In this section
Soft and flexible robotic systems for affordable healthcare.
Our research investigates fundamental aspects of control of soft and flexible robots for surgery. These include harnessing the intrinsic compliance of soft robots, rejecting disturbances that characterise the surgical environment, and complying with stringent safety requirements. Our ambition is to provide affordable robotic solutions for a range of surgical applications, including endoscopy, percutaneous intervention, and multi-handed surgery.
Robotics for healthcare is one of the fastest growing segments in the global robotics market. However, conventional surgical robots are unaffordable in low-resource settings. Harnessing the potential of soft and flexible robots can contribute to making surgery safter, more accurate, and more accessible in low-middle income countries. These are pressing needs due to the aging population, and to the growing workforce crisis in the healthcare market.
Our work aims to improve accuracy, reduce the risk of injury, and reduce discomfort in percutaneous interventions such as biopsy, in diagnostic and interventional endoscopy, and in multi-handed surgery.
Dr Enrico Franco
Lecturer
@article{Franco:2016:10.3389/frobt.2016.00048,
author = {Franco, E},
doi = {10.3389/frobt.2016.00048},
journal = {Frontiers in Robotics and AI},
title = {Combined Adaptive and Predictive Control for a Teleoperation System with Force Disturbance and Input Delay},
url = {http://dx.doi.org/10.3389/frobt.2016.00048},
volume = {3},
year = {2016}
}
TY - JOUR
AB - This work presents a new discrete-time adaptive-predictive control algorithm for a system with force disturbance and input delay. This scenario is representative of a mechatronic device for percutaneous intervention with pneumatic actuation and long supply lines which is controlled remotely in the presence of an unknown external force resulting from needle-tissue interaction or gravity. The ultimate goal of this research is the robotic-assisted percutaneous intervention of the liver under Magnetic Resonance Imaging (MRI) guidance. Since the control algorithm is intended for a digital microcontroller, it is presented in the discrete-time form. The controller design is illustrated for a 1 degree-of-freedom system and is conducted with a modular approach combining position control, adaptive disturbance compensation, and predictive control. The controller stability is analyzed and the effect of the input delay and of the tuning parameters is discussed. The controller performance is assessed with simulations considering a disturbance representative of needle insertion forces. The results indicate that the adaptive-predictive controller is effective in the presence of a variable disturbance and of a known or variable input delay.
AU - Franco,E
DO - 10.3389/frobt.2016.00048
PY - 2016///
SN - 2296-9144
TI - Combined Adaptive and Predictive Control for a Teleoperation System with Force Disturbance and Input Delay
T2 - Frontiers in Robotics and AI
UR - http://dx.doi.org/10.3389/frobt.2016.00048
UR - http://hdl.handle.net/10044/1/37588
VL - 3
ER -
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