Open-source High-precision Autonomous Suturing Framework With Visual Guidance

Fuente: arXiv
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Auteurs principaux: Lin, Hongbin, Li, Bin, Liu, Yunhui, Au, Kwok Wai Samuel
Format: Preprint
Publié: 2022
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author Lin, Hongbin
Li, Bin
Liu, Yunhui
Au, Kwok Wai Samuel
author_facet Lin, Hongbin
Li, Bin
Liu, Yunhui
Au, Kwok Wai Samuel
contents Autonomous surgery has attracted increasing attention for revolutionizing robotic patient care, yet remains a distant and challenging goal. In this paper, we propose an image-based framework for high-precision autonomous suturing operation. We first build an algebraic geometric algorithm to achieve accurate needle pose estimation, then design the corresponding keypoint-based calibration network for joint-offset compensation, and further plan and control suture trajectory. Our solution ranked first among all competitors in the AccelNet Surgical Robotics Challenge. Videos and codes can be found in https://sites.google.com/view/accel-2022-cuhk.
format Preprint
id arxiv_https___arxiv_org_abs_2210_01406
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle Open-source High-precision Autonomous Suturing Framework With Visual Guidance
Lin, Hongbin
Li, Bin
Liu, Yunhui
Au, Kwok Wai Samuel
Robotics
Autonomous surgery has attracted increasing attention for revolutionizing robotic patient care, yet remains a distant and challenging goal. In this paper, we propose an image-based framework for high-precision autonomous suturing operation. We first build an algebraic geometric algorithm to achieve accurate needle pose estimation, then design the corresponding keypoint-based calibration network for joint-offset compensation, and further plan and control suture trajectory. Our solution ranked first among all competitors in the AccelNet Surgical Robotics Challenge. Videos and codes can be found in https://sites.google.com/view/accel-2022-cuhk.
title Open-source High-precision Autonomous Suturing Framework With Visual Guidance
topic Robotics
url https://arxiv.org/abs/2210.01406