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

    Dwyer G, Giataganas P, Pratt P, Hughes M, Yang G-Zet al., 2015,

    A Miniaturised Robotic Probe for Real-Time Intraoperative Fusion of Ultrasound and Endomicroscopy

    , IEEE International Conference on Robotics and Automation (ICRA), Publisher: IEEE COMPUTER SOC, Pages: 1196-1201, ISSN: 1050-4729
    Payne CJ, Gras G, Hughes M, Nathwani D, Yang G-Zet al., 2015,

    A Hand-Held Flexible Mechatronic Device for Arthroscopy

    , IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Publisher: IEEE, Pages: 817-823, ISSN: 2153-0858
    Liu J, Yang GZ, 2014,

    Robust speech recognition in reverberant environments by using an optimal synthetic room impulse response model

    , Speech Communication, Vol: 67, Pages: 65-77, ISSN: 1872-7182

    This paper presents a practical technique for Automatic speech recognition (ASR) in multiple reverberant environment selection. Multiple ASR models are trained with artificial synthetic room impulse responses (IRs), i.e. simulated room IRs, with different reverberation time (T60Models) and tested on real room IRs with varying T60Rooms. To apply our method, the biggest challenge is to choose a proper artificial room IR model for training ASR models. In this paper, a generalised statistical IR model with attenuated reverberation after an early reflection period, named attenuated IR model, has been adopted based on three time-domain statistical IR models. Its optimal values of the reverberation-attenuation factor and the early reflection period on the recognition rate have been searched and determined. Extensive testing has been performed over four real room IR sets (63 IRs in total) with variant T60Rooms and speaker microphone distances (SMDs). The optimised attenuated IR model had the best performance in terms of recognition rate over others. Specific considerations of the practical use of the method have been taken into account including: (i) the maximal training step of T60Model in order to get the minimal number of models with acceptable performance; (ii) the impact of selection errors on the ASR caused by the estimation error of T60Room; and (iii) the performance over SMD and direct-to-reverberation energy Ratio (DRR). It is shown that recognition rates of over 80∼∼90% are achieved in most cases. One important advantage of the method is that T60Room can be estimated either from reverberant sound directly ( Takeda et al., 2009, Falk and Chan, 2010 and Löllmann et al., 2010) or from an IR measured from any point of the room as it remains constant in the same room ( Kuttruff, 2000), thus it is particularly suited to mobile applications. Compared to many classical dereverberation methods, the proposed method is more suited to ASR tasks in multiple reverb

    Wisanuvej PW, Liu JL, Chen CMC, Yang GZYet al., 2014,

    Blind collision detection and obstacle characterisation using a compliant robotic arm

    , 2014 IEEE International Conference on Robotics and Automation (ICRA), Publisher: IEEE, ISSN: 1050-4729

    This paper presents a novel blind collision detection and material characterisation scheme for a compliant robotic arm. By the incorporation of a simple MEMS accelerometer at each joint, the robot is able to detect collision, identify the material of an obstacle, and create a map of the environment. Detailed hardware design is provided, illustrating its value for building a compact and economical robot platform. The proposed method does not require the additional use of vision sensor for mapping the environment, and hence is termed as `blind' collision detection and environment mapping. Based on the shock wave and vibration signals, the proposed algorithm is able to classify a range of materials encountered. Detailed laboratory evaluation was performed with controlled obstacle collision from different orientation and locations with varying force and materials. The proposed method has achieved 98% detection sensitivity while maintaining 77% specificity. Furthermore, by using sound feature extraction and machine learning techniques, the classifier produces an accuracy of 98% for classifying four different impact materials. In this paper, we also demonstrate its use for detailed environment mapping by using the proposed method.

    Seneci CA, Shang J, Leibrandt K, Vitiello V, Patel N, Darzi A, Teare J, Yang GZet al., 2014,

    Design and evaluation of a novel flexible robot for transluminal and endoluminal surgery

    , IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Pages: 1314-1321

    Precise and repetitive positional control of surgical robots is important to reduce time and risks of surgical procedures. These factors become particularly important when deploying the surgical system through a flexible path to areas with a tight workspace such as the stomach or oesophagus where high dexterity, flexibility, accuracy and stability are required. This paper presents a flexible access robot combining articulated joints and continuum flexible section for both transluminal and endoluminal surgeries. Kinematic model and control strategy for the flexible robot are described in the paper. The experiment simulating a transoral gastric procedure demonstrates great flexibility and dexterity of the device. The results show that good accuracy and repetitive control of the device are achieved, which demonstrate the potential application of the device for transluminal or endoluminal surgery.

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=6&respub-action=search.html Current Millis: 1561474641475 Current Time: Tue Jun 25 15:57:21 BST 2019