Shape Sensor Research Articles

3D shape sensor based on discrete-point Rayleigh reflectors inscribed by femtosecond pulses in multicore fibers

Fiber optic sensors which use reflectometry methods to process Rayleigh backscattering signal, are susceptible to any optical losses due to the inherently low level of Rayleigh backscattering in standard telecom optical fibers. In this work, we fabricate and study the shape sensor based on a multicore optical fiber with randomly spaced discrete-point reflectors inscribed in its cores by femtosecond laser pulses. By testing the sensor on different 3D shape samples, we demonstrate the robustness of the shape reconstruction accuracy to introduced optical losses of the signal up to 20 dB with the relative reconstruction error being less than 4 %. In contrast, such level of optical losses dramatically increases the reconstruction error when the unmodified fiber cores are used. A higher signal-to-noise ratio together with low birefringence of the inscribed point reflectors enable accurate shape sensing including the forms with low curvature.

Optical fiber shape reconstruction algorithm based on 3D Euler spiral model

Abstract This paper presents a reconstruction algorithm that uses a 3D Euler spiral model to construct the microsegment of a 3D space curve to improve the reconstruction efficiency. Euler spiral is a curve whose shape information changes linearly with arc length, which improves the current assumption of the reconstruction algorithms that the shape information of the micro-segment is constant, and effectively reduces the number of interpolations required, and thus improves the efficiency of the shape algorithm. To verify the effectiveness of this algorithm, a method for constructing random space curves is proposed. Three random space curves of different lengths are reconstructed and the results are compared with the reconstruction algorithms based on the homogeneous transformation matrix and Bishop frame. The results show that this model can significantly improve the efficiency of the algorithm. Under the random space curves of 1 m, 10 m, and 100 m, the efficiency is enhanced by about 15, 27, and 30 times respectively. Prepare a shape sensor with a length of 1465mm to verify the highest reconstruction accuracy of 3D Euler spiral model, which is consistent with the simulation results. The results provide a solid foundation for further research in the field of shape sensing, and show potential for promoting the development of applications that rely on real-time shape measurements.

Omnidirectional optic fiber shape sensor for submarine landslide monitoring

In-situ submarine landslide monitoring is imperative for ensuring the safety of ocean infrastructures, although it poses greater challenges compared to conventional landslide monitoring methods. In response to this need, we developed an omnidirectional optic fiber shape sensor (OFSS) and a self-contained submarine landslide monitoring system. Wavelength division multiplexing (WDM) and space division multiplexing (SDM) are used to build 10 omnidirectional curvature sensors with 3 fiber Bragg gating (FBG) arrays. Difference curvature demodulation algorithm is introduced to eliminate bending-irrelative effects. The omnidirectional curvature transmission matrix (OCTM) is obtained through calibration process with standard curvature molds. Frenet algorithm is used to recovery the shape. Laboratory experiments demonstrate OFSS’s ability to monitor 3D shape in real time, achieving the deflection error of 0.23 % and the bending direction error of 0.06 rad in the simple bending shape recovery experiment. In the S-shape recovery experiment, the OFSS’s deflection error is 0.77 % and the bending direction error is 0.04 rad. Subsequently, the system underwent testing in shallow water within a ship dock. In this experiment, the OFSS is successfully penetrated into the seabed and remained embedded in the soil for 90 min. The maximal shift observed at the end of the OFSS is 4.61×10-3m with the standard deviation of 9.95×10-4m, while the bending direction exhibited a maximal shift of 3×10-3 rad with the standard deviation of 7.51×10-4rad over the course of the 90-minute duration. These results validate the system’s effectiveness in providing accurate and reliable in-situ monitoring of submarine landslide.

Accuracy compensation method for 2D curve reconstruction of torsional FBG shape sensor of scraper conveyor

The straightness perception of scraper conveyor is a technology that helps to achieve intelligent operation of coal mine working faces. However, there is a problem of accuracy degradation caused by sensor torsion based on fiber Bragg grating (FBG) shape sensing technology. This paper proposes an accuracy compensation method based on torsion angle, and verifies the effectiveness of accuracy compensation through simulation and experimental research. Experimental tests have shown that when the torsion angle of the sensing substrate is 10° and 20°, the end accuracy of the reconstructed curve after accuracy compensation is increased by 2.77% and 1.93% compared to before compensation, respectively. This study indicates that compensation based on the torsion angle can significantly improve the accuracy of two-dimensional (2D) curve reconstruction, and it has broad engineering application prospects in fields such as straightness perception of scraper conveyors and monitoring of underwater pipelines.

Length-extended 3D shape sensor using wavelength/space-division multiplexing grating arrays in a multicore fiber.

Limited by the multiplexing number of fiber Bragg grating (FBG), further improvement in the length of 3D shape sensing based on FBG technology is challenging. In this Letter, a wavelength-division and space-division multiplexing multicore fiber grating method is proposed, which extends the sensing length. Employing the femtosecond-laser point-by-point technology, we inscribed WDM grating arrays in six outer cores of a seven-core fiber, respectively. Three cores were utilized as a segment for shape sensing, and two such segments were offset by a specific length and combined to form a shape sensor. Utilizing an FBG interrogator, the proposed shape sensor achieved 2D and 3D shape sensing at a length of 967 mm and effectively mitigated the effects of temperature variations. In experiments, maximum shape reconstruction errors per unit lengths are 1.89%, 2.72%, and 1.47% for 2D shape, 3D shape, and an arbitrary shape under variable temperature conditions, respectively. The proposed method holds promise for further extending the shape sensing length by utilizing multicore fibers or fiber clusters containing more cores.

High-spatial-resolution φ-OFDR shape sensor based on multicore optical fiber with femtosecond-laser-induced permanent scatter arrays: publisher's note.

This publisher's note contains a correction to Opt. Lett.48, 3219 (2023)10.1364/OL.486644.

OFDR shape sensor based on a femtosecond-laser-inscribed weak fiber Bragg grating array in a multicore fiber.

An optical frequency domain reflectometry (OFDR) shape sensor was demonstrated based on a femtosecond-laser-inscribed weak fiber Bragg grating (WFBG) array in a multicore fiber (MCF). A WFBG array consisting of 60 identical WFBGs was successfully inscribed in each core along a 60 cm long MCF using the femtosecond-laser point-by-point technology, where the length and space of each WFBG were 2 and 8 mm, respectively. The strain distribution of each core in two-dimensional (2D) and three-dimensional (3D) shape sensing was successfully demodulated using the traditional cross correlation algorithm, attributed to the accurate localization of each WFBG. The minimum reconstruction error per unit length of the 2D and 3D shape sensors has been improved to 1.08% and 1.07%, respectively, using the apparent curvature vector method based on the Bishop frame.

Accuracy of instrument tip position using fiber optic shape sensing for navigated bronchoscopy

The purpose of this study was to evaluate the accuracy of a method for estimating the tip position of a fiber optic shape-sensing (FOSS) integrated instrument being inserted through a bronchoscope. A modified guidewire with a multicore optical fiber was inserted into the working channel of a custom-made catheter with three electromagnetic (EM) sensors. The displacement between the instruments was manually set, and a point-based method was applied to match the position of the EM sensors to corresponding points on the shape. The accuracy was evaluated in a realistic bronchial model. An additional EM sensor was used to sample the tip of the guidewire, and the absolute deviation between this position and the estimated tip position was calculated. For small displacements between the tip of the FOSS integrated tool and the catheter, the median deviation in estimated tip position was ≤5 mm. For larger displacements, deviations exceeding 10 mm were observed. The deviations increased when the shape sensor had sharp curvatures relative to more straight shapes. The method works well for clinically relevant displacements of a biopsy tool from the bronchoscope tip, and when the path to the lesion has limited curvatures. However, improvements must be made to our configuration before pursuing further clinical testing.

In-situ consolidation deformation of composite laminate with gaps of various widths

Gaps between prepreg tapes, which occur when prepreg tapes are placed automatically, cause concave deformation of the laminate during consolidation, which degrades the quality of the cured laminate. However, this in-situ concave deformation has never been measured. This study measures consolidation deformation of a cross-ply thermosetting composite laminate containing gaps of various widths at the middle layer. A unique fiber-optic-based shape sensor is used for the in-situ deformation monitoring and the deformation during autoclave pressurization and heating is presented. The results indicate that the deformation phenomenon depends on whether the upper bagging-side layer bridging the gap contacts the tool-side layer below the gap as it sinks into the gap during consolidation. The consolidation process reveals when the gap width is narrow, the fibers and the resin from the prepreg layer flow into the gap and displace upwards the sunken upper layer, partially reducing the concave deformation. One attempt to suppress gap-induced deformation is also made by using a curing condition inspired by the observation and understanding of this deformation mechanism.

Shape detection of thin diameter flexible sensors with non-uniform gratings

Flexible intelligent medical device shape feedback has a very important application prospect in intelligent structure detection. Due to the error accumulation effect, the distribution of gratings is also an important factor affecting the reconstruction error of shape sensors. A grating positions optimization method based on the fusion of adaptive mutation particle swarm optimization algorithm and shape reconstruction algorithm is proposed in the paper. The curves with 10 measurement points arranged at a sensing length of 810 mm and 4 measurement points arranged at a sensing length of 200 mm are simulated and calculated. After multiple optimization training, the sparse optimal distribution of gratings with the smallest shape error is obtained. Package sensors with uniform and non-uniform distribution of grating points based on the obtained point positions, and conduct planar shape reconstruction experiments. After multiple shape reconstruction experiments, the shape errors of the sensor shape reconstruction endpoint for uniform gratings are 2.76% and 2.94%, respectively, and the reconstruction accuracy for non-uniform gratings is 1.94% and 2.71%. The optimized shape sensor has good performance, thus proving the effectiveness of the fiber grating sensing grid point optimization method in flexible medical device deformation monitoring.

Design of pseudo brain nano gold layer photonic crystal fiber sensor and investigation of fabrication accuracy

In this research, a new photonic crystal fiber sensor is proposed based on human brain scan images. As the human brain analyzes information in the cerebellum to make decisions, the use of this design and placement of air holes in the shape of human brain is the main reason of more electromagnetic field limitation in the center of the fiber or pseudo-cerebellum. Finite element method based on mode solver (FEM) is used to analyze this sensor. The size of the air holes and the thickness of the plasmonic layer are proposed in this design based on the Nelder-Mead optimization algorithm. The possible errors caused by the sensor fabrication are investigated and a unique equation is presented to estimate the effect of the size of the air holes on the sensor confinement loss. Numerical inference show that this brain shape sensor has an amazing maximum amplitude sensitivity (AS) of 7208 RIU−1 and appropriate maximum wavelength sensitivity (WS) of 10000 nm/RIU. Therefore, the proposed sensor has great prospects for medical, chemical and pharmaceutical measurements and diagnostic applications because of its high sensitivity, powerful detection and easy fabrication.

Optical Fiber-Based Needle Shape Sensing in Real Tissue: Single Core vs. Multicore Approaches.

Flexible needle insertion procedures are common in minimally-invasive surgeries for diagnosing and treating prostate cancer. Bevel-tip needles provide physicians the capability to steer the needle during long insertions to avoid vital anatomical structures in the patient and reduce post-operative patient discomfort. To provide needle placement feedback to the physician, sensors are embedded into needles for determining the real-time 3D shape of the needle during operation without needing to visualize the needle intra-operatively. Through expansive research in fiber optics, a plethora of bio-compatible, MRI-compatible, optical shape-sensors have been developed to provide real-time shape feedback, such as single-core and multicore fiber Bragg gratings. In this paper, we directly compare single-core fiber-based and multicore fiber-based needle shape-sensing through similarly constructed, four-active area sensorized bevel-tip needles inserted into phantom and ex-vivo tissue on the same experimental platform. In this work, we found that for shape-sensing in phantom tissue, the two needles performed identically with a p-value of 0.164 > 0.05, but in ex-vivo real tissue, the single-core fiber sensorized needle significantly outperformed the multicore fiber configuration with a p-value of 0.0005 < 0.05. This paper also presents the experimental platform and method for directly comparing these optical shape sensors for the needle shape-sensing task, as well as provides direction, insight and required considerations for future work in constructively optimizing sensorized needles.

Intelligent soft self-twisted shape sensor

This paper introduces an all-fiber flexible soft sensor that combines machine learning methods to acquire the ability to recognize its own twisted shape. The sensor is twisted into various shapes, the recognition accuracy of the shapes can reach 100 %. Unlike existing sensors, which require multiple sensors to form an array, such sensor requires only a single optical fiber MZI (Mach-Zehnder interferometer) embedded inside the flexible material, which makes the sensing structure and wiring connection very simple. At the same time, the sensor presents very good reliability, bend sensitivity and repeatability. Its temperature performance is also investigated. All above highlighting its great potential in intelligent robots, medical rehabilitation, surgical endoscopes, and object recognition.

Low-Cost Distributed Optical Waveguide Shape Sensor Based on WTDM Applied in Bionics.

Bionic robotics, driven by advancements in artificial intelligence, new materials, and manufacturing technologies, is attracting significant attention from research and industry communities seeking breakthroughs. One of the key technologies for achieving a breakthrough in robotics is flexible sensors. This paper presents a novel approach based on wavelength and time division multiplexing (WTDM) for distributed optical waveguide shape sensing. Structurally designed optical waveguides based on color filter blocks validate the proposed approach through a cost-effective experimental setup. During data collection, it combines optical waveguide transmission loss and the way of controlling the color and intensity of the light source and detecting color and intensity variations for modeling. An artificial neural network is employed to model and demodulate a data-driven optical waveguide shape sensor. As a result, the correlation coefficient between the predicted and real bending angles reaches 0.9134 within 100 s. To show the parsing performance of the model more intuitively, a confidence accuracy curve is introduced to describe the accuracy of the data-driven model at last.

Dynamic curvature sensing using time expanded ΦOTDR.

Shape sensing can be accomplished using optical fiber sensors through different interrogation principles such as fiber Bragg gratings, optical frequency-domain reflectometry (OFDR), or optical time-domain reflectometry (OTDR). These techniques are either not entirely distributed, have poor performance in dynamic sensing, or are only valid for few-meter-long fibers. Here, we present a system able to perform distributed curvature sensing with a range of 125 m, 10-cm resolution, and a sampling rate of 50 Hz. This is done by interrogating three cores of a multi-core fiber (MCF) with the novel, to the best of our knowledge, time-expanded phase-sensitive (TE-Φ)OTDR technique. This system fills a performance gap in fiber shape sensors, opening the door to applications in civil engineering, medicine, or seismology.

Reconfiguration Error Correction Model for an FBG Shape Sensor Based on the Sparrow Search Algorithm.

A reconfiguration error correction model for an FBG shape sensor (FSS) is proposed. The model includes curvature, bending direction error correction, and the self-correction of the FBG placement angle and calibration error based on an improved sparrow search algorithm (SSA). SSA could automatically correct the placement angle and calibration direction of the FBG, and then use the corrected placement angle and calibration direction to correct the curvature and bending direction of the FSS, thereby improving the accuracy of shape reconfiguration. After error correction, the tail point reconfiguration errors of different shapes were reduced from 2.56% and 4.96% to 1.12% and 2.45%, respectively. This paper provides a new reconfiguration error correction method for FSS that does not require a complicated experimental calibration process, is simpler, more efficient, and more operable than traditional methods, and has great potential in FSS application scenarios.

FBG-based 3D shape sensor based on spun multi-core fibre for continuum surgical robots

FBG-based 3D shape sensor based on spun multi-core fibre for continuum surgical robots

Design and Fabrication of a Fiber Bragg Grating Shape Sensor for Shape Reconstruction of a Continuum Manipulator.

Continuum dexterous manipulators (CDMs) are suitable for performing tasks in a constrained environment due to their high dexterity and maneuverability. Despite the inherent advantages of CDMs in minimally invasive surgery, real-time control of CDMs' shape during nonconstant curvature bending is still challenging. This study presents a novel approach for the design and fabrication of a large deflection fiber Bragg grating (FBG) shape sensor embedded within the lumens inside the walls of a CDM with a large instrument channel. The shape sensor consisted of two fibers, each with three FBG nodes. A shape-sensing model was introduced to reconstruct the centerline of the CDM based on FBG wavelengths. Different experiments, including shape sensor tests and CDM shape reconstruction tests, were conducted to assess the overall accuracy of the shape-sensing. The FBG sensor evaluation results revealed the linear curvature-wavelength relationship with the large curvature detection of 0.045 mm and a high wavelength shift of up to 5.50 nm at a 90° bending angle in both the bending directions. The CDM's shape reconstruction experiments in a free environment demonstrated the shape-tracking accuracy of 0.216 ± 0.126 mm for positive/negative deflections. Also, the CDM shape reconstruction error for three cases of bending with obstacles was observed to be 0.436 ± 0.370 mm for the proximal case, 0.485 ± 0.418 mm for the middle case, and 0.312 ± 0.261 mm for the distal case. This study indicates the adequate performance of the FBG sensor and the effectiveness of the model for tracking the shape of the large-deflection CDM with nonconstant-curvature bending for minimally invasive orthopedic applications.

High-spatial-resolution φ-OFDR shape sensor based on multicore optical fiber with femtosecond-laser-induced permanent scatter arrays.

An optical fiber φ-OFDR shape sensor with a submillimeter spatial resolution of 200 µm was demonstrated by using femtosecond-laser-induced permanent scatter array (PS array) multicore fiber (MCF). A PS array was successfully inscribed in each slightly twisted core of the 400-mm-long MCF. The two-dimensional (2D) and three-dimensional (3D) shapes of the PS-array-inscribed MCF were successfully reconstructed by using PS-assisted φ-OFDR, vector projections, and the Bishop frame based on the PS-array-inscribed MCF. The minimum reconstruction error per unit length of the 2D and 3D shape sensor was 2.21% and 1.45%, respectively.

High-Accuracy 3D Shape Sensor Based on Anti-Twist Packaged High Uniform Multicore Fiber FBGs

High-Accuracy 3D Shape Sensor Based on Anti-Twist Packaged High Uniform Multicore Fiber FBGs