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 Wojciech Matusik 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.
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.