State Estimation for Indoor and Outdoor Operation with a Micro-Aerial Vehicle

Abstract

In this work, we detail a methodology for estimating the state of a microaerial vehicle (MAV) as it transitions between different operating environments with varying applicable sensors. We ensure that the estimate is smooth and continuous throughout and provide an associated quality measure of the state estimate. We address the challenge of maintaining consistency between local and global measurements and propose a strategy to recursively estimate the transform between different coordinate frames. We close with experiments that validate the approach and the resulting performance as a MAV navigates between mixed indoor and outdoor environments.