MIT researchers have created a "massive" dataset to help AI systems identify objects through touch alone, using a sensor-laden glove costing around $10 to make. The knitted, scalable tactile glove was fitted with 550 sensors to capture pressure signals, turning them into tactile maps to create a dataset of 26 everyday items. "We can use this data for machine learning and image recognition," said lead author Dr. Xiaodong Zhang, an associate professor at the Massachusetts Institute of Technology.
MIT researchers have created a "massive" dataset to help AI systems identify objects through touch alone, using a sensor-laden glove costing around $10 to make. The knitted, scalable tactile glove was fitted with 550 sensors to capture pressure signals, turning them into tactile maps to create a dataset of 26 everyday items. A convolutional neural network used it to identify objects with 76% accuracy and, using a separate dataset, guessed the weight of items to within around 60g.