Haptic Signal

Haptic signals, encompassing tactile and kinesthetic feedback, aim to enhance human-robot interaction and improve various applications by providing a sense of touch. Current research focuses on developing effective methods for generating and interpreting haptic information, employing machine learning models like convolutional neural networks (CNNs) and Long Short-Term Memory (LSTM) networks for tasks such as object recognition, risk prediction, and teleoperation. This field is significant for improving accessibility (e.g., for visually impaired individuals), automating complex tasks (e.g., robotic charging), and enhancing the realism and intuitiveness of virtual and augmented reality experiences. The integration of haptic feedback with other sensory modalities, such as vision and audio, is a key area of ongoing development.