Modeling and steering of a novel actuated-tip needle through a soft-tissue simulant using Fiber Bragg Grating sensors

Needle insertions are common during surgical procedures. Accurately delivering the needle at a specific location in the human body is of importance for the clinical outcome of the procedure. Studies have already shown that robotically inserting traditional needles with a bevel tip can improve targeting accuracy. However, steering of such needles requires spinning the needle, which may lead to additional tissue damage. Therefore, we propose a novel design consisting of a flexible needle with a tendon-driven actuated-tip. Changing the orientation of the actuated-tip allows to control the steering direction of the needle and the amount of deflection. We derive the kinematic model which describes the needle path given the actuated-tip orientation based on nonholonomic kinematics. We present a method for steering the needle towards a target location in soft tissue. This method incorporates online parameter estimation in order to adapt for changes in tissue stiffness. Needle insertion experiments are performed in soft-tissue simulants, made from porcine gelatin. Needle tip pose is measured during insertion using Fiber Bragg Grating (FBG) based shape reconstruction. Results show that the needle can be steered towards targets located at 20 mm from the initial insertion axis, at a depth of 100 mm with a mean targeting error of 2.02 mm.