Knot-inspired optical sensors for slip detection and friction measurement in dexterous robotic manipulation

Abstract

Friction plays a critical role in dexterous robotic manipulation. However, realizing friction sensing remains a challenge due to the difficulty in designing sensing structures to decouple multi-axial forces. Inspired by the topological mechanics of knots, we construct optical fiber knot (OFN) sensors for slip detection and friction measurement. By introducing local-ized self-contacts along the fiber, the knot structure enables anisotropic responses to normal and frictional forces. By em-ploying OFNs and a change point detection algorithm, we demonstrate adaptive robotic grasping of slipping cups. We further develop a robotic finger that can measure tri-axial forces via a centrosymmetric architecture composed of five OFNs. Such a tactile finger allows a robotic hand to manipulate human tools dexterously. This work could provide a straightforward and cost-effective strategy for promoting adaptive grasping, dexterous manipulation, and human-robot interaction with tactile sensing.