Simultaneous Online Registration-Independent Stiffness Identification and Tip Localization of Surgical Instruments in Robot-assisted Eye Surgery.

Autor:	Ebrahimi A; Department of Mechanical Engineering and also Laboratory for Computational Sensing and Robotics at the Johns Hopkins University, Baltimore, MD, 21218, USA., Sefati S; Department of Mechanical Engineering and also Laboratory for Computational Sensing and Robotics at the Johns Hopkins University, Baltimore, MD, 21218, USA., Gehlbach P; Wilmer Eye Institute, Johns Hopkins Hospital, Baltimore, MD, 21287, USA., Taylor RH; Department of Mechanical Engineering and also Laboratory for Computational Sensing and Robotics at the Johns Hopkins University, Baltimore, MD, 21218, USA.; Department of Computer Science and also Laboratory for Computational Sensing and Robotics at the Johns Hopkins University, Baltimore, MD, 21218, USA., Iordachita I; Department of Mechanical Engineering and also Laboratory for Computational Sensing and Robotics at the Johns Hopkins University, Baltimore, MD, 21218, USA.
Jazyk:	angličtina
Zdroj:	IEEE transactions on robotics : a publication of the IEEE Robotics and Automation Society [IEEE Trans Robot] 2023 Apr; Vol. 39 (2), pp. 1373-1387. Date of Electronic Publication: 2022 Sep 09.
DOI:	10.1109/tro.2022.3201393
Abstrakt:	Notable challenges during retinal surgery lend themselves to robotic assistance which has proven beneficial in providing a safe steady-hand manipulation. Efficient assistance from the robots heavily relies on accurate sensing of surgery states (e.g. instrument tip localization and tool-to-tissue interaction forces). Many of the existing tool tip localization methods require preoperative frame registrations or instrument calibrations. In this study using an iterative approach and by combining vision and force-based methods, we develop calibration- and registration-independent (RI) algorithms to provide online estimates of instrument stiffness (least squares and adaptive). The estimations are then combined with a state-space model based on the forward kinematics (FWK) of the Steady-Hand Eye Robot (SHER) and Fiber Brag Grating (FBG) sensor measurements. This is accomplished using a Kalman Filtering (KF) approach to improve the deflected instrument tip position estimations during robot-assisted eye surgery. The conducted experiments demonstrate that when the online RI stiffness estimations are used, the instrument tip localization results surpass those obtained from pre-operative offline calibrations for stiffness.
Databáze:	MEDLINE
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