Detection and prediction of near-term state estimation degradation via online nonlinear observability analysis

Abstract

We pursue the formulation of an online methodology to detect future motions that can result in degraded perceptual information leading to state estimation inaccuracy and degeneracy. As autonomous systems and first responders engage in an unknown environment, real-time perceptual and state estimation systems enable accurate localization with respect to the environment. We propose a methodology leveraging numerical techniques in nonlinear observability analysis to enable online detection of degenerate conditions and the computation of motions leading to degradation in localization performance. The approach is specialized to a representative monocular visual-inertial state estimation formulation and evaluated through simulation and experiments to assess the performance of the system to both detect degenerate conditions and identify motions that may lead to future degradation or the failure of the localization system.