MIT researchers have developed a low-cost, sensor-packed glove that captures pressure signals as humans interact with objects. The glove can be used to create high-resolution tactile datasets that robots can leverage to better identify, weigh, and manipulate objects.
The researchers developed a low-cost knitted glove, called “scalable tactile glove” (STAG), equipped with about 550 tiny sensors across nearly the entire hand. Each sensor captures pressure signals as humans interact with objects in various ways. A neural network processes the signals to “learn” a dataset of pressure-signal patterns related to specific objects. Then, the system uses that dataset to classify the objects and predict their weights by feel alone, with no visual input needed.
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