Title :
Learning surgical know-how: Dexterity for a cognitive endoscope robot
Author :
Andreas Bihlmaier;Heinz Worn
Author_Institution :
Institute for Anthropomatics and Robotics (IAR), Intelligent Process Control and Robotics Lab (IPR), Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
fDate :
7/1/2015 12:00:00 AM
Abstract :
A successful surgery requires a working cooperation between the surgeon, the anesthetist and the operating room staff. In minimally invasive surgery a further cooperation is essential: The teamwork between surgeon and camera assistant. Because the surgeon has to handle two instruments, he is unable to guide the endoscope at the same time. Thus the surgeon has to rely on the assistant to provide him with a proper view of the anatomical structures he is operating on. Unfortunately, in practice the team does often not have a lot of teamwork experience. Good positioning of the endoscope does not follow simple control rules, but is highly dependent on the current task and the individual surgical technique. In some cases both instruments should be in the center of the field of view, in others only one instrument is visible at the edge of the image. The paper describes how this endoscope guidance know-how can be learned from the assistant and made available to a cognitive camera guidance robot. As a result, the surgeon can rely on an assistance system, which works based on recorded surgical know-how instead of manually programmed actions.
Keywords :
"Endoscopes","Surgery","Cameras","Instruments","Knowledge based systems","Robot sensing systems"
Conference_Titel :
Cybernetics and Intelligent Systems (CIS) and IEEE Conference on Robotics, Automation and Mechatronics (RAM), 2015 IEEE 7th International Conference on
Print_ISBN :
978-1-4673-7337-1
Electronic_ISBN :
2326-8239
DOI :
10.1109/ICCIS.2015.7274610