The secret role of undesired physical effects in accurate shape sensing with eccentric FBGs

• URL: http://arxiv.org/abs/2210.16316v1
• Date: Fri, 28 Oct 2022 09:07:08 GMT
• Title: The secret role of undesired physical effects in accurate shape sensing with eccentric FBGs
• Authors: Samaneh Manavi Roodsari, Sara Freund, Martin Angelmahr, Georg Rauter, Azhar Zam, Wolfgang Schade, and Philippe C. Cattin
• Abstract summary: Eccentric fiber Bragg gratings (FBG) are cheap and easy-to-fabricate shape sensors that are often interrogated with simple setups. Here, we present a novel technique to overcome these limitations and provide accurate and precise shape estimation.
• Score: 1.0805335573008565
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Fiber optic shape sensors have enabled unique advances in various navigation tasks, from medical tool tracking to industrial applications. Eccentric fiber Bragg gratings (FBG) are cheap and easy-to-fabricate shape sensors that are often interrogated with simple setups. However, using low-cost interrogation systems for such intensity-based quasi-distributed sensors introduces further complications to the sensor's signal. Therefore, eccentric FBGs have not been able to accurately estimate complex multi-bend shapes. Here, we present a novel technique to overcome these limitations and provide accurate and precise shape estimation in eccentric FBG sensors. We investigate the most important bending-induced effects in curved optical fibers that are usually eliminated in intensity-based fiber sensors. These effects contain shape deformation information with a higher spatial resolution that we are now able to extract using deep learning techniques. We design a deep learning model based on a convolutional neural network that is trained to predict shapes given the sensor's spectra. We also provide a visual explanation, highlighting wavelength elements whose intensities are more relevant in making shape predictions. These findings imply that deep learning techniques benefit from the bending-induced effects that impact the desired signal in a complex manner. This is the first step toward cheap yet accurate fiber shape sensing solutions.

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