Measuring how much light goes from every LED to every diode, the researchers end up with close to 1,000 signals that each contain some information about the contact that was made. Whenever the finger touches something, its skin deforms, so light shifts around in the transparent layer underneath. The finger also has more than 30 photodiodes that measure how the light bounces around. Under the "skin," their finger has a layer made of transparent silicone, into which they shined light from more than 30 LEDs. Firstly, in this project, the researchers use light to sense touch. The study, published online in IEEE/ASME Transactions on Mechatronics, demonstrates the two aspects of the underlying technology that combine to enable the new results. Their final result is a fully integrated, sensorized robot finger, with a low wire count, built using accessible manufacturing methods and designed for easy integration into dexterous hands. They then demonstrated that purely data-driven deep learning methods can extract useful information from the data, including contact location and applied normal force, without the need for analytical models. The Columbia Engineering team took a new approach: the novel use of overlapping signals from light emitters and receivers embedded in a transparent waveguide layer that covers the functional areas of the finger.īy measuring light transport between every emitter and receiver, they showed that they can obtain a very rich signal data set that changes in response to deformation of the finger due to touch. "In this paper, we have demonstrated a multicurved robotic finger with accurate touch localization and normal force detection over complex 3D surfaces."Ĭurrent methods for building touch sensors have proven difficult to integrate into robot fingers due to multiple challenges, including difficulty in covering multicurved surfaces, high wire count, or difficulty fitting into small fingertips, thus preventing use in dexterous hands. "There has long been a gap between stand-alone tactile sensors and fully integrated tactile fingers - tactile sensing is still far from ubiquitous in robotic manipulation," says Matei Ciocarlie, associate professor in the departments of mechanical engineering and computer science, who led this work in collaboration with Electrical Engineering Professor Ioannis (John) Kymissis.
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