  In robotic-assisted partial nephrectomy, surgeons remove a part of a kidney
often due to the presence of a mass. A drop-in ultrasound probe paired to a
surgical robot is deployed to execute multiple swipes over the kidney surface
to localise the mass and define the margins of resection. This sub-task is
challenging and must be performed by a highly skilled surgeon. Automating this
sub-task may reduce cognitive load for the surgeon and improve patient
outcomes. The overall goal of this work is to autonomously move the ultrasound
probe on the surface of the kidney taking advantage of the use of the
Pneumatically Attachable Flexible (PAF) rail system, a soft robotic device used
for organ scanning and repositioning. First, we integrate a shape-sensing
optical fibre into the PAF rail system to evaluate the curvature of target
organs in robotic-assisted laparoscopic surgery. Then, we investigate the
impact of the stiffness of the material of the PAF rail on the curvature
sensing accuracy, considering that soft targets are present in the surgical
field. Finally, we use shape sensing to plan the trajectory of the da Vinci
surgical robot paired with a drop-in ultrasound probe and autonomously generate
an Ultrasound scan of a kidney phantom.
