4.7 Article

Large Curvature Bending Measurable Fiber-Optic Neurons for Multi-Joint Bending Perception

Journal

JOURNAL OF LIGHTWAVE TECHNOLOGY
Volume 41, Issue 17, Pages 5780-5787

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JLT.2023.3267468

Keywords

Bending sensor; large curvature; dexterous robotic hand; fiber bragg grating; optical fiber sensor

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In recent years, dexterous robotic hands have become indispensable in intelligent equipment. The use of bionic neurons that provide finger motion perception improves joint control accuracy. By utilizing series- and parallel-integrated inner cladding fiber Bragg gratings (ICFBG) as bionic neurons, the proposed fiber-optic neurons (FON) can achieve multi-joint bending perception in a robotic finger. The FONs are insensitive to temperature and axial strain and can potentially be utilized in robotic gesture recognition and control systems.
In recent years, dexterous robotic hands have become an indispensable part of intelligent equipment. The introduction of bionic neurons that provide finger motion perception will improve the accuracy of joint control. Here, series- and parallel-integrated inner cladding fiber Bragg gratings (ICFBG) act as bionic neurons to realize multi-joint bending perception in a robotic finger by measuring the reflective intensity changes of the ICFBGs. The fiber-optic neurons (FON) were fabricated using femtosecond laser point-by-point technology in the inner cladding of bend-insensitive single-mode fiber (BIF). The proposed FONs can measure large curvature bending up to 250 m(-1), with a bending sensitivity of & SIM;0.07 dB/m(-1) and a measuring resolution of 0.4 m(-1). Additionally, vector bending sensing can be achieved using the two pairs of ICFBGs that are orthogonally distributed to each other. The FONs are insensitive to temperature and axial strain. Furthermore, the proposed FONs were fixed to the knuckles of a robotic finger for multi-joint bending perception. The results show that FONs can potentially be used in robotic gesture recognition and control systems.

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