Low-Altitude Road Following, Using Strap-Down Cameras on Miniature Aerial Vehicles

Miniature air vehicles (MAVs) are particularly well suited for short-distance, over-the-horizon, low-altitude surveillance and reconnaissance tasks. New camera and battery technologies have greatly increased a MAVs potential for these tasks. This thesis focuses on aerial surveillance of borders and...

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Main Author: Egbert, Joseph M.
Format: Others
Published: BYU ScholarsArchive 2007
Subjects:
MAV
Online Access:https://scholarsarchive.byu.edu/etd/1558
https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=2557&context=etd
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spelling ndltd-BGMYU2-oai-scholarsarchive.byu.edu-etd-25572021-09-12T05:00:59Z Low-Altitude Road Following, Using Strap-Down Cameras on Miniature Aerial Vehicles Egbert, Joseph M. Miniature air vehicles (MAVs) are particularly well suited for short-distance, over-the-horizon, low-altitude surveillance and reconnaissance tasks. New camera and battery technologies have greatly increased a MAVs potential for these tasks. This thesis focuses on aerial surveillance of borders and roads, where a strap-down camera is used in-the-loop to track a border or road pathway. It is assumed that quality tracking requires that the pathway always remain in the footprint of the camera. The objective of this thesis is to explore roll-angle and altitude-above-ground-level constraints imposed on a bank-to-turn MAV due to the requirement to keep the pathway in the footprint of a downward-looking strap-down camera. This thesis derives the required altitude to maintain the pathway in the footprint of the camera and associated bank-angle constraints. Constraints are derived for both roads whose geometry is unknown a priori and roads with known geometry obtained from digital elevation map (DEM) data. MAV geometry and camera localization are used to derive these constraints. The thesis also discusses simple computer vision techniques for pathway following and a corresponding guidance law. The pixels of the captured color video are statistically classified into road and non-road components. Standard computer vision functions are used to eliminate classification noise and obtain a road heading direction. The effectiveness of the result is explored using a high fidelity simulator. Flight test results on small UAVs demonstrate the practicality of the road-following method. 2007-11-30T08:00:00Z text application/pdf https://scholarsarchive.byu.edu/etd/1558 https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=2557&context=etd http://lib.byu.edu/about/copyright/ Theses and Dissertations BYU ScholarsArchive MAGICC road following MAV image-directed control miniature air vehicles Electrical and Computer Engineering
collection NDLTD
format Others
sources NDLTD
topic MAGICC
road following
MAV
image-directed control
miniature air vehicles
Electrical and Computer Engineering
spellingShingle MAGICC
road following
MAV
image-directed control
miniature air vehicles
Electrical and Computer Engineering
Egbert, Joseph M.
Low-Altitude Road Following, Using Strap-Down Cameras on Miniature Aerial Vehicles
description Miniature air vehicles (MAVs) are particularly well suited for short-distance, over-the-horizon, low-altitude surveillance and reconnaissance tasks. New camera and battery technologies have greatly increased a MAVs potential for these tasks. This thesis focuses on aerial surveillance of borders and roads, where a strap-down camera is used in-the-loop to track a border or road pathway. It is assumed that quality tracking requires that the pathway always remain in the footprint of the camera. The objective of this thesis is to explore roll-angle and altitude-above-ground-level constraints imposed on a bank-to-turn MAV due to the requirement to keep the pathway in the footprint of a downward-looking strap-down camera. This thesis derives the required altitude to maintain the pathway in the footprint of the camera and associated bank-angle constraints. Constraints are derived for both roads whose geometry is unknown a priori and roads with known geometry obtained from digital elevation map (DEM) data. MAV geometry and camera localization are used to derive these constraints. The thesis also discusses simple computer vision techniques for pathway following and a corresponding guidance law. The pixels of the captured color video are statistically classified into road and non-road components. Standard computer vision functions are used to eliminate classification noise and obtain a road heading direction. The effectiveness of the result is explored using a high fidelity simulator. Flight test results on small UAVs demonstrate the practicality of the road-following method.
author Egbert, Joseph M.
author_facet Egbert, Joseph M.
author_sort Egbert, Joseph M.
title Low-Altitude Road Following, Using Strap-Down Cameras on Miniature Aerial Vehicles
title_short Low-Altitude Road Following, Using Strap-Down Cameras on Miniature Aerial Vehicles
title_full Low-Altitude Road Following, Using Strap-Down Cameras on Miniature Aerial Vehicles
title_fullStr Low-Altitude Road Following, Using Strap-Down Cameras on Miniature Aerial Vehicles
title_full_unstemmed Low-Altitude Road Following, Using Strap-Down Cameras on Miniature Aerial Vehicles
title_sort low-altitude road following, using strap-down cameras on miniature aerial vehicles
publisher BYU ScholarsArchive
publishDate 2007
url https://scholarsarchive.byu.edu/etd/1558
https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=2557&context=etd
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