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

Fuente: arXiv
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Autori principali: Masuhr, Christian, Koch, Julian, Schüppstuhl, Thorsten
Natura: Preprint
Pubblicazione: 2025
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author Masuhr, Christian
Koch, Julian
Schüppstuhl, Thorsten
author_facet Masuhr, Christian
Koch, Julian
Schüppstuhl, Thorsten
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2509_05391
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Evaluating Magic Leap 2 Tool Tracking for AR Sensor Guidance in Industrial Inspections
Masuhr, Christian
Koch, Julian
Schüppstuhl, Thorsten
Robotics
Human-Computer Interaction
Multimedia
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.
title Evaluating Magic Leap 2 Tool Tracking for AR Sensor Guidance in Industrial Inspections
topic Robotics
Human-Computer Interaction
Multimedia
url https://arxiv.org/abs/2509.05391