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A Novel Point Set Registration-Based Hand–Eye Calibration Method for Robot-Assisted Surgery

Pedicle screw insertion with robot assistance dramatically improves surgical accuracy and safety when compared with manual implantation. In developing such a system, hand–eye calibration is an essential component that aims to determine the transformation between a position tracking and robot-arm sys...

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Autores principales: Sun, Wenyuan, Liu, Jihao, Zhao, Yuyun, Zheng, Guoyan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9656731/
https://www.ncbi.nlm.nih.gov/pubmed/36366144
http://dx.doi.org/10.3390/s22218446
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author Sun, Wenyuan
Liu, Jihao
Zhao, Yuyun
Zheng, Guoyan
author_facet Sun, Wenyuan
Liu, Jihao
Zhao, Yuyun
Zheng, Guoyan
author_sort Sun, Wenyuan
collection PubMed
description Pedicle screw insertion with robot assistance dramatically improves surgical accuracy and safety when compared with manual implantation. In developing such a system, hand–eye calibration is an essential component that aims to determine the transformation between a position tracking and robot-arm systems. In this paper, we propose an effective hand–eye calibration method, namely registration-based hand–eye calibration (RHC), which estimates the calibration transformation via point set registration without the need to solve the [Formula: see text] equation. Our hand–eye calibration method consists of tool-tip pivot calibrations in two-coordinate systems, in addition to paired-point matching, where the point pairs are generated via the steady movement of the robot arm in space. After calibration, our system allows for robot-assisted, image-guided pedicle screw insertion. Comprehensive experiments are conducted to verify the efficacy of the proposed hand–eye calibration method. A mean distance deviation of 0.70 mm and a mean angular deviation of 0.68° are achieved by our system when the proposed hand–eye calibration method is used. Further experiments on drilling trajectories are conducted on plastic vertebrae as well as pig vertebrae. A mean distance deviation of 1.01 mm and a mean angular deviation of 1.11° are observed when the drilled trajectories are compared with the planned trajectories on the pig vertebrae.
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spelling pubmed-96567312022-11-15 A Novel Point Set Registration-Based Hand–Eye Calibration Method for Robot-Assisted Surgery Sun, Wenyuan Liu, Jihao Zhao, Yuyun Zheng, Guoyan Sensors (Basel) Article Pedicle screw insertion with robot assistance dramatically improves surgical accuracy and safety when compared with manual implantation. In developing such a system, hand–eye calibration is an essential component that aims to determine the transformation between a position tracking and robot-arm systems. In this paper, we propose an effective hand–eye calibration method, namely registration-based hand–eye calibration (RHC), which estimates the calibration transformation via point set registration without the need to solve the [Formula: see text] equation. Our hand–eye calibration method consists of tool-tip pivot calibrations in two-coordinate systems, in addition to paired-point matching, where the point pairs are generated via the steady movement of the robot arm in space. After calibration, our system allows for robot-assisted, image-guided pedicle screw insertion. Comprehensive experiments are conducted to verify the efficacy of the proposed hand–eye calibration method. A mean distance deviation of 0.70 mm and a mean angular deviation of 0.68° are achieved by our system when the proposed hand–eye calibration method is used. Further experiments on drilling trajectories are conducted on plastic vertebrae as well as pig vertebrae. A mean distance deviation of 1.01 mm and a mean angular deviation of 1.11° are observed when the drilled trajectories are compared with the planned trajectories on the pig vertebrae. MDPI 2022-11-03 /pmc/articles/PMC9656731/ /pubmed/36366144 http://dx.doi.org/10.3390/s22218446 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Sun, Wenyuan
Liu, Jihao
Zhao, Yuyun
Zheng, Guoyan
A Novel Point Set Registration-Based Hand–Eye Calibration Method for Robot-Assisted Surgery
title A Novel Point Set Registration-Based Hand–Eye Calibration Method for Robot-Assisted Surgery
title_full A Novel Point Set Registration-Based Hand–Eye Calibration Method for Robot-Assisted Surgery
title_fullStr A Novel Point Set Registration-Based Hand–Eye Calibration Method for Robot-Assisted Surgery
title_full_unstemmed A Novel Point Set Registration-Based Hand–Eye Calibration Method for Robot-Assisted Surgery
title_short A Novel Point Set Registration-Based Hand–Eye Calibration Method for Robot-Assisted Surgery
title_sort novel point set registration-based hand–eye calibration method for robot-assisted surgery
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9656731/
https://www.ncbi.nlm.nih.gov/pubmed/36366144
http://dx.doi.org/10.3390/s22218446
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