Virtual fixture control of a hybrid parallel-serial robot for assisting ophthalmic surgery: An experimental study

Nasseri, M. Ali; Gschirr, P.; Eder, Maximilian; Nair, Suraj; Kobuch, Karin; Maier, Mathias; Zapp, Daniel; Lohmann, Chris P.; Knoll, Alois

doi:10.1109/biorob.2014.6913865

Cited by 24 publications

(12 citation statements)

References 16 publications

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“…6, the robot is controlled to move the needle in X , Y , and Z direction with 20 and 40 µm and each movement is repeated 25 times. The robot is also controlled to yaw and pitch around the needle tip as the RCM control point with virtual fixture control [27]. The yaw and rotation angle is set from −45 • to 45 • with 15 • as the step.…”

Section: Experiments and Resultsmentioning

confidence: 99%

6DOF Needle Pose Estimation for Robot-Assisted Vitreoretinal Surgery

et al. 2019

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Vitreoretinal (VR) surgery is typical microsurgery with delicate and complex surgical procedures. The vision-based navigation for robot-assisted VR surgery has not been fully exploited because of the challenges that arise from illumination, high precision, and safety assessments. This paper presents a novel method to estimate the 6DOF needle pose specifically for the application of robotic intraocular needle navigation using optical coherence tomography (OCT) volumes. The key ingredients of the proposed method are 1) 3D needle point cloud segmentation in OCT volume and 2) needle point cloud 6DOF pose estimation using a modified iterative closest point (ICP) algorithm. To address the former, a voting mechanism with geometric features of the needle is utilized to robustly segment the needle in OCT volume. Afterward, the CAD model of the needle point cloud is matched with the segmented needle point cloud to estimate the 6DOF needle pose with a proposed shift-rotate ICP (SR-ICP). This method is evaluated by the existing ophthalmic robot on ex-vivo pig eyes. The quantitative and qualitative results are evaluated and presented for the proposed method.INDEX TERMS Biomedical engineering, biomedical image processing, biomedical signal processing, medical robotics.

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Section: Experiments and Resultsmentioning

confidence: 99%

6DOF Needle Pose Estimation for Robot-Assisted Vitreoretinal Surgery

et al. 2019

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“…The same team developed a virtual-fixture control method and experimentally evaluated its use on an ex vivo pig eye [ 9 ]. These virtual fixtures included the virtual constraint of the RCM and autonomous RCM adjustment.…”

Section: Advanced Surgical Robotic Systemsmentioning

confidence: 99%

Advanced robotic surgical systems in ophthalmology

Gerber

Pettenkofer

Hubschman

2020

Eye

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In this paper, an overview of advanced robotic surgical systems in ophthalmology is provided. The systems are introduced as representative examples of the degree of human vs. robotic control during surgical procedures. The details are presented on each system and the latest advancements of each are described. Future potential applications for surgical robotics in ophthalmology are discussed in detail, with representative examples provided alongside recent progress.

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“…A solution to this lack of dexterity was proposed by Wei through the addition of extra degrees of freedom to the surgical instrument inside the eye, which is inconsistent with currently accepted intraocular practice. Nasseri applied a parallel‐coupled joint mechanism to achieve an adjustable pivot point. Vitreo‐retinal surgery was realized by implementing force feedback as a user interface while removing tremors caused by human motions .…”

Section: Introductionmentioning

confidence: 99%