The robotic surgery market is currently exploding, many manufacturers will enter the robotic surgery market in the years to come. After the current shift from open to robotic surgery, we know see a clear shift towards image-guided surgery. In image-guided surgery, patient-specific models are being overlayed onto surgical viewpoints as to inform the surgeon on the anatomy and possible caveats.
As such, augmented reality overlays are starting to find their way into the robotic consoles. One of the bottlenecks in this field is pose estimation of the robotic arms and more specifically of the endoscopic camera. Orsi academy is the world's largest robotic surgery training facility and as such heavily invested in this shift towards image-guided surgery. Accurately knowing where the surgical position of the camera is inside the patient, provides extra information to enable image-guided surgery and augmented reality overlays.
The goal of this masterthesis is to develop a prototype for pose estimation in robotic surgery. The student will build a setup using existing LIDAR cameras and sensors to deploy this to robotic surgery arms.