Validating Augmented Reality (AR) tracking and interaction models requires precise, repeatable ground-truth motion. However, human users cannot reliably perform consistent motion due to biomechanical variability. Robotic manipulators are promising to act as human motion proxies if they can mimic human movements. In this work, we design and implement ARBot, a real-time teleoperation platform that can effectively capture natural human motion and accurately replay the movements via robotic manipulators. ARBot includes two capture models: stable wrist motion capture via a custom CV and IMU pipeline, and natural 6-DOF control via a mobile application. We design a proactively-safe QP controller to ensure smooth, jitter-free execution of the robotic manipulator, enabling it to function as a high-fidelity record and replay physical proxy. We open-source ARBot and release a benchmark dataset of 132 human and synthetic trajectories captured using ARBot to support controllable and scalable AR evaluation.

翻译：验证增强现实（AR）跟踪与交互模型需要精确、可重复的真实运动数据。然而，由于生物力学的变异性，人类用户无法可靠地执行一致的运动。若机器人操作臂能够模拟人体运动，则有望作为人体运动代理。本研究设计并实现了ARBot——一个能够有效捕捉自然人机运动并通过机器人操作臂精确复现动作的实时遥操作平台。ARBot包含两种捕捉模型：通过定制化计算机视觉与惯性测量单元流程实现的稳定手腕运动捕捉，以及通过移动应用程序实现的自然六自由度控制。我们设计了一种主动安全的二次规划控制器，确保机器人操作臂执行平滑无抖振，使其能够作为高保真的记录与回放物理代理。我们开源了ARBot，并发布了使用ARBot捕捉的132条人类与合成轨迹基准数据集，以支持可控且可扩展的AR评估。