Monocular vision based navigation in GPS-denied riverine environments

This paper presents a new method to estimate the range and bearing of landmarks and solve the simultaneous localization and mapping (SLAM) problem. The proposed ranging and SLAM algorithms have application to a micro aerial vehicle (MAV) flying through riverine environments which occasionally involve heavy foliage and forest canopy. Monocular vision navigation has merits in MAV applications since it is lightweight and provides abundant visual cues of the environment in comparison to other ranging methods. In this paper, we suggest a monocular vision strategy incorporating image segmentation and epipolar geometry to extend the capability of the ranging method to unknown outdoor environments. The validity of our proposed method is verified through experiments in a river-like environment.