Low-altitude road following using strap-down cameras on miniature air vehicles
This paper addresses the problem of autonomously maneuvering a miniature air vehicle (MAV) to follow a road using computer vision as the primary guidance sensor. We focus on low-altitude flight with the objective of maximizing the pixel density of the road in the image. The airframe is assumed to be a bank-to-turn fixed-wing MAV with a downward-looking strap-down camera. The road is identified in the image using HSV classification, flood-fill operations, and connected-component analysis. The main contribution of the paper is the derivation of explicit roll-angle and altitude-above-ground-level (AGL) constraints that guarantee that the road will remain in the footprint of the camera, assuming a flat earth. The effectiveness of our approach is demonstrated through high fidelity simulation and through flight results. (C) 2010 Elsevier Ltd. All rights reserved.
road following computer vision unmanned air vehicle autonomous navigation