Material Recognition

Material recognition, the automated identification of materials from various data sources, aims to improve robotic perception, enhance e-commerce design workflows, and enable more sophisticated human-computer interaction. Current research focuses on developing robust models using diverse data modalities, including RGB-D images, force measurements, tactile sensing (vibration and thermal), and hyperspectral imaging, often employing deep learning architectures like Siamese networks and recursive Bayesian estimation. These advancements are driving progress in applications ranging from autonomous navigation and granular material handling to assistive robotics for visually impaired individuals and intelligent design automation in e-commerce.