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.