Brief description:
Background:
Robotic Assisted Minimal Invasive Surgery (RAMIS) integrates the accuracy, precision, and high payload of robots with human problem-solving capabilities, opening up new horizons in 21st century surgery. The most common surgical robot, the da Vinci surgical robotic system however poses new challenges for surgeons as well (e.g. lack of force feedback, limited field of vision, etc.) thus in the Antal Bejczy Center of Intelligent Robotics (BARK) we are developing solutions that can potentially help surgeons to overcome these difficulties.
Task:
Tracking the surgeon’s eye movements is useful in several ways (surgical ability assessment, assisting with operating room communication, robot control). The task of this thesiswork is to implement and examine different position control methods of the endoscopic camera of the da Vinci Robot based on gaze tracking.
Software environments: ROS, Python/C++
Task details:
- Identification of current state-of-the-art solutions
- Familiarize with the eye gaze tracking system and the da Vinci Robot’s control system
- Implementation of different control methods for the endoscope-holding robot arm
- Performance based assessment of the implemented control methods
- User-experience based assessment of the implemented control methods