Shape Sensing

Shape sensing focuses on accurately determining the three-dimensional configuration of flexible objects, primarily for robotic applications like minimally invasive surgery and industrial automation. Current research emphasizes developing miniaturized, robust sensors—including fiber Bragg gratings (FBGs), resistive flex sensors, and optical fiber systems—often coupled with deep learning models (e.g., convolutional neural networks) for efficient shape reconstruction from sensor data. These advancements improve the precision and reliability of robotic control, enabling safer and more effective operations in challenging environments.