Natural Landmark-based Monocular Localization for MAVs

Highly accurate localization of a micro aerial vehicle (MAV) with respect to a scene is important for a wide range of applications, in particular surveillance and inspection. Most existing approaches to visual localization focus on indoor environments, while such tasks require outdoor navigation. Within this work, we introduce a novel algorithm for monocular visual localization for MAVs based on the concept of virtual views in 3D space. Under the assumption that significant parts of the scene do not alter their geometry and serve as natural landmarks, the accuracy of our visual approach outperforms consumer grade GPS systems. In an experimental setup we compare our approach to a state-of-the-art visual SLAM algorithm and evaluate the performance by geometric validation from an observer's view. As our method directly allows global registration, it is neither prone to drift nor bias. This makes it well suited for long-term autonomous navigation.