Quantifying Robot Localization Safety: A New Integrity Monitoring Method for Fixed-Lag Smoothing

Abstract

Localization safety, or integrity risk, is the probability of undetected localization failures and a common aviation performance metric used to verify a minimum accuracy requirement. As autonomous robots become more common, applying integrity risk metrics will be necessary to verify localization performance. This letter introduces a new method, solution separation, to quantify landmark-based mobile robot localization safety for fixed-lag smoothing estimators and compares it's computation time and fault detection capabilities to achi-squared integrity monitoring method. Results show that solution separation is more computationally efficient and results in a tighter upper-bound on integrity risk when few measurements are included, which makes it the method of choice for lightweight, safety-critical applications such as UAVs. Conversely, chi-squared requires more computing resources but performs better when more measurements are included, making the method more appropriate for high performance computing platforms such as autonomous vehicles.