🤖 AI Summary
This study addresses the challenge of accurate shape estimation in continuum robots, whose high compliance hinders precise control in minimally invasive surgery. The authors propose an integrated fabrication approach based on direct laser writing (DLW), wherein graphene strain sensors are in situ generated via laser carbonization of polymers and monolithically integrated with continuum joints. This design simplifies structural complexity and enhances sensor consistency. Coupled with both linear and nonlinear modeling techniques and a closed-loop control algorithm, the system achieves significantly improved deformation sensing accuracy. Experimental results demonstrate a joint angle prediction error as low as 1.76° and a closed-loop tracking error under 3°, validating the effectiveness and practicality of the proposed sensing strategy.
📝 Abstract
Continuum robots offer a promising approach for minimally invasive and natural-orifice surgical procedures due to their inherent compliance and dexterity. However, this flexibility also makes estimating the current shape of the robot challenging. Several approaches have been used to reconstruct the shape of these robots, including imaging, optical sensing, magnetic sensing, and resistive sensing. Strain sensors fabricated using direct laser writing (DLW) could provide an alternative sensing method. This technique involves using a laser to induce carbonization of certain polymers to create graphene patterns, such as strain sensors. In this paper, we demonstrate how a flexible continuum joint and a DLW sensor can be machined as one monolithic structure using the same laser and the same setup. The fabricated sensors are characterized using linear and nonlinear models, which are used to predict the joint angle with error as low as 1.76 degrees. Furthermore, we demonstrate how a DLW sensor can be used to implement closed-loop control in a robotic joint, achieving tracking error under 3 degrees.