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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

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

Citation

BibTex format

@inproceedings{Zhang:2014,
author = {Zhang, L and Lee, S-L and Yang, G-Z and Mylonas, GP},
pages = {3496--3502},
publisher = {IEEE},
title = {Semi-autonomous navigation for robot assisted tele-echography using generalized shape models and co-registered RGB-D cameras},
url = {http://hdl.handle.net/10044/1/26984},
year = {2014}
}

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RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - — This paper proposes a semi-autonomous navigatedmaster-slave system, for robot assisted remote echography forearly trauma assessment. Two RGB-D sensors are used tocapture real-time 3D information of the scene at the slave sidewhere the patient is located. A 3D statistical shape model isbuilt and used to generate a customized patient model basedon the point cloud generated by the RGB-D sensors. Thecustomized patient model can be updated and adaptively fittedto the patient. The model is also used to generate a trajectoryto navigate a KUKA robotic arm and safely conduct theultrasound examination. Extensive validation of the proposedsystem shows promising results in terms of accuracy androbustness.
AU  - Zhang,L
AU  - Lee,S-L
AU  - Yang,G-Z
AU  - Mylonas,GP
EP  - 3502
PB  - IEEE
PY  - 2014///
SP  - 3496
TI  - Semi-autonomous navigation for robot assisted tele-echography using generalized shape models and co-registered RGB-D cameras
UR  - http://hdl.handle.net/10044/1/26984
ER  -

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