基于球形标记体模与无阈值中心定位的无跟踪器机器人超声标定
Tracker-Free Robotic Ultrasound Calibration with a Spherical-Marker Phantom and Threshold-Free Center Localization
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中文总结 AI 辅助
提出一种无跟踪器机器人超声标定框架，采用球形标记体模和无阈值中心定位方法，实现自动标定，实验验证精度与三标记方法相当。
中文摘要 AI 辅助
机器人超声（US）标定对于准确建立超声图像与机器人坐标系之间的关系至关重要，但现有方法往往需要复杂的体模或外部3D跟踪器，使得准确且自动化的标定仍具挑战性。在本工作中，我们开发了一种无跟踪器的机器人超声标定框架，采用球形标记体模和高度自动化的感知流程进行球心定位。所提出的无阈值图像处理方法基于每幅超声图像的强度分布来定位球形特征，消除了人工调整的强度阈值，并在不同成像设置下提高了鲁棒性，无需针对每个系统重新调整。随后，利用球形基准标记的多姿态观测来估计超声到末端执行器（US-to-EE）的变换，无需外部跟踪或预先在机器人基座坐标系中定位球心。我们在机器人超声平台上通过重复扫描球体验证了所提框架，并使用具有已知CAD模型的几何不同体模进一步评估了标定后的系统。在12折交叉验证中，单标记标定实现了球心精度和准确度分别为$1.75\pm0.51$ mm和$0.85\pm0.11$ mm，而三标记标定分别为$1.72\pm0.51$ mm和$0.84\pm0.12$ mm。在三个重建集上，单标记标定产生的配准后点到表面平均绝对误差（MAE）±标准差（SD）合并值对于圆锥体为$0.41\pm0.35$ mm，对于三棱柱为$0.50\pm0.41$ mm，与三标记结果（分别为$0.40\pm0.35$ mm和$0.48\pm0.40$ mm）非常接近。
英文摘要
Robotic ultrasound (US) calibration is essential for accurately relating US images to the robot coordinate system, but accurate and automated calibration remains challenging because existing methods often require complex phantoms or external 3D trackers. In this work, we develop a tracker-free robotic US calibration framework using a spherical-marker phantom and a highly automated perception pipeline for sphere-center localization. The proposed threshold-free image-processing method localizes the spherical feature based on each US image's intensity distribution, eliminating hand-tuned intensity thresholds and improving robustness across imaging settings without per-system retuning. Multi-pose observations of the spherical fiducial are then used to estimate the US-to-EE transformation without external tracking or prior localization of the sphere center in the robot base frame. We validate the proposed framework on a robotic US platform through repeated sphere scans and further assess the calibrated system using geometrically distinct phantoms with known CAD models. Across 12 cross-validation folds, single-marker calibration achieved sphere-center accuracy and precision of $1.75\pm0.51$ mm and $0.85\pm0.11$ mm, respectively, compared with $1.72\pm0.51$ mm and $0.84\pm0.12$ mm for three-marker calibration. Across the three reconstruction sets, the single-marker calibration yielded pooled post-registration point-to-surface MAE$\pm$SD values of $0.41\pm0.35$ mm for the cone and $0.50\pm0.41$ mm for the triangular prism, closely matching the three-marker results of $0.40\pm0.35$ mm and $0.48\pm0.40$ mm, respectively.
发表机构
- University of Michigan（密歇根大学）
机构由 AI 辅助整理，请以论文原文为准。
