Basic description of the topic:
During the last three decades, the rapid spread of Robot-Assisted Minimally Invasive Surgery (RAMIS) induced a revolution to the surgical practice. In the new technique, interventions can be performed through small incisions, while the area of operation is viewed on endoscopic camera stream. Despite its benefits, RAMIS also presented difficulties to the surgeons, some subtasks of the operation became monotonous and time-consuming. A significant portion of current research efforts aims to automate these subtasks to reduce the cognitive load on the surgeon. Although solutions on automating interventions performed on rigid tissues exist, automation regarding soft tissues is still highly challenging. During the last years, the automation of surgical training exercises gained currency as a simplified model of more complex subtasks.
The task is the high level implementation of autonomous surgical training exercises on the research-enhanced da Vinci Surgical System, da Vinci Research Kit (DVRK) available in the Antal Bejczy Center for Intelligent Robotics. The low level control of the robot is supported by the modular iRob Surgical Automation Framework (irob-saf). The task includes object detection and pose estimation on RGB-D camera stream, high level implementation of the workflow of the exercise, and the validation of the solution.
Detailed tasks:
- Literature overview in the field of surgical subtask automation;
- Get acquainted with ROS, the da Vinci Surgical System, the DVRK platform and irob-saf;
- Get acquainted with the used RGB-D camera;
- Object detection and pose estimation;
- Integrating the vision system with the robot and the DVRK research platform and irob-saf;
- High level implementation of the workflow of the chosen surgical training exercise
- Testing and analyzing the results.
Over the course of the project, the student will get involved with the various research project of the Antal Bejczy Center for Intelligent Robotics.