Autonomous Robotic Endoscope Control based on Semantically Rich Instructions.

In keyhole interventions, surgeons rely on a colleague to act as a camera assistant when their hands are occupied with surgical instruments. This often leads to reduced image stability, increased task completion times and sometimes errors. Robotic endoscope holders (REHs), controlled by a set of basic instructions, have been proposed as an alternative, but their unnatural handling increases the cognitive load of the surgeon, hindering their widespread clinical acceptance. We propose that REHs collaborate with the operating surgeon via semantically rich instructions that closely resemble those issued to a human camera assistant, such as "focus on my right-hand instrument". As a proof-of-concept, we present a novel system that paves the way towards a synergistic interaction between surgeons and REHs. The proposed platform allows the surgeon to perform a bi-manual coordination and navigation task, while a robotic arm autonomously performs various endoscope positioning tasks. Within our system, we propose a novel tooltip localization method based on surgical tool segmentation, and a novel visual servoing approach that ensures smooth and correct motion of the endoscope camera. We validate our vision pipeline and run a user study of this system. Through successful application in a medically proven bi-manual coordination and navigation task, the framework has shown to be a promising starting point towards broader clinical adoption of REHs.