Research in surgical robotics has an established track record at Imperial College, and a number of research and commercial surgical robot platforms have been developed over the years. The Hamlyn Centre is a champion for technological innovation and clinical adoption of robotic, minimally invasive surgery. We work in partnership with major industrial leaders in medical devices and surgical robots, as well as developing our own platforms such as the i-Snake® and Micro-IGES platforms. The Da Vinci surgical robot is used extensively for endoscopic radical prostatectomy, hiatal hernia surgery, and low pelvic and rectal surgery, and in 2003, St Mary’s Hospital carried out its first Totally Endoscopic Robotic Coronary Artery Bypass (TECAB).

The major focus of the Hamlyn Centre is to develop robotic technologies that will transform conventional minimally invasive surgery, explore new ways of empowering robots with human intelligence, and develop[ing miniature 'microbots' with integrated sensing and imaging for targeted therapy and treatment. We work closely with both industrial and academic partners in open platforms such as the DVRK, RAVEN and KUKA. The Centre also has the important mission of driving down costs associated with robotic surgery in order to make the technology more accessible, portable, and affordable. This will allow it to be fully integrated with normal surgical workflows so as to benefit a much wider patient population.

The Hamlyn Centre currently chairs the UK Robotics and Autonomous Systems (UK-RAS) Network. The mission of the Network is to to provide academic leadership in Robotics and Autonomous Systems (RAS), expand collaboration with industry and integrate and coordinate activities across the UK Engineering and Physical Sciences Research Council (EPSRC) funded RAS capital facilities and Centres for Doctoral Training (CDTs).


BibTex format

author = {Zhang, L and Ye, M and Giataganas, P and Hughes, M and Bradu, A and Podoleanu, A and Yang, G},
doi = {10.1109/MRA.2017.2680543},
journal = {IEEE Robotics & Automation Magazine},
pages = {63--72},
title = {From macro to micro: autonomous multiscale image fusion for robotic surgery},
url = {},
volume = {24},
year = {2017}

RIS format (EndNote, RefMan)

AB - In recent years, minimally invasive robotic surgery has shown great promises for enhancing surgical precision and improving patient outcomes. Despite these advances, intraoperative tissue characterisation (such as the identification of cancerous tissue) still relies on traditional biopsy and histology, a process that is time-consuming and often disrupts the normal surgical workflow. In order to provide effective intra-operative decision-making, emerging optical biopsy techniques, such as probe based confocal laser endomicroscopy (pCLE) and optical coherence tomography (OCT), have been developed to provide real-time in vivo, in situ assessment of tissue micro-structures. Clinical deployment of these techniques, however, requires large area surveillance, from macro (mm/cm) to micro (µm) coverage in order to differentiate underlying tissue structures. This article provides a real-time multi-scale fusion scheme for robotic surgery. It demonstrates how the da Vinci surgical robot, used together with the da Vinci Research Kit, can be used for automated 2D scanning of pCLE/OCT probes, providing large area tissue surveillance by image stitching. Open-loop control of the robot provides insufficient precision for probe scanning, and therefore the motion is visually servoed using the live pCLE images (for lateral position) and OCT images (for axial position). The resulting tissue maps can then be fused in real-time with a stereo reconstruction from the laparoscopic video, providing the surgeon with a multi-scale 3D view of the operating site.
AU - Zhang,L
AU - Ye,M
AU - Giataganas,P
AU - Hughes,M
AU - Bradu,A
AU - Podoleanu,A
AU - Yang,G
DO - 10.1109/MRA.2017.2680543
EP - 72
PY - 2017///
SN - 1070-9932
SP - 63
TI - From macro to micro: autonomous multiscale image fusion for robotic surgery
T2 - IEEE Robotics & Automation Magazine
UR -
UR -
VL - 24
ER -