor, with each sensor operating independently, explained a press release on the NUS website. This allows ACES-enabled electronic skin to continue functioning as long as there is one connection between the sensor and the conductor, making it less vulnerable to damage.
But what if the skin, despite everything, sustains some damage? Tee has a solution to that, as well. By pairing ACES with a transparent, self-healing and water-resistant sensor skin layer, also developed by Tee and his team, the electronic skin can self-repair, just like human skin, writes Verdict Medical Devices, reporting on Tee’s research.
“One of the challenges with many self-healing materials today is that they are not transparent and they do not work efficiently when wet,” said Tee, as reported by Verdict Medical Devices. “With this idea in mind, we began to look at jellyfish—they are transparent, and able to sense the wet environment. So, we wondered how we could make an artificial material that could mimic the water-resistant nature of jellyfish and yet also be touch-sensitive."
The self-healing skin works by suspending a fluorocarbon-based polymer in a fluorine-rich ionic liquid to create a gel. The polymer network interacts with the ionic liquid via reversible ion-dipole interactions, which allows it to self-heal, reported Verdict Medical Devices.
ACES technology can be used to develop prosthetic limbs that will help disabled individuals better restore their sense of touch, said Tee. Other potential applications include developing more intelligent robots that can perform disaster recovery tasks or take over mundane packaging operations, for example. The NUS team is looking to further apply the ACES platform on advanced robots and prosthetic devices in the next phase of its research.
The research was first reported in the scientific journal Science Robotics published on July 17, 2019.