Shape Sensing Based on Longitudinal Strain Measurements Considering Elongation, Bending, and Twisting

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Modes, V.; Ortmaier,T.; Burgner-Kahrs, J.: Shape Sensing Based on Longitudinal Strain Measurements Considering Elongation, Bending, and Twisting. In: IEEE Sensors Journal 21 (2021), Nr. 5, S. 6712-6723. DOI: https://doi.org/10.1109/JSEN.2020.3043999

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To cite the version in the repository, please use this identifier: https://doi.org/10.15488/10387

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Sum total of downloads: 105




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Abstract: 
The inherent flexibility, the small dimensions as well as the curvilinear shape of continuum robots makes it challenging to precisely measure their shape. Optical fibers with Bragg gratings (FBGs) provide a powerful tool to reconstruct the centerline of continuum robots. We present a theoretical model to determine the shape of such a sensor array based on longitudinal strain measurements and incorporating bending, twisting, and elongation. To validate our approach, we conduct several simulations by calculating arbitrary shapes based on the Cosserat rod theory. Our algorithm showed a maximum mean relative shape deviation of 0.04%, although the sensor array was twisted up to 78°. Because we derive a closed-form solution for the strain curvature twist model, we also give analytical sensitivity values for the model, which can be used in the calculation of error propagation.
License of this version: Es gilt deutsches Urheberrecht. Das Dokument darf zum eigenen Gebrauch kostenfrei genutzt, aber nicht im Internet bereitgestellt oder an Außenstehende weitergegeben werden.
Document Type: article
Publishing status: acceptedVersion
Issue Date: 2020
Appears in Collections:Fakultät für Maschinenbau

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pos. country downloads
total perc.
1 image of flag of China China 54 51.43%
2 image of flag of Germany Germany 15 14.29%
3 image of flag of United States United States 8 7.62%
4 image of flag of No geo information available No geo information available 6 5.71%
5 image of flag of United Kingdom United Kingdom 4 3.81%
6 image of flag of Japan Japan 3 2.86%
7 image of flag of Italy Italy 3 2.86%
8 image of flag of Iran, Islamic Republic of Iran, Islamic Republic of 3 2.86%
9 image of flag of Hong Kong Hong Kong 3 2.86%
10 image of flag of Canada Canada 2 1.90%
    other countries 4 3.81%

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