Stability and robustness analysis tools for marine robot localization and mapping applications

Abstract

The aim of this analysis is to explore the fundamental stability issues of a robotic vehicle carrying out localization, mapping, and feedback control in a perturbation-filled environment. Motivated by the application of an ocean vehicle performing an autonomous ship hull inspection, a planar vehicle model performs localization using point features from a given map. Cases in which the agent must update the map are also considered. The stability of the marine robot controller and estimator duo is investigated using a pair of theorems requiring boundedness and convergence of the transition matrix Euclidean norm. These theorems yield a stability test for the feedback controller. Perturbations are then considered using a theorem on the convergence on the perturbed system transition matrix, yielding a robustness test for the estimator. Together, these tests form a set of tools which can be used in planning and evaluating the robustness of marine vehicle survey trajectories, which is demonstrated through experiment. An augmented A* kinodynamic path-planning algorithm is then implemented to search the control input space for the globally robustness-optimal survey trajectory.