A team of Facebook researchers has built a new kind of electronic skin and fingertip that offers an inexpensive, versatile, durable, and replaceable solution for long-term robotic use.
Called ‘ReSkin’, it employs a self-supervised learning algorithm to help auto-calibrate the sensor, making it able to share data between sensors and systems to make robots more sensitive.
‘ReSkin’ is a new open-source touch-sensing “skin” created by Meta AI researchers in collaboration with Carnegie Mellon University that can help researchers advance their AI’s tactile-sensing skills quickly. At scale, Facebook said in a statement late on Monday.
Robust tactile sensing is a significant bottleneck in robotics.
“Current sensors are either too expensive, offer a poor resolution, or are simply too unwieldy for custom robots. ReSkin has the potential to overcome several of these issues,” said Lerrel Pinto, an assistant professor of computer science at New York University.
Its lightweight and small form factor make it compatible with arbitrary grippers.
“We’ll be releasing the design, relevant documentation, code, and base models in order to help AI researchers use ReSkin without having to collect or train their own data sets. That, in turn, should help advance AI’s tactile sensing skills quickly and at scale,” Facebook noted.
A generalizable tactile sensing skin like aReSkin’ will provide a source of rich contact data that could be helpful in advancing AI in a wide range of touch-based tasks, including object classification, proprioception, and robotic grasping.
AI models trained with learned tactile sensing skills will be capable of many types of tasks, including those that require higher sensitivity, such as working in health care settings, or greater dexterity, such as maneuvering small, soft, or sensitive objects.
“ReSkin can also be integrated with other sensors to collect visual, sound, and touch data outside the lab and in unstructured environments,” said Facebook.
ReSkin is inexpensive to produce, costing less than $6 each at 100 units and even less at larger quantities.
It’s 2-3 mm thick and can be used for more than 50,000 interactions while also having a high temporal resolution of up to 400Hz and a spatial resolution of 1 mm with 90 percent accuracy.
“These specifications make it ideal for form factors as varied as robot hands, tactile gloves, arm sleeves, and even dog shoes, all of which can help researchers collect tactile data for new AI models that would previously have been difficult or impossible to gather,” the social network said.