Fibre Bragg grating (FBG) sensor system for highly flexible single-link robots

Payo, Ismael; Feliú, V.; Cortázar, O. D.

doi:10.1016/j.sna.2008.11.033

Cited by 28 publications

(13 citation statements)

References 21 publications

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“…2(b)). The needle path is predicted by using needle tip position (5) and orientation (6), and the parameters characterizing the needle path (radius (r t ) and cutangle (β)).…”

Section: A Kinematics-based Modelmentioning

confidence: 99%

Three-Dimensional Needle Shape Reconstruction Using an Array of Fiber Bragg Grating Sensors

Roesthuis

Kemp²,

Dobbelsteen

et al. 2014

IEEE/ASME Trans. Mechatron.

229

151

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We present a prototype of a flexible nitinol needle (φ 1.0 mm and length 172 mm) integrated with an array of 12 Fiber Bragg Grating (FBG) sensors. These sensors measure the axial strain, which enables the computation of the needle curvature. We reconstruct the three-dimensional (3-D) needle shape from the curvature. Experiments are performed where the needle is deflected in free space. The maximum errors between the experiments and beam theory-based model are 0.20 mm (in-plane deflection with single bend), 0.51 mm (in-plane deflection with double bend), and 1.66 mm (out-of-plane). We also describe kinematics-based and mechanics-based models for predicting the 3-D needle shape during insertion into soft tissue. We perform experiments where the needle is inserted into a soft-tissue simulant, and the 3-D needle shape is reconstructed using the FBG sensors. We compare the reconstructed needle shape to deflection obtained from camera images and our models. The maximum error between the experiments and the camera images is 0.74 mm. The maximum errors between the kinematics-based and mechanics-based models and the camera images are 3.77 mm and 2.20 mm, respectively. This study demonstrates that deflection models and needles integrated with FBG sensors have the potential to be used in combination with clinical imaging modalities in order to enable accurate needle steering.

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“…2(b)). The needle path is predicted by using needle tip position (5) and orientation (6), and the parameters characterizing the needle path (radius (r t ) and cutangle (β)).…”

Section: A Kinematics-based Modelmentioning

confidence: 99%

Three-Dimensional Needle Shape Reconstruction Using an Array of Fiber Bragg Grating Sensors

Roesthuis

Kemp²,

Dobbelsteen

et al. 2014

IEEE/ASME Trans. Mechatron.

229

151

View full text Add to dashboard Cite

show abstract

“…In order to reliably and widely use these actuators in soft surgical manipulator, mastering the relationship between shape measurement and position control of the actuator is indispensable. Considering the flexible bodies of the soft manipulator, some conventional rigid sensors, like encoders and strain gauges [5,6] have problems of complex cable networks, electromagnetic and noise signal interference, etc., and the rigid sensor will damage human tissue when the manipulator interacts with the human organs surround it [7][8][9]. The visual-based sensing systems are also inapplicable due to the narrow spaces and various obstacles in human body.…”

Section: Introductionmentioning

confidence: 99%

Design, Measurement and Shape Reconstruction of Soft Surgical Actuator Based on Fiber Bragg Gratings

Zhu

Sun

et al. 2018

Applied Sciences

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Soft actuators are the components responsible for organs and tissues adsorptive fixation in some surgical operations, but the lack of shape sensing and monitoring of a soft actuator greatly limits their application potential. Consequently, this paper proposes a real-time 3D shape reconstruction method of soft surgical actuator which has an embedded optical fiber with two Fiber Bragg Grating (FBG) sensors. First, the design principle and the sensing of the soft actuator based on FBG sensors are analyzed, and the fabrication process of soft actuator which has an embedded optical fiber with two FBG sensors is described. Next, the calibration of the FBG sensors is conducted. Based on curvatures and curve fitting functions, the strategy of 3D shapes reconstruction of the soft actuator is presented. Finally, some bending experiments of the soft actuator are carried out, and the 3D shapes of the soft actuator at different bending states are reconstructed. This well reconstructed 3D shape of a soft actuator demonstrates the effectiveness of the shape reconstruction method that is proposed in this paper, as well as the potential and increased applications of these structures for real soft surgical actuators.

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“…Recently, morphological sensing with FBG embedded flexible sensors has become a hot topic [ 5 , 6 , 7 , 8 ]. Payo et al [ 9 ] measured the deflections of a robotic arm based on FBG sensors and interpolation methods. Xu et al and Bhamber et al [ 10 , 11 ] adopted orthogonal FBG arrays to measure bidirectional curvatures, then reconstructed shapes using a curve fitting algorithm.…”

Section: Introductionmentioning

confidence: 99%

Design and Optimization of FBG Implantable Flexible Morphological Sensor to Realize the Intellisense for Displacement

Tian

Wang

Sui

et al. 2018

Sensors

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The measurement accuracy of the intelligent flexible morphological sensor based on fiber Bragg grating (FBG) structure was limited in the application of geotechnical engineering and other fields. In order to improve the precision of intellisense for displacement, an FBG implantable flexible morphological sensor was designed in this study, and the classification morphological correction method based on conjugate gradient method and extreme learning machine (ELM) algorithm was proposed. This study utilized finite element simulations and experiments, in order to analyze the feasibility of the proposed method. Then, following the corrections, the results indicated that the maximum relative error percentages of the displacements at measuring points in different bending shapes were determined to be 6.39% (Type 1), 7.04% (Type 2), and 7.02% (Type 3), respectively. Therefore, it was confirmed that the proposed correction method was feasible, and could effectively improve the abilities of sensors for displacement intellisense. In this paper, the designed intelligent sensor was characterized by temperature self-compensation, bending shape self-classification, and displacement error self-correction, which could be used for real-time monitoring of deformation field in rock, subgrade, bridge, and other geotechnical engineering, presenting the vital significance and application promotion value.

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Fibre Bragg grating (FBG) sensor system for highly flexible single-link robots

Cited by 28 publications

References 21 publications

Three-Dimensional Needle Shape Reconstruction Using an Array of Fiber Bragg Grating Sensors

Three-Dimensional Needle Shape Reconstruction Using an Array of Fiber Bragg Grating Sensors

Design, Measurement and Shape Reconstruction of Soft Surgical Actuator Based on Fiber Bragg Gratings

Design and Optimization of FBG Implantable Flexible Morphological Sensor to Realize the Intellisense for Displacement

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