Evaluating Magic Leap 2 Tool Tracking for AR Sensor Guidance in Industrial Inspections

Abstract

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.