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:



  • Showing results for:
  • Reset all filters

Search results

  • Journal article
    Zhang D, Chen J, Li W, Bautista Salinas D, Yang G-Zet al., 2020,

    A microsurgical robot research platform for robot-assisted microsurgery research and training.

    , Int J Comput Assist Radiol Surg, Vol: 15, Pages: 15-25

    PURPOSE: Ocular surgery, ear, nose and throat surgery and neurosurgery are typical types of microsurgery. A versatile training platform can assist microsurgical skills development and accelerate the uptake of robot-assisted microsurgery (RAMS). However, the currently available platforms are mainly designed for macro-scale minimally invasive surgery. There is a need to develop a dedicated microsurgical robot research platform for both research and clinical training. METHODS: A microsurgical robot research platform (MRRP) is introduced in this paper. The hardware system includes a slave robot with bimanual manipulators, two master controllers and a vision system. It is flexible to support multiple microsurgical tools. The software architecture is developed based on the robot operating system, which is extensible at high-level control. The selection of master-slave mapping strategy was explored, while comparisons were made between different interfaces. RESULTS: Experimental verification was conducted based on two microsurgical tasks for training evaluation, i.e. trajectory following and targeting. User study results indicated that the proposed hybrid interface is more effective than the traditional approach in terms of frequency of clutching, task completion time and ease of control. CONCLUSION: Results indicated that the MRRP can be utilized for microsurgical skills training, since motion kinematic data and vision data can provide objective means of verification and scoring. The proposed system can further be used for verifying high-level control algorithms and task automation for RAMS research.

  • Journal article
    Zhang H, Khushi V, Yang G-Z, 2019,

    Line scanning, fiber bundle fluorescence HiLo endomicroscopy with confocal slit detection

    , Journal of Biomedical Optics, Vol: 24, ISSN: 1083-3668

    Fiber bundle fluorescence endomicroscopy is an effective method for in vivo imaging of biological tissue samples. Line-scanning confocal laser endomicroscopy realizes confocal imaging at a much higher frame rate compared to the point scanning system, but with reduced optical sectioning. To address this problem, we describe a fiber bundle endomicroscopy system that utilizes the HiLo technique to enhance the optical sectioning while still maintaining high image acquisition rates. Confocal HiLo endomicroscopy is achieved by synchronizing the scanning hybrid-illumination laser line with the rolling shutter of a CMOS camera. An evident improvement of axial sectioning is achieved as compared to the line-scanning confocal endomicroscopy without the HiLo technique. Comparisons are also made with epifluorescence endomicroscopy with and without HiLo. The optical sectioning enhancement is demonstrated on lens tissue as well as porcine kidney tissue

  • Journal article
    Zhang D, Cursi F, Yang G-Z, 2019,

    WSRender: A Workspace Analysis and Visualization Toolbox for Robotic Manipulator Design and Verification

    , IEEE ROBOTICS AND AUTOMATION LETTERS, Vol: 4, Pages: 3836-3843, ISSN: 2377-3766
  • Journal article
    Guo Y, Deligianni F, Gu X, Yang G-Zet al., 2019,

    3-D Canonical pose estimation and abnormal gait recognition with a single RGB-D camera

    , IEEE Robotics and Automation Letters, Vol: 4, Pages: 3617-3624, ISSN: 2377-3766

    Assistive robots play an important role in improvingthe quality of life of patients at home. Among all the monitoringtasks, gait disorders are prevalent in elderly and people with neurological conditions and this increases the risk of fall. Therefore,the development of mobile systems for gait monitoring at home innormal living conditions is important. Here, we present a mobilesystem that is able to track humans and analyze their gait incanonical coordinates based on a single RGB-D camera. First,view-invariant three-dimensional (3-D) lower limb pose estimationis achieved by fusing information from depth images along with2-D joints derived in RGB images. Next, both the 6-D camerapose and the 3-D lower limb skeleton are real-time tracked in acanonical coordinate system based on simultaneously localizationand mapping (SLAM). A mask-based strategy is exploited to improve the re-localization of the SLAM in dynamic environments.Abnormal gait is detected by using the support vector machine andthe bidirectional long-short term memory network with respect toa set of extracted gait features. To evaluate the robustness of thesystem, we collected multi-cameras, ground truth data from 16healthy volunteers performing 6 gait patterns that mimic commongait abnormalities. The experiment results demonstrate that ourproposed system can achieve good lower limb pose estimation andsuperior recognition accuracy compared to previous abnormal gaitdetection methods.

  • Journal article
    Barbot A, Tan H, Power M, Seichepine F, Yang G-Zet al., 2019,

    Floating magnetic microrobots for fiber functionalization

    , SCIENCE ROBOTICS, Vol: 4, ISSN: 2470-9476

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: Request URI: /respub/WEB-INF/jsp/search-t4-html.jsp Query String: id=759&limit=5&page=4&respub-action=search.html Current Millis: 1597398324824 Current Time: Fri Aug 14 10:45:24 BST 2020