TY - CHAP
T1 - Homography-based Visual Servoing with Remote Center of Motion for Semi-autonomous Robotic Endoscope Manipulation
AU - Huber, Martin
AU - Bason Mitchell, John
AU - Henry, Ross
AU - Ourselin, Sebastien
AU - Vercauteren, Tom
AU - Bergeles, Christos
N1 - Funding Information:
This work was supported by core and project funding from the Wellcome/EPSRC [WT203148/Z/16/Z; NS/A000049/1; WT101957; NS/A000027/1]. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101016985 (FAROS project). The authors gratefully acknowledge the support of Dr Carlo Seneci, Maleeha Al-Hamadani, Dr Chayanin Tangwiriyasakul, Dr Hongbing Liu, and Julius Bernth in the research that led to this manuscript.
Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - The dominant visual servoing approaches in Minimally Invasive Surgery (MIS) follow single points or adapt the endoscope's field of view based on the surgical tools' distance. These methods rely on point positions with respect to the camera frame to infer a control policy. Deviating from the dominant methods, we formulate a robotic controller that allows for image-based visual servoing that requires neither explicit tool and camera positions nor any explicit image depth information. The proposed method relies on homography-based image registration, which changes the automation paradigm from point-centric towards surgical-scene-centric approach. It simultaneously respects a programmable Remote Center of Motion (RCM). Our approach allows a surgeon to build a graph of desired views, from which, once built, views can be manually selected and automatically servoed to irrespective of robot-patient frame transformation changes. We evaluate our method on an abdominal phantom and provide an open source ROS Moveit integration for use with any serial manipulator 3. A video is provided 4.
AB - The dominant visual servoing approaches in Minimally Invasive Surgery (MIS) follow single points or adapt the endoscope's field of view based on the surgical tools' distance. These methods rely on point positions with respect to the camera frame to infer a control policy. Deviating from the dominant methods, we formulate a robotic controller that allows for image-based visual servoing that requires neither explicit tool and camera positions nor any explicit image depth information. The proposed method relies on homography-based image registration, which changes the automation paradigm from point-centric towards surgical-scene-centric approach. It simultaneously respects a programmable Remote Center of Motion (RCM). Our approach allows a surgeon to build a graph of desired views, from which, once built, views can be manually selected and automatically servoed to irrespective of robot-patient frame transformation changes. We evaluate our method on an abdominal phantom and provide an open source ROS Moveit integration for use with any serial manipulator 3. A video is provided 4.
UR - http://www.scopus.com/inward/record.url?scp=85124801620&partnerID=8YFLogxK
U2 - 10.1109/ISMR48346.2021.9661563
DO - 10.1109/ISMR48346.2021.9661563
M3 - Conference paper
AN - SCOPUS:85124801620
T3 - 2021 International Symposium on Medical Robotics, ISMR 2021
BT - 2021 International Symposium on Medical Robotics, ISMR 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 International Symposium on Medical Robotics, ISMR 2021
Y2 - 17 November 2021 through 19 November 2021
ER -