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A new type of touch sensor for robotics and other bio-mimicking (bionic) applications is so sensitive that it works from up to 100 mm away, without direct contact between the sensor and the objects being detected.
Electronic skins have become a crucial element in bionic robots, allowing robotic systems to analyse an object’s shape, and to pick it up and move it.
Researchers at Qingdao University in China, with collaborators elsewhere in China and South Korea, developed a sensor that detects interference in the electric field between an object and the sensor from 5 mm to 100 mm away. They described their innovation in the journal Science and Technology of Advanced Materials.
“To bring greater sensitivity and versatility to the sensor, we have developed new composite films with surprising and very useful electrical properties,” says Xinlin Li of the Qingdao University team.
3D finger recognition and data transmission to a mobile phone.
The most surprising finding came when the researchers combined two materials with a high dielectric constant — a measure of their response to electric fields. This composite had an unexpectedly low dielectric constant, a counter-intuitive result ideally suited to making a sensor that is more sensitive to electric fields.
The composite of graphitic carbon nitride and polydimethylsiloxane, a silicone polymer, was then 3D-printed into a grid that could detect objects before contact. The researchers tested its capabilities using their fingers.
“The performance was outstanding, in terms of sensitivity, speed of response, and robust stability through many cycles of use,” says Li. “This opens new possibilities in wearable objects, electronic skin, and remotely controlling devices.”
The scientists incorporated the sensor into a printed circuit board allowing data to be transmitted over 4G networks used by mobile phones and other devices.
They now plan to develop the technology for mass production and explore further possibilities like gesture recognition, obstacle avoidance, and applications in intelligent medical care.
Further information
Prof Xinlin Li
[email protected]
Qingdao University
STAM Inquiries
[email protected]
