Huber Martin, Mitchell John Bason, Henry Ross, Ourselin Sébastien, Vercauteren Tom, Bergeles Christos
School of Biomedical Engineering & Image Sciences, Faculty of Life Sciences & Medicine, King's College London, London, United Kingdom.
Department of Medical Physics and Biomedical Engineering, Faculty of Engineering Sciences, University College London, London, United Kingdom.
Int Symp Med Robot. 2021 Nov 17;220:1-7. doi: 10.1109/ISMR48346.2021.9661563.
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. A video is provided.
微创手术（MIS）中占主导地位的视觉伺服方法遵循单点或根据手术工具的距离调整内窥镜的视野。这些方法依靠相对于相机坐标系的点位置来推断控制策略。与主流方法不同，我们制定了一种机器人控制器，该控制器允许基于图像的视觉伺服，既不需要明确的工具和相机位置，也不需要任何明确的图像深度信息。所提出的方法依赖于基于单应性的图像配准，这将自动化范式从以点为中心转变为以外科手术场景为中心的方法。它同时考虑了可编程的运动远程中心（RCM）。我们的方法允许外科医生构建所需视图的图形，一旦构建完成，无论机器人-患者坐标系如何变换，都可以手动选择并自动伺服到这些视图。我们在腹部模型上评估了我们的方法，并提供了一个开源的ROS Moveit集成，可与任何串联机械手配合使用。提供了一段视频。
