Evaluating Magic Leap 2 Controller Tracking for Sensor Tool Guidance in AR-Based Industrial Inspections
Year: 2025
Type: conference-paper
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) controller’s 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 controller’s suitability for the inspection use case and similar industrial sensor-based AR guidance tasks.
Institution: Hamburg University of Technology
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4415058841