Localization of Interaction using Fibre-Optic Shape Sensing in Soft-Robotic Surgery Tools

Abstract

Minimally invasive surgery requires real-time tool tracking to guide the surgeon where depth perception and visual occlusion present navigational challenges. Although vision-based and external sensor-based tracking methods exist, fibre-optic sensing can overcome their limitations as they can be integrated directly into the device, are biocompatible, small, robust and geometrically versatile. In this paper, we integrate a fibre Bragg grating-based shape sensor into a soft robotic device. The soft robot is the pneumatically attachable flexible (PAF) rail designed to act as a soft interface between manipulation tools and intra-operative imaging devices. We demonstrate that the shape sensing fibre can detect the location of the tools paired with the PAF rail, by exploiting the change in curvature sensed by the fibre when a strain is applied to it. We then validate this with a series of grasping tasks and continuous US swipes, using the system to detect in real-time the location of the tools interacting with the PAF rail. The overall location-sensing accuracy of the system is 64.6%, with a margin of error between predicted location and actual location of 3.75 mm.