Dietsch, S;
McDonald-Bowyer, A;
Dimitrakakis, E;
Coote, JM;
Lindenroth, L;
Stilli, A;
Stoyanov, D;
(2022)
Localization of Interaction using Fibre-Optic Shape Sensing in Soft-Robotic Surgery Tools.
In:
IEEE International Conference on Intelligent Robots and Systems.
(pp. pp. 8057-8063).
IEEE
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Abstract
Minimally invasive surgery requires real-time tool tracking to guide the surgeon where depth perception and visual occlusion present navigational challenges. Although vision-based and external sensor-based tracking methods exist, fibre-optic sensing can overcome their limitations as they can be integrated directly into the device, are biocompatible, small, robust and geometrically versatile. In this paper, we integrate a fibre Bragg grating-based shape sensor into a soft robotic device. The soft robot is the pneumatically attachable flexible (PAF) rail designed to act as a soft interface between manipulation tools and intra-operative imaging devices. We demonstrate that the shape sensing fibre can detect the location of the tools paired with the PAF rail, by exploiting the change in curvature sensed by the fibre when a strain is applied to it. We then validate this with a series of grasping tasks and continuous US swipes, using the system to detect in real-time the location of the tools interacting with the PAF rail. The overall location-sensing accuracy of the system is 64.6%, with a margin of error between predicted location and actual location of 3.75 mm.
| Type: | Proceedings paper |
|---|---|
| Title: | Localization of Interaction using Fibre-Optic Shape Sensing in Soft-Robotic Surgery Tools |
| Event: | 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) |
| Dates: | 23 Oct 2022 - 27 Oct 2022 |
| ISBN-13: | 9781665479271 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/IROS47612.2022.9981765 |
| Publisher version: | https://doi.org/10.1109/IROS47612.2022.9981765 |
| Language: | English |
| Additional information: | This research was funded in whole, or in part, by the Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS) [203145/Z/16/Z]; the Engineering and Physical Sciences Research Council (EPSRC) [EP/P027938/1, EP/R004080/1, EP/P012841/1]; and the Royal Academy of Engineering Chair in Emerging Technologies Scheme [CiET1819/2/36]. For the purpose of open access, the author has applied a CC BY public copyright licence to any author accepted manuscript version arising from this submission. This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Med Phys and Biomedical Eng |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10164279 |
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