理解工业扩展现实中传感器追踪的脆弱性 / Understanding Sensor Vulnerabilities in Industrial XR Tracking
1️⃣ 一句话总结
这项研究发现,在工业扩展现实系统中,惯性传感器的性能下降比视觉传感器更容易导致严重的定位漂移,因此设计和评估时应更重视惯性传感器的可靠性。
Extended Reality (XR) systems deployed in industrial and operational settings rely on Visual--Inertial Odometry (VIO) for continuous six-degree-of-freedom pose tracking, yet these environments often involve sensing conditions that deviate from ideal assumptions. Despite this, most VIO evaluations emphasize nominal sensor behavior, leaving the effects of sustained sensor degradation under operational conditions insufficiently understood. This paper presents a controlled empirical study of VIO behavior under degraded sensing, examining faults affecting visual and inertial modalities across a range of operating regimes. Through systematic fault injection and quantitative evaluation, we observe a pronounced asymmetry in fault impact where degradations affecting visual sensing typically lead to bounded pose errors on the order of centimeters, whereas degradations affecting inertial sensing can induce substantially larger trajectory deviations, in some cases reaching hundreds to thousands of meters. These observations motivate greater emphasis on inertial reliability in the evaluation and design of XR systems for real-life industrial settings.
理解工业扩展现实中传感器追踪的脆弱性 / Understanding Sensor Vulnerabilities in Industrial XR Tracking
这项研究发现,在工业扩展现实系统中,惯性传感器的性能下降比视觉传感器更容易导致严重的定位漂移,因此设计和评估时应更重视惯性传感器的可靠性。
源自 arXiv: 2602.14413