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 = {Wisanuvej, PW and Liu, JL and Chen, CMC and Yang, GZY},
doi = {10.1109/ICRA.2014.6907170},
publisher = {IEEE},
title = {Blind collision detection and obstacle characterisation using a compliant robotic arm},
url = {},
year = {2014}

RIS format (EndNote, RefMan)

AB - 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.
AU - Wisanuvej,PW
AU - Liu,JL
AU - Chen,CMC
AU - Yang,GZY
DO - 10.1109/ICRA.2014.6907170
PY - 2014///
SN - 1050-4729
TI - Blind collision detection and obstacle characterisation using a compliant robotic arm
UR -
UR -
ER -