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用于连续体机器人形状重建的光纤布拉格光栅形状传感器的设计与制造

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

作者信息

Amirkhani Golchehr, Goodridge Anna, Esfandiari Mojtaba, Phalen Henry, Ma Justin H, Iordachita Iulian, Armand Mehran

机构信息

Department of Mechanical Engineering and the Laboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, MD 21218 USA.

Laboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, MD 21218 USA.

出版信息

IEEE Sens J. 2023 Jun 15;23(12):12915-12929. doi: 10.1109/jsen.2023.3274146. Epub 2023 May 15.


DOI:10.1109/jsen.2023.3274146
PMID:38558829
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10977927/
Abstract

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.

摘要

连续体灵巧操作器(CDM)由于其高灵活性和机动性,适用于在受限环境中执行任务。尽管CDM在微创手术中具有固有优势,但在非恒定曲率弯曲过程中对CDM形状进行实时控制仍然具有挑战性。本研究提出了一种新颖的方法,用于设计和制造一种大挠度光纤布拉格光栅(FBG)形状传感器,该传感器嵌入具有大器械通道的CDM壁内的管腔中。形状传感器由两根光纤组成,每根光纤有三个FBG节点。引入了一种形状传感模型,以基于FBG波长重建CDM的中心线。进行了不同的实验,包括形状传感器测试和CDM形状重建测试,以评估形状传感的整体准确性。FBG传感器评估结果显示了线性曲率-波长关系,在两个弯曲方向上,大曲率检测为0.045 mm,在90°弯曲角度下波长偏移高达5.50 nm。在自由环境中进行的CDM形状重建实验表明,正/负挠度的形状跟踪精度为0.216±0.126 mm。此外,观察到在有障碍物的三种弯曲情况下,近端情况的CDM形状重建误差为0.436±0.370 mm,中间情况为0.485±0.418 mm,远端情况为0.312±0.261 mm。本研究表明,FBG传感器具有足够的性能,该模型对于跟踪具有非恒定曲率弯曲的大挠度CDM形状以用于微创骨科应用是有效的。

相似文献

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

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[2]
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[3]
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[4]
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[5]
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[6]
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[7]
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[8]
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[9]
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[10]
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本文引用的文献

[1]
A Dexterous Robotic System for Autonomous Debridement of Osteolytic Bone Lesions in Confined Spaces: Human Cadaver Studies.

IEEE Trans Robot. 2022-4

[2]
Towards Automatic Robotic Calibration System for Flexible Needles with FBG Sensors.

Int Symp Med Robot. 2021-11

[3]
A Surgical Robotic System for Treatment of Pelvic Osteolysis Using an FBG-Equipped Continuum Manipulator and Flexible Instruments.

IEEE ASME Trans Mechatron. 2021-2

[4]
An Active Steering Hand-held Robotic System for Minimally Invasive Orthopaedic Surgery Using a Continuum Manipulator.

IEEE Robot Autom Lett. 2021-4

[5]
Data-Driven Shape Sensing of a Surgical Continuum Manipulator Using an Uncalibrated Fiber Bragg Grating Sensor.

IEEE Sens J. 2021-2-1

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IEEE Trans Med Robot Bionics. 2019-2

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Opt Express. 2019-2-4

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Sensors (Basel). 2018-5-17

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Mechanical Model of Dexterous Continuum Manipulators with Compliant Joints and Tendon/External Force Interactions.

IEEE ASME Trans Mechatron. 2017-2

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