[论文解读] System-Level Error Propagation and Tail-Risk Amplification in Reference-Based Robotic Navigation

Ning Hu, Maochen Li+1 more|arXiv (Cornell University)|Feb 8, 2026

Robotics and Sensor-Based Localization被引用 0

一句话总结

论文提出一个统一框架，用于建模安装引起的扰动在双平面 X 射线引导的机器人导航中，通过多阶段基于参考的感知管线传播，量化系统级误差放大和尾部风险，超越平均精度。

ABSTRACT

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.

研究动机与目标

• 为安全关键机器人导航中的基于参考的多阶段几何感知的可靠性分析提供动力。
• 开发一个统一的一阶不确定性传播框架，用于安装引起的扰动与像素级噪声的相互作用。
• 识别主导的敏感性通道并量化超出平均精度的最坏情形误差行为。
• 使用真实的双平面 X 射线台式实验验证框架，确认放大趋势。
• 为具有风险意识、可靠的导航系统提供设计指南。

提出的方法

• 构建一个系统级误差传播模型，将安装扰动通过管线阶段（双平面成像、投影矩阵估计、三角测量、坐标映射）与像素级噪声耦合。
• 使用一阶解析不确定性传播推导敏感性通道。
• 进行蒙特卡罗仿真以表征误差放大和尾部风险行为。
• 分离放大主驱动因素，比较旋转错位与平移错位的影响。
• 使用真实的双平面 X 射线成像条件的台式实验验证预测。

实验结果

研究问题

• RQ1 安装引起的扰动在基于参考的导航管线中传播的主导系统级通道是什么？
• RQ2 安装扰动如何与像素级噪声相互作用以影响尾部风险和最坏情形误差？
• RQ3 在典型的双平面几何下，旋转 vs 平移错位对误差放大的贡献有多大？
• RQ4 真实世界的台式实验是否与所提传播与放大框架相符？

主要发现

• 旋转安装误差被确定为系统级误差放大的主要驱动因素。
• 在典型的双平面几何下，等量级的平移错位发挥次要作用。
• 框架预测的误差放大趋势在现实成像条件下的台式实验中得到验证。
• 本研究揭示了多阶段几何感知管线的结构性局限性，并为风险意识设计提供参考。