3D shape sensing with multicore optical fibers

Standard

3D shape sensing with multicore optical fibers : Transformation Matrices Versus Frenet-Serret Equations for Real-Time Application. / Paloschi, Davide; Bronnikov, Kirill A.; Korganbayev, Sanzhar et al.

In: IEEE Sensors Journal, Vol. 21, No. 4, 9233257, 15.02.2021, p. 4599-4609.

Research output: Contribution to journal › Article › peer-review

Harvard

Paloschi, D, Bronnikov, KA, Korganbayev, S, Wolf, A, Dostovalov, A & Saccomandi, P 2021, '3D shape sensing with multicore optical fibers: Transformation Matrices Versus Frenet-Serret Equations for Real-Time Application', IEEE Sensors Journal, vol. 21, no. 4, 9233257, pp. 4599-4609. https://doi.org/10.1109/JSEN.2020.3032480

APA

Paloschi, D., Bronnikov, K. A., Korganbayev, S., Wolf, A., Dostovalov, A., & Saccomandi, P. (2021). 3D shape sensing with multicore optical fibers: Transformation Matrices Versus Frenet-Serret Equations for Real-Time Application. IEEE Sensors Journal, 21(4), 4599-4609. [9233257]. https://doi.org/10.1109/JSEN.2020.3032480

Vancouver

Paloschi D, Bronnikov KA, Korganbayev S, Wolf A, Dostovalov A, Saccomandi P. 3D shape sensing with multicore optical fibers: Transformation Matrices Versus Frenet-Serret Equations for Real-Time Application. IEEE Sensors Journal. 2021 Feb 15;21(4):4599-4609. 9233257. doi: 10.1109/JSEN.2020.3032480

Author

Paloschi, Davide ; Bronnikov, Kirill A. ; Korganbayev, Sanzhar et al. / 3D shape sensing with multicore optical fibers : Transformation Matrices Versus Frenet-Serret Equations for Real-Time Application. In: IEEE Sensors Journal. 2021 ; Vol. 21, No. 4. pp. 4599-4609.

BibTeX

@article{50cef9263761486f8b3be79f5fd0f950,

title = "3D shape sensing with multicore optical fibers: Transformation Matrices Versus Frenet-Serret Equations for Real-Time Application",

abstract = "This paper presents the characterization of an algorithm aimed at performing accurate fiber optic-based shape sensing. The measurement of the shape relies on the evaluation of the strains applied to an optic fiber in order to identify relevant spatial parameters, such as the curvature radii and bending direction, which define its shape. The measurement system is based on a 7-core multicore fiber, containing up to 9 triplets of fiber Bragg grating sensors (FBGs) organized around a central core used as reference. The proposed study aims at comparing the widely used Frenet-Serret equations with an algorithm based on the homogeneous transformation matrices that are normally used in robotics to express the position of a point in different frames, i.e. from local to global coordinates. The numerical results of the performed experiments (with different multicore fibers and setups) extensively prove the superiority of the alternative method over the Frenet-Serret equations in terms of finding a trade-off between accuracy and execution time.",

keywords = "Fiber Bragg grating, Frenet-Serret, Homogeneous transformation matrix, Multicore optical fiber, Performance, Shape sensing, Three-dimensional, performance, three-dimensional, multicore optical fiber, homogeneous transformation matrix, fiber Bragg grating",

author = "Davide Paloschi and Bronnikov, {Kirill A.} and Sanzhar Korganbayev and Alexey Wolf and Alexander Dostovalov and Paola Saccomandi",

year = "2021",

month = feb,

day = "15",

doi = "10.1109/JSEN.2020.3032480",

language = "English",

volume = "21",

pages = "4599--4609",

journal = "IEEE Sensors Journal",

issn = "1530-437X",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

number = "4",

}

RIS

TY - JOUR

T1 - 3D shape sensing with multicore optical fibers

T2 - Transformation Matrices Versus Frenet-Serret Equations for Real-Time Application

AU - Paloschi, Davide

AU - Bronnikov, Kirill A.

AU - Korganbayev, Sanzhar

AU - Wolf, Alexey

AU - Dostovalov, Alexander

AU - Saccomandi, Paola

PY - 2021/2/15

Y1 - 2021/2/15

N2 - This paper presents the characterization of an algorithm aimed at performing accurate fiber optic-based shape sensing. The measurement of the shape relies on the evaluation of the strains applied to an optic fiber in order to identify relevant spatial parameters, such as the curvature radii and bending direction, which define its shape. The measurement system is based on a 7-core multicore fiber, containing up to 9 triplets of fiber Bragg grating sensors (FBGs) organized around a central core used as reference. The proposed study aims at comparing the widely used Frenet-Serret equations with an algorithm based on the homogeneous transformation matrices that are normally used in robotics to express the position of a point in different frames, i.e. from local to global coordinates. The numerical results of the performed experiments (with different multicore fibers and setups) extensively prove the superiority of the alternative method over the Frenet-Serret equations in terms of finding a trade-off between accuracy and execution time.

AB - This paper presents the characterization of an algorithm aimed at performing accurate fiber optic-based shape sensing. The measurement of the shape relies on the evaluation of the strains applied to an optic fiber in order to identify relevant spatial parameters, such as the curvature radii and bending direction, which define its shape. The measurement system is based on a 7-core multicore fiber, containing up to 9 triplets of fiber Bragg grating sensors (FBGs) organized around a central core used as reference. The proposed study aims at comparing the widely used Frenet-Serret equations with an algorithm based on the homogeneous transformation matrices that are normally used in robotics to express the position of a point in different frames, i.e. from local to global coordinates. The numerical results of the performed experiments (with different multicore fibers and setups) extensively prove the superiority of the alternative method over the Frenet-Serret equations in terms of finding a trade-off between accuracy and execution time.

KW - Fiber Bragg grating

KW - Frenet-Serret

KW - Homogeneous transformation matrix

KW - Multicore optical fiber

KW - Performance

KW - Shape sensing

KW - Three-dimensional

KW - performance

KW - three-dimensional

KW - multicore optical fiber

KW - homogeneous transformation matrix

KW - fiber Bragg grating

UR - http://www.scopus.com/inward/record.url?scp=85096446072&partnerID=8YFLogxK

U2 - 10.1109/JSEN.2020.3032480

DO - 10.1109/JSEN.2020.3032480

M3 - Article

AN - SCOPUS:85096446072

VL - 21

SP - 4599

EP - 4609

JO - IEEE Sensors Journal

JF - IEEE Sensors Journal

SN - 1530-437X

IS - 4

M1 - 9233257

ER -

ID: 26082336