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Development of an Angular Sensor for Shape Sensing of Medical Robots

Iafolla, Lorenzo. Development of an Angular Sensor for Shape Sensing of Medical Robots. 2021, Doctoral Thesis, University of Basel, Faculty of Medicine.

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Official URL: https://edoc.unibas.ch/84832/

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Abstract

Tracking is a crucial need to control an endoscopic surgical tool accurately. Unfortunately, widely used solutions based on optical trackers cannot work in this case because the line-of-sight is blocked once the endoscope is inside the patient's body. Other promising techniques are fiber Bragg grating, electromagnetic trackers, and intra-operative imaging-based shape sensing, but these still show some issues and further investigations are required. For this reason, this work aims to develop new solutions to track the pose and to sense the shape of robotic articulated endoscopes for minimally invasive surgery.
This thesis lays down the foundations for a new tracking and shape sensing method based on a novel, miniaturizable, angular measuring system, called ASTRAS (Angular Sensor for TRAcking Systems). This is a shadow sensor able to generate a shadow image with a one-to-one correspondence to an input angle. The tracking method involves measuring the joints bending angles of the articulated endoscope by placing one ASTRAS in each of them. Subsequently, the position, the orientation, and the shape of the endoscope can be calculated from these angular measurements.
As ASTRAS is a novel concept, it was necessary to define and test the methods to achieve the required accuracy. Pursuing this, we developed 1) the measurement principle of the measuring system, 2) the measurement methods (i.e., image processing techniques) to determine the input angle from the shadow image, 3) the methods to extend the angular range up to 360 degrees (ASTRAS360), 4) the machine learning-based methods to compensate for systematic errors (e.g., linearity error or imperfections of the mechanics), 5) techniques based on FPGA electronic devices to acquire and process data in real-time. For each of these developments, we performed experiments for validation. For example, we demonstrated that ASTRAS is very precise (5 arcsec) even when using a miniaturized image sensor (e.g., NanEye, 1x1x0.5 mm^3).
The result of this work is the know-how to design new versions of ASTRAS specifically for minimally invasive robotics. In particular, the miniaturized version of ASTRAS has the potential to outperform the existing angular measuring systems (i.e., rotary encoder). It will provide an alternative solution to the existing tracking and shape sensing technologies.
Furthermore, ASTRAS is prone to further developments, such as being used to measure over two degrees of freedom (i.e., two angles). This would enable further applications in medical robotics, such as tracking of continuum (non-articulated) robots.
Advisors:Cattin, Philippe Claude
Committee Members:Rauter, Georg and Ciuti, Gastone
Faculties and Departments:03 Faculty of Medicine > Departement Biomedical Engineering > Imaging and Computational Modelling > Center for medical Image Analysis & Navigation (Cattin)
UniBasel Contributors:Cattin, Philippe Claude and Rauter, Georg
Item Type:Thesis
Thesis Subtype:Doctoral Thesis
Thesis no:14419
Thesis status:Complete
Number of Pages:133
Language:English
Identification Number:
  • urn: urn:nbn:ch:bel-bau-diss144197
edoc DOI:
Last Modified:10 Nov 2021 05:30
Deposited On:09 Nov 2021 11:58

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