In this section
We use perceptual methods, AI, and frugal robotics innovation to deliver transformative diagnostic and treatment solutions.
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.
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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
@article{Zhou:2024:10.3390/s24103156,
author = {Zhou, Z and Yang, J and Runciman, M and Avery, J and Sun, Z and Mylonas, G},
doi = {10.3390/s24103156},
journal = {Sensors},
title = {A tension sensor array for cable-driven surgical robots},
url = {http://dx.doi.org/10.3390/s24103156},
volume = {24},
year = {2024}
}
TY - JOUR
AB - Tendon–sheath structures are commonly utilized to drive surgical robots due to their compact size, flexibility, and straightforward controllability. However, long-distance cable tension estimation poses a significant challenge due to its frictional characteristics affected by complicated factors. This paper proposes a miniature tension sensor array for an endoscopic cable-driven parallel robot, aiming to integrate sensors into the distal end of long and flexible surgical instruments to sense cable tension and alleviate friction between the tendon and sheath. The sensor array, mounted at the distal end of the robot, boasts the advantages of a small size (16 mm outer diameter) and reduced frictional impact. A force compensation strategy was presented and verified on a platform with a single cable and subsequently implemented on the robot. The robot demonstrated good performance in a series of palpation tests, exhibiting a 0.173 N average error in force estimation and a 0.213 N root-mean-square error. In blind tests, all ten participants were able to differentiate between silicone pads with varying hardness through force feedback provided by a haptic device.
AU - Zhou,Z
AU - Yang,J
AU - Runciman,M
AU - Avery,J
AU - Sun,Z
AU - Mylonas,G
DO - 10.3390/s24103156
PY - 2024///
SN - 1424-8220
TI - A tension sensor array for cable-driven surgical robots
T2 - Sensors
UR - http://dx.doi.org/10.3390/s24103156
UR - http://hdl.handle.net/10044/1/112052
VL - 24
ER -
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