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).


Search or filter publications

Filter by type:

Filter by publication type

Filter by year:

to

Results

  • Showing results for:
  • Reset all filters

Search results

  • Journal article
    Zhang D, Lo FP-W, Zheng J-Q, Bai W, Yang G-Z, Lo Bet al., 2020,

    Data-driven microscopic pose and depth estimation for optical microrobot manipulation

    , ACS Photonics, Vol: 7, Pages: 3003-3014, ISSN: 2330-4022

    Optical microrobots have a wide range of applications in biomedical research for both in vitro and in vivo studies. In most microrobotic systems, the video captured by a monocular camera is the only way for visualizing the movements of microrobots, and only planar motion, in general, can be captured by a monocular camera system. Accurate depth estimation is essential for 3D reconstruction or autofocusing of microplatforms, while the pose and depth estimation are necessary to enhance the 3D perception of the microrobotic systems to enable dexterous micromanipulation and other tasks. In this paper, we propose a data-driven method for pose and depth estimation in an optically manipulated microrobotic system. Focus measurement is used to obtain features for Gaussian Process Regression (GPR), which enables precise depth estimation. For mobile microrobots with varying poses, a novel method is developed based on a deep residual neural network with the incorporation of prior domain knowledge about the optical microrobots encoded via GPR. The method can simultaneously track microrobots with complex shapes and estimate the pose and depth values of the optical microrobots. Cross-validation has been conducted to demonstrate the submicron accuracy of the proposed method and precise pose and depth perception for microrobots. We further demonstrate the generalizability of the method by adapting it to microrobots of different shapes using transfer learning with few-shot calibration. Intuitive visualization is provided to facilitate effective human-robot interaction during micromanipulation based on pose and depth estimation results.

  • Conference paper
    Zhan J, Cartucho J, Giannarou S, 2020,

    Autonomous tissue scanning under free-form motion for intraoperative tissue characterisation

    , 2020 IEEE International Conference on Robotics and Automation (ICRA), Publisher: IEEE, Pages: 11147-11154

    In Minimally Invasive Surgery (MIS), tissue scanning with imaging probes is required for subsurface visualisation to characterise the state of the tissue. However, scanning of large tissue surfaces in the presence of motion is a challenging task for the surgeon. Recently, robot-assisted local tissue scanning has been investigated for motion stabilisation of imaging probes to facilitate the capturing of good quality images and reduce the surgeon's cognitive load. Nonetheless, these approaches require the tissue surface to be static or translating with periodic motion. To eliminate these assumptions, we propose a visual servoing framework for autonomous tissue scanning, able to deal with free-form tissue motion. The 3D structure of the surgical scene is recovered, and a feature-based method is proposed to estimate the motion of the tissue in real-time. The desired scanning trajectory is manually defined on a reference frame and continuously updated using projective geometry to follow the tissue motion and control the movement of the robotic arm. The advantage of the proposed method is that it does not require the learning of the tissue motion prior to scanning and can deal with free-form motion. We deployed this framework on the da Vinci ® surgical robot using the da Vinci Research Kit (dVRK) for Ultrasound tissue scanning. Our framework can be easily extended to other probe-based imaging modalities.

  • Journal article
    Kim JA, Wales DJ, Yang G-Z, 2020,

    Optical spectroscopy for in vivo medical diagnosis—a review of the state of the art and future perspectives

    , Progress in Biomedical Engineering, Vol: 2, Pages: 042001-042001
  • Journal article
    Gil B, Li B, Gao A, Yang G-Zet al., 2020,

    Miniaturized Piezo Force Sensor for a Medical Catheter and Implantable Device

    , ACS APPLIED ELECTRONIC MATERIALS, Vol: 2, Pages: 2669-2677, ISSN: 2637-6113
  • Journal article
    Zhang D, Barbot A, Lo B, Yang G-Zet al., 2020,

    Distributed force control for microrobot manipulation via planar multi-spot optical tweezer

    , Advanced Optical Materials, Vol: 8, Pages: 1-15, ISSN: 2195-1071

    Optical tweezers (OT) represent a versatile tool for micro‐manipulation. To avoid damages to living cells caused by illuminating laser directly on them, microrobots controlled by OT can be used for manipulation of cells or living organisms in microscopic scale. Translation and planar rotation motion of microrobots can be realized by using a multi‐spot planar OT. However, out‐of‐plane manipulation of microrobots is difficult to achieve with a planar OT. This paper presents a distributed manipulation scheme based on multiple laser spots, which can control the out‐of‐plane pose of a microrobot along multiple axes. Different microrobot designs have been investigated and fabricated for experimental validation. The main contributions of this paper include: i) development of a generic model for the structure design of microrobots which enables multi‐dimensional (6D) control via conventional multi‐spot OT; ii) introduction of the distributed force control for microrobot manipulation based on characteristic distance and power intensity distribution. Experiments are performed to demonstrate the effectiveness of the proposed method and its potential applications, which include indirect manipulation of micro‐objects.

This data is extracted from the Web of Science and reproduced under a licence from Thomson Reuters. You may not copy or re-distribute this data in whole or in part without the written consent of the Science business of Thomson Reuters.

Request URL: http://wlsprd.imperial.ac.uk:80/respub/WEB-INF/jsp/search-t4-html.jsp Request URI: /respub/WEB-INF/jsp/search-t4-html.jsp Query String: id=759&limit=5&page=2&respub-action=search.html Current Millis: 1620297569977 Current Time: Thu May 06 11:39:29 BST 2021