Force sensing in continuum manipulators using fiber Bragg grating sensors

Khan, Fouzia; Roesthuis, Roy J.; Misra, Sarthak

doi:10.1109/iros.2017.8206073

Cited by 48 publications

(35 citation statements)

References 24 publications

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“…In some cases, stabilization of the catheter tip requires position feedback and a relatively fast control rate. To address this, studies have presented miniature sensors inside the catheter body [96]. Fiber Bragg grating sensors can be used to acquire information about the interaction forces and the shape of the instrument.…”

Section: Discussionmentioning

confidence: 99%

Flexible Instruments for Endovascular Interventions: Improved Magnetic Steering, Actuation, and Image-Guided Surgical Instruments

Heunis

Sikorski

Misra

2018

IEEE Robot. Automat. Mag.

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Section: Discussionmentioning

confidence: 99%

Flexible Instruments for Endovascular Interventions: Improved Magnetic Steering, Actuation, and Image-Guided Surgical Instruments

Heunis

Sikorski

Misra

2018

IEEE Robot. Automat. Mag.

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“…The steering algorithm will compensate deviations from the intended path, thus reducing the targeting error. In order to improve the needletissue force model, we will combine the model with FBG-based force sensing technique [44] to provide force feedback. This integration will allow us to study the user feedback perception as the needle crosses different tissue layers.…”

Section: Clinician/usermentioning

confidence: 99%

Tele-Operated MRI-Guided Needle Insertion for Prostate Interventions

Moreira

Kuil

Dias

et al. 2019

J. Med. Robot. Res.

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Prostate cancer is one of the leading causes of death in men. Prostate interventions using magnetic resonance imaging (MRI) benefits from high tissue contrast if compared to other imaging modalities. The Minimally Invasive Robotics In An MRI environment (MIRIAM) robot is an MRI-compatible system able to steer different types of needles towards a point of interest using MRI guidance. However, clinicians can be reluctant to give the robot total control of the intervention. This work integrates a haptic device in the MIRIAM system to allow input from the clinician during the insertion. A shared control architecture is achieved by letting the clinician control the insertion depth via the haptic device, while the robotic system controls the needle orientation. The clinician receives haptic feedback based on the insertion depth and tissue characteristics. Four control laws relating the motion of the master robot (haptic device) to the motion of the slave robot (MIRIAM robot) are presented and evaluated. Quantitative and qualitative results from 20 human subjects demonstrate that the squared-velocity control law is the most suitable option for our application. Additionally, a pre-operative target localization algorithm is presented in order to provide the robot with the target location. The target localization and reconstruction algorithm are validated in phantom and patient images with an average dice similarity coefficient (DSC) of 0.78. The complete system is validated through experiments by inserting a needle towards a target within the MRI scanner. Four human subjects perform the experiment achieving an average targeting error of 3.4[Formula: see text]mm.

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“…Current researches on force sensing for soft objects can be divided into two major categories: direct sensing and indirect sensing. The first category employs embedded sensors to measure the strain directly by placing the sensors at the tip of robotic tools [14], [15], around the shaft in a helical layout [16], or along the arc length [17] of the robotic manipulator. The direct sensing approaches generally lead to more accurate estimation of external forces.…”

Section: Related Workmentioning

confidence: 99%

Calibration and External Force Sensing for Soft Robots Using an RGB-D Camera

Zhang

Petit

Dequidt

et al. 2019

IEEE Robot. Autom. Lett.

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Benefiting from the deformability of soft robots, calibration and force sensing for soft robots are possible using an external vision-based system, instead of embedded mechatronic force sensors. In this paper, we first propose a calibration method to calibrate both the sensor-robot coordinate system and the actuator inputs. This task is addressed through a sequential optimization problem for both variables. We also introduce an external force sensing system based on a realtime Finite Element (FE) model with the assumption of static configurations, and which consists of two steps: force location detection and force intensity computation. The algorithm that estimates force location relies on the segmentation of the point cloud acquired by an RGB-D camera. Then, the force intensities can be computed by solving an inverse quasi-static problem based on matching the FE model with the point cloud of the soft robot. As for validation, the proposed strategies for calibration and force sensing have been tested using a parallel soft robot driven by four cables.

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Force sensing in continuum manipulators using fiber Bragg grating sensors

Cited by 48 publications

References 24 publications

Flexible Instruments for Endovascular Interventions: Improved Magnetic Steering, Actuation, and Image-Guided Surgical Instruments

Flexible Instruments for Endovascular Interventions: Improved Magnetic Steering, Actuation, and Image-Guided Surgical Instruments

Tele-Operated MRI-Guided Needle Insertion for Prostate Interventions

Calibration and External Force Sensing for Soft Robots Using an RGB-D Camera

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