Real-Time Surface Shape Sensing for Soft and Flexible Structures Using Fiber Bragg Gratings

In this letter, we present a new soft and flexible sensor which can reconstruct its surface shape in real time. A single-core optical fiber with fiber Bragg gratings (FBGs) is capable of detecting sparse local strains at high bandwidth using wavelength-division multiplexing. The fiber was embedded i...

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Bibliographic Details
Published in:IEEE robotics and automation letters 2019-04, Vol.4 (2), p.1454-1461
Main Authors: Lun, Tian Le Tim, Wang, Kui, Ho, Justin D. L., Lee, Kit-Hang, Sze, Kam Yim, Kwok, Ka-Wai
Format: Article
Language:English
Subjects:
Bragg gratings
Design parameters
Elastomers
Error compensation
Fiber bragg gratings
Fiber gratings
Finite element method
Flexible components
flexible robots
Flexible structures
Machine learning
Mapping
Morphology
Noise reduction
Optical fibers
Real time
Robot sensing systems
Sensors
Shape
soft sensors and actuators
Strain
Substrates
Surface morphology
Surface reconstruction
surface shape sensing
Wave division multiplexing
Wavelength division multiplexing
Wiring
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Summary:In this letter, we present a new soft and flexible sensor which can reconstruct its surface shape in real time. A single-core optical fiber with fiber Bragg gratings (FBGs) is capable of detecting sparse local strains at high bandwidth using wavelength-division multiplexing. The fiber was embedded into an elastomeric substrate to reconstruct its global surface morphology. Finite element analysis was used to determine the design parameters, and also to validate the unique mapping from sparse strain measurements to the continuum shape of the sensor. To simplify the fabrication and error compensation process without precise/prior knowledge of the FBG locations in the sensor, machine learning-based modeling was applied. This enables real time, robust and reliable shape reconstruction. It is demonstrated to outperform various applications of electronics-based sensors, which require sophisticated electrode wiring and noise reduction. Experiments were performed to evaluate the sensing accuracy and repeatability.
ISSN:2377-3766
2377-3766
DOI:10.1109/LRA.2019.2893036