Tactile Robotic System

Tactile robotic systems aim to equip robots with a sense of touch, enabling them to perform complex manipulation tasks requiring fine motor skills and interaction with the environment. Current research emphasizes integrating tactile sensing with vision, utilizing machine learning models like convolutional neural networks and transformer-based architectures for data processing and control, often within simulation environments for efficient training and sim-to-real transfer. This field is significant for advancing robotics in manufacturing, object manipulation, and other applications requiring precise, adaptable interaction, particularly in unstructured or dynamic environments.