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arXiv · 2210.01406

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

Hongbin Lin·Bin Li·Yunhui Liu·Kwok Wai Samuel Au
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Abstract

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.

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Hongbin Lin, Bin Li, Yunhui Liu, Kwok Wai Samuel Au. 2022-10-04. Open-source High-precision Autonomous Suturing Framework With Visual Guidance. https://arxiv.org/abs/2210.01406

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