Relative navigation of autonomous GPS-degraded micro air vehicles

Abstract

Unlike many current navigation approaches for micro air vehicles, the relative navigation (RN) framework presented in this paper ensures that the filter state remains observable in GPS-denied environments by working with respect to a local reference frame. By subtly restructuring the problem, RN ensures that the filter uncertainty remains bounded, consistent, and normally-distributed, and insulates flight-critical estimation and control processes from large global updates. This paper thoroughly outlines the RN framework and demonstrates its practicality with several long flight tests in unknown GPS-denied and GPS-degraded environments. The relative front end is shown to produce low-drift estimates and smooth, stable control while leveraging off-the-shelf algorithms. The system runs in real time with onboard processing, fuses a variety of vision sensors, and works indoors and outdoors without requiring special tuning for particular sensors or environments. RN is shown to produce globally-consistent, metric, and localized maps by incorporating loop closures and intermittent GPS measurements.