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.

翻译：部署于工业与操作环境中的扩展现实系统依赖视觉-惯性里程计实现连续的六自由度位姿跟踪，然而这些环境往往存在偏离理想假设的感知条件。尽管如此，当前多数VIO评估主要关注标称传感器性能，导致对实际运行条件下持续传感器退化影响的认知尚不充分。本文通过受控实验研究退化感知条件下的VIO行为，系统考察了不同运行状态下影响视觉与惯性模态的故障类型。通过系统性故障注入与定量评估，我们发现故障影响存在显著不对称性：影响视觉感知的退化通常仅导致厘米量级的有限位姿误差，而影响惯性感知的退化则可能引发显著更大的轨迹偏差，在某些情况下可达数百至数千米量级。这些发现表明，在面向实际工业场景的XR系统评估与设计中，应更加重视惯性测量单元的可靠性。