In this section
The MIM Lab develops robotic and mechatronics surgical systems for a variety of procedures.
Twitter/X: @MIMLab_Robotics
Youtube: Mechatronics in Medicine Lab
The Mechatronics in Medicine Laboratory develops robotic and mechatronics surgical systems for a variety of procedures including neuro, cardiovascular, orthopaedic surgeries, and colonoscopies. Examples include bio-inspired catheters that can navigate along complex paths within the brain (such as EDEN2020), soft robots to explore endoluminal anatomies (such as the colon), and virtual reality solutions to support surgeons during knee replacement surgeries.
...
......
Mr Ayhan Aktas
Casual - Student demonstrator - lower rate
Dr Daniel Bautista Salinas
Research Associate
Dr Kaiwen Chen
Research Associate
Mr Zejian Cui
Research Postgraduate
Mr Connor Daly
Research Postgraduate
Emeritus Professor Brian L Davies FREng
Emeritus Professor
Mr Zhaoyang Jacopo Hu
Research Postgraduate
Dr Hisham M Iqbal
Research Associate
Mr Alex Ranne
Research Postgraduate
Professor Ferdinando M Rodriguez y Baena
Co-Director of Hamlyn Centre, Professor of Medical Robotics
Dr Jialei Shi
Research Associate
Mr Spyridon Souipas
Casual - Other work
Ms Emilia Zari
Research Postgraduate
@article{Liu:2016:10.1109/LRA.2016.2528292,
author = {Liu, F and Garriga-Casanovas, A and Secoli, R and Baena, FRY},
doi = {10.1109/LRA.2016.2528292},
journal = {IEEE Robotics and Automation Letters},
pages = {601--608},
title = {Fast and adaptive fractal tree-based path planning for programmable bevel tip steerable needles},
url = {http://dx.doi.org/10.1109/LRA.2016.2528292},
volume = {1},
year = {2016}
}
TY - JOUR
AB - Steerable needles are a promising technology for minimally invasive surgery, as they can provide access to difficult to reach locations while avoiding delicate anatomical regions. However, due to the unpredictable tissue deformation associated with needle insertion and the complexity of many surgical scenarios, a real-time path planning algorithm with high update frequency would be advantageous. Real-time path planning for nonholonomic systems is commonly used in a broad variety of fields, ranging from aerospace to submarine navigation. In this letter, we propose to take advantage of the architecture of graphics processing units (GPUs) to apply fractal theory and thus parallelize real-time path planning computation. This novel approach, termed adaptive fractal trees (AFT), allows for the creation of a database of paths covering the entire domain, which are dense, invariant, procedurally produced, adaptable in size, and present a recursive structure. The generated cache of paths can in turn be analyzed in parallel to determine the most suitable path in a fraction of a second. The ability to cope with nonholonomic constraints, as well as constraints in the space of states of any complexity or number, is intrinsic to the AFT approach, rendering it highly versatile. Three-dimensional (3-D) simulations applied to needle steering in neurosurgery show that our approach can successfully compute paths in real-time, enabling complex brain navigation.
AU - Liu,F
AU - Garriga-Casanovas,A
AU - Secoli,R
AU - Baena,FRY
DO - 10.1109/LRA.2016.2528292
EP - 608
PY - 2016///
SN - 2377-3766
SP - 601
TI - Fast and adaptive fractal tree-based path planning for programmable bevel tip steerable needles
T2 - IEEE Robotics and Automation Letters
UR - http://dx.doi.org/10.1109/LRA.2016.2528292
UR - http://hdl.handle.net/10044/1/33050
VL - 1
ER -
General enquiries
hamlyn@imperial.ac.uk
Facility enquiries
hamlyn.facility@imperial.ac.uk
The Hamlyn Centre
Bessemer Building
South Kensington Campus
Imperial College
London, SW7 2AZ
Map location
