Open AccessSupervised Autonomous Electrosurgery via Biocompatible Near-Infrared Tissue Tracking Techniques
Author(s) -
Hamed Saeidi,
Jiawei Ge,
Michael Kam,
Justin D. Opfermann,
Simon Léonard,
Arjun S. Joshi,
Axel Krieger
Publication year - 2019
Publication title -
ieee transactions on medical robotics and bionics
Language(s) - English
Resource type - Journals
ISSN - 2576-3202
DOI - 10.1109/tmrb.2019.2949870
Subject(s) - computer science , computer vision , teleoperation , artificial intelligence , robot , trajectory , biocompatible material , biomedical engineering , automation , medicine , engineering , mechanical engineering , physics , astronomy
Autonomous robotic surgery systems aim to improve patient outcomes by leveraging the repeatability and consistency of automation and also reducing human induced errors. However, intraoperative autonomous soft tissue tracking and robot control still remains a challenge due to the lack of structure, and high deformability of such tissues. In this paper, we take advantage of biocompatible Near-Infrared (NIR) marking methods and develop a supervised autonomous 3D path planning, filtering, and control strategy for our Smart Tissue Autonomous Robot (STAR) to enable precise and consistent incisions on complex 3D soft tissues. Our experimental results on cadaver porcine tongue samples indicate that the proposed strategy reduces surface incision error and depth incision error by 40.03% and 51.5%, respectively, compared to a teleoperation strategy via da Vinci. Furthermore, compared to an autonomous path planning method with linear interpolation between the NIR markers, the proposed strategy reduces the incision depth error by 48.58% by taking advantage of 3D tissue surface information.