Vision-based surgical robot arm docking assistance for optimal spatial configuration

Lead Research Organisation: King's College London
Department Name: Imaging & Biomedical Engineering

Abstract

Smaller modular surgical robot systems using several robotic arms that can be positioned independently are now available. These systems have been designed for easier integration in existing space-restricted operating rooms and to allow for patient- and operation-specific robotic configurations to be used. Additional training may however be required to optimally position the arms and subjective configuration preferences may lead to increased disparity of care. In this project, the student will develop novel computer vision and data science approaches to: 1) learn from existing setups used in expert centres and suggest optimal patient- and operation-specific robotic configurations; 2) design learning-based 3D vision algorithms to accurately map the relative position of the patient and the robotic arms, which may be draped for sterility; and 3) provide assistance to the theatre staff to dock the arms in the target position. Accurate base-to-base calibration will also be a key enabler for automated multi-arm control.

Publications

10 25 50

Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/Y035364/1 31/03/2024 29/09/2032
2930165 Studentship EP/Y035364/1 30/09/2024 29/09/2028 Yanghe Hao