Embeddable Coiled Soft Sensor-Based Joint Angle Sensing for Flexible Surgical Manipulator

Abstract

Tendon-driven flexible endoscopic surgical robots have been developed to access narrow curved paths without incision. Robot shape information is essential for precise control and to prevent unwanted tissue damage. In this paper, we propose a joint angle sensing method using coiled soft sensors to estimate the shape of the hyperredundant manipulator, which is commonly used in flexible endoscopic surgical robots. The soft sensors can be fabricated with small size and are highly stretchable, such that by being pre-stretched, they can be integrated between individual joints, maintain a center hollow, and sense both compression and extension. The pre-stretch length is experimentally selected by using the sensor linearity to maximize the potential sensitivity. We validated the proposed design using a two-degree of freedom (DOF) single joint manipulator by implementing two sensors; sensors at all joints could sense joint angle independently and simultaneously with a root-mean-square error (RMSE) less than 2.53°. Based on the proposed method, a two-DOF configuration of the hyperredundant manipulator that can be used in real applications was achieved, following a constant curvature model in real time with values RMSE of 2.30° and 2.63°, for pitch and yaw joint angle respectively.