Evaluating Magic Leap 2 Tool Tracking for AR Sensor Guidance in Industrial Inspections
Masuhr, Christian, Koch, Julian, Schüppstuhl, Thorsten
–arXiv.org Artificial Intelligence
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.
arXiv.org Artificial Intelligence
Nov-26-2025
- Country:
- Asia > Japan
- Kyūshū & Okinawa > Kyūshū > Fukuoka Prefecture > Fukuoka (0.04)
- Europe
- North America > United States (0.04)
- Asia > Japan
- Genre:
- Research Report > New Finding (1.00)
- Industry:
- Energy > Renewable (0.68)
- Health & Medicine > Health Care Technology (0.67)
- Technology: