System-Level Error Propagation and Tail-Risk Amplification in Reference-Based Robotic Navigation

TL;DR

This paper analyzes how installation errors in reference-based robotic navigation systems are amplified through the perception pipeline, affecting system reliability and highlighting the importance of system-level error modeling.

Contribution

It introduces a unified error propagation framework for understanding how structural perturbations influence navigation accuracy and tail risk in biplanar X-ray guided systems.

Findings

Rotational installation errors significantly amplify system errors.

Translational misalignments have a secondary impact under typical conditions.

Experimental results confirm the predicted error amplification trends.

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.