Calibration of Concentric Tube Continuum Robots: Automatic Alignment of Precurved Elastic Tubes

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Modes, V.; Burgner-Kahrs, J.: Calibration of Concentric Tube Continuum Robots: Automatic Alignment of Precurved Elastic Tubes. In: IEEE Robotics and Automation Letters 5 (2020), Nr. 1, S. 103-110. DOI: https://doi.org/10.1109/LRA.2019.2946060

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To cite the version in the repository, please use this identifier: https://doi.org/10.15488/10388

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Sum total of downloads: 86




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Abstract: 
Joint level calibration is an integral part of robotics as it directly influences the achievable accuracy. As opposed to serial robotic arms, continuum robots are not composed of any rigid links or joints, but of elastic materials that undergo bending and torsion. The jointless composition requires dedicated calibration procedures. In this letter, we introduce an automatic method for aligning precurved elastic tubes for joint level calibration of concentric tube continuum robots. The robot tip is equipped with a sensor in order to track its position during calibration such that subsequent data processing can extract the rotational zero position automatically. While we present a general framework independent of the utilized sensor technology, we evaluate our approach using three different sensing methodologies, i.e. magnetic, inductive, and electromagnetic. Furthermore, we advise on properties for appropriate sensors. Our experimental results show, that the rotational home position can be found reproducibly with a minimal dispersion of 0.011°.
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: 2019
Appears in Collections:Fakultät für Maschinenbau

distribution of downloads over the selected time period:

downloads by country:

pos. country downloads
total perc.
1 image of flag of Germany Germany 31 36.05%
2 image of flag of Russian Federation Russian Federation 9 10.47%
3 image of flag of China China 8 9.30%
4 image of flag of United States United States 7 8.14%
5 image of flag of Czech Republic Czech Republic 7 8.14%
6 image of flag of France France 6 6.98%
7 image of flag of No geo information available No geo information available 2 2.33%
8 image of flag of Sweden Sweden 2 2.33%
9 image of flag of Hong Kong Hong Kong 2 2.33%
10 image of flag of Canada Canada 2 2.33%
    other countries 10 11.63%

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