评估魔镜2手柄在工业检测中的追踪精度，为AR导航提供可靠数据。
Evaluating Magic Leap 2 Tool Tracking for AR Sensor Guidance in Industrial Inspections
- 用机械臂与光学追踪系统构建标准化测试流程
- 静态与动态追踪误差均低于0.8毫米，重复性优于0.5毫米
- 适合工业传感器引导类AR应用的开发者与工程师参考
对商用增强现实硬件的严格评估至关重要，但针对现代头戴式显示器（HMD）上工具追踪的公开基准仍有限。本文通过系统评估魔镜2（ML2）控制器的追踪性能，填补这一空白。采用符合EN ISO 9283标准的机械臂实现可重复运动，并以光学追踪系统作为真值，评估了静态与动态条件下的表现，涵盖氢气泄漏检测任务中真实路径场景。结果提供了ML2控制器在精度与重复性方面的量化基准，并提出一种稳健、可迁移的评估方法，为判断其在检测任务及类似基于传感器的工业AR引导应用中的适用性提供了依据。
原文摘要 · Abstract (English)
Rigorous evaluation of commercial Augmented Reality (AR) hardware is crucial, yet public benchmarks for tool tracking on modern Head-Mounted Displays (HMDs) are limited. This paper addresses this gap by systematically assessing the Magic Leap 2 (ML2) controllers tracking performance. Using a robotic arm for repeatable motion (EN ISO 9283) and an optical tracking system as ground truth, our protocol evaluates static and dynamic performance under various conditions, including realistic paths from a hydrogen leak inspection use case. The results provide a quantitative baseline of the ML2 controller's accuracy and repeatability and present a robust, transferable evaluation methodology. The findings provide a basis to assess the controllers suitability for the inspection use case and similar industrial sensor-based AR guidance tasks.
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