Designing patient specific magnetically actuated tentacle robots for minimally invasive surgery
Lead Research Organisation:
University of Leeds
Department Name: Electronic and Electrical Engineering
Abstract
The aim of the PhD is to establish a system to design and build patient specific millimetre scale magnetically actuated tentacles for minimally invasive surgical interventions. Throughout the project and in pursuit of this aim I expect to produce output in the form of published material.
In order to achieve these parallel goals I will need a thorough understanding of the underlying science involved in soft robotic design and manipulation and, in particular, my chosen method of analysis. The understanding and presentation of (in the form of publications) these underlying sciences can be considered to represent the objectives of the project;
These subject categories can be broadly summarised into;
a) traditional (hard) robotic modelling
b) continuum mechanics; elastic material behaviour is needed to understand and model soft robots
c) the Finite Element Method; the numerical method via which I can understand the response behaviour of those soft robots
d) Machine Learning and Artificial Neural Networks; many commentators consider this the future of soft robotic modelling and it is important that we (and I) are at the forefront of this development
e) data harvesting, in particular, image processing; machines can only learn from data and, in order that my plans can work, I need to be proficient at data gathering, from simulation, from images and from any other methods that may become available.
In order to achieve these parallel goals I will need a thorough understanding of the underlying science involved in soft robotic design and manipulation and, in particular, my chosen method of analysis. The understanding and presentation of (in the form of publications) these underlying sciences can be considered to represent the objectives of the project;
These subject categories can be broadly summarised into;
a) traditional (hard) robotic modelling
b) continuum mechanics; elastic material behaviour is needed to understand and model soft robots
c) the Finite Element Method; the numerical method via which I can understand the response behaviour of those soft robots
d) Machine Learning and Artificial Neural Networks; many commentators consider this the future of soft robotic modelling and it is important that we (and I) are at the forefront of this development
e) data harvesting, in particular, image processing; machines can only learn from data and, in order that my plans can work, I need to be proficient at data gathering, from simulation, from images and from any other methods that may become available.
