In this section

Human-Centred Automation, Robotics and Monitoring

We use perceptual methods, AI, and frugal robotics innovation to deliver transformative diagnostic and treatment solutions.

Head of Group

Dr George Mylonas

B415B Bessemer Building
South Kensington Campus

+44 (0)20 3312 5145

YouTube ⇒ HARMS Lab

What we do

The HARMS lab leverages perceptually enabled methodologies, artificial intelligence, and frugal innovation in robotics (such as soft surgical robots) to deliver transformative solutions for diagnosis and treatment. Our research is driven by both problem-solving and curiosity, aiming to build a comprehensive understanding of the actions, interactions, and reactions occurring in the operating room. We focus on using robotic technologies to facilitate procedures that are not yet widely adopted, particularly in endoluminal surgery, such as advanced treatments for gastrointestinal cancer.

Meet the team

Mr Amirhosein Alian
Research Postgraduate

Dr James P Avery
Honorary Lecturer

Mr Junhong Chen
Research Postgraduate

Mr Kaizhong Deng
Research Postgraduate

Mr Hanqi LOU
Research Postgraduate

Dr George Mylonas BEng, MSc, DIC, PhD
Senior Lecturer in Robotics and Technology in Cancer

Dr Adrian Rubio Solis
Research Associate in Sensing and Machine Learning

Dr Jianlin Yang
Research Associate

Mr Zhangxi Zhou
Research Postgraduate

Citation

BibTex format

@inproceedings{Avery:2019:10.1109/ICRA.2019.8793862,
author = {Avery, J and Runciman, M and Darzi, A and Mylonas, GP},
doi = {10.1109/ICRA.2019.8793862},
pages = {9066--9072},
publisher = {IEEE},
title = {Shape sensing of variable stiffness soft robots using electrical impedance tomography},
url = {http://dx.doi.org/10.1109/ICRA.2019.8793862},
year = {2019}
}

Download

RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - Soft robotic systems offer benefits over traditional rigid systems through reduced contact trauma with soft tissues and by enabling access through tortuous paths in minimally invasive surgery. However, the inherent deformability of soft robots places both a greater onus on accurate modelling of their shape, and greater challenges in realising intraoperative shape sensing. Herein we present a proprioceptive (self-sensing) soft actuator, with an electrically conductive working fluid. Electrical impedance measurements from up to six electrodes enabled tomographic reconstructions using Electrical Impedance Tomography (EIT). A new Frequency Division Multiplexed (FDM) EIT system was developed capable of measurements of 66 dB SNR with 20 ms temporal resolution. The concept was examined in two two-degree-of-freedom designs: a hydraulic hinged actuator and a pneumatic finger actuator with hydraulic beams. Both cases demonstrated that impedance measurements could be used to infer shape changes, and EIT images reconstructed during actuation showed distinct patterns with respect to each degree of freedom (DOF). Whilst there was some mechanical hysteresis observed, the repeatability of the measurements and resultant images was high. The results show the potential of FDM-EIT as a low-cost, low profile shape sensor in soft robots.
AU  - Avery,J
AU  - Runciman,M
AU  - Darzi,A
AU  - Mylonas,GP
DO  - 10.1109/ICRA.2019.8793862
EP  - 9072
PB  - IEEE
PY  - 2019///
SN  - 1050-4729
SP  - 9066
TI  - Shape sensing of variable stiffness soft robots using electrical impedance tomography
UR  - http://dx.doi.org/10.1109/ICRA.2019.8793862
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000494942306095&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - https://ieeexplore.ieee.org/document/8793862
UR  - http://hdl.handle.net/10044/1/79679
ER  -