揭示了影像导航中误差逐级放大的系统性风险，为安全导航设计提供新框架。
System-Level Error Propagation and Tail-Risk Amplification in Reference-Based Robotic Navigation
- 建立统一误差传播模型，分析安装偏差如何在多阶段感知中累积放大。
- 发现旋转安装误差是主导因素，其影响远超同量级平移误差。
- 适用于医疗机器人等高安全性要求的实时导航系统可靠性评估。
基于图像的机器人导航系统常依赖参考式的几何感知流程，通过多阶段估计构建精确空间地图。在双平面X射线引导导航中，此类流程因具备实时性与几何可解释性而广泛应用。然而，导航可靠性可能受制于一种被忽视的系统级失效机制：感知阶段引入的安装结构扰动会沿感知重建链逐步放大，并主导执行层面的误差与尾部风险行为。本文从系统层面研究该机制，提出统一的误差传播建模框架，刻画安装引起的结构扰动如何通过双平面成像、投影矩阵估计、三角测量与坐标映射过程，与像素级观测噪声耦合传播。结合一阶解析不确定性传播与蒙特卡洛仿真，分析主要敏感通道并量化均值之外的最坏情况误差表现。结果表明，旋转安装误差是系统级误差放大的主因，而同量级平移错位在典型双平面几何下作用较弱。真实双平面X射线台架实验进一步验证了预测的放大趋势在实际成像条件下依然成立。这些发现揭示了基于参考的多阶段几何感知流程的结构性局限，并为安全关键型机器人导航系统的可靠性分析与风险感知设计提供了理论框架。
原文摘要 · Abstract (English)
Image guided robotic navigation systems often rely on reference based geometric perception pipelines, where accurate spatial mapping is established through multi stage estimation processes. In biplanar X ray guided navigation, such pipelines are widely used due to their real time capability and geometric interpretability. However, navigation reliability can be constrained by an overlooked system level failure mechanism in which installation induced structural perturbations introduced at the perception stage are progressively amplified along the perception reconstruction execution chain and dominate execution level error and tail risk behavior. This paper investigates this mechanism from a system level perspective and presents a unified error propagation modeling framework that characterizes how installation induced structural perturbations propagate and couple with pixel level observation noise through biplanar imaging, projection matrix estimation, triangulation, and coordinate mapping. Using first order analytic uncertainty propagation and Monte Carlo simulations, we analyze dominant sensitivity channels and quantify worst case error behavior beyond mean accuracy metrics. The results show that rotational installation error is a primary driver of system level error amplification, while translational misalignment of comparable magnitude plays a secondary role under typical biplanar geometries. Real biplanar X ray bench top experiments further confirm that the predicted amplification trends persist under realistic imaging conditions. These findings reveal a broader structural limitation of reference based multi stage geometric perception pipelines and provide a framework for system level reliability analysis and risk aware design in safety critical robotic navigation systems.
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