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Vision-based Target Geo-location using a Fixed-wing Miniature Air Vehicle

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Abstract

This paper presents a method for determining the GPS location of a ground-based object when imaged from a fixed-wing miniature air vehicle (MAV). Using the pixel location of the target in an image, measurements of MAV position and attitude, and camera pose angles, the target is localized in world coordinates. The main contribution of this paper is to present four techniques for reducing the localization error. In particular, we discuss RLS filtering, bias estimation, flight path selection, and wind estimation. The localization method has been implemented and flight tested on BYU’s MAV testbed and experimental results are presented demonstrating the localization of a target to within 3 m of its known GPS location.

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Authors and Affiliations

  1. Magicc Lab, Brigham Young University, Provo, UT, 84602, USA

    D. Blake Barber, Timothy W. McLain, Randal W. Beard & Clark N. Taylor

  2. Scientific Systems Company, Inc., Woburn, MA, 01801, USA

    Joshua D. Redding

Authors
  1. D. Blake Barber
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  2. Joshua D. Redding
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  3. Timothy W. McLain
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  4. Randal W. Beard
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  5. Clark N. Taylor
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Correspondence to Randal W. Beard.

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Barber, D.B., Redding, J.D., McLain, T.W. et al. Vision-based Target Geo-location using a Fixed-wing Miniature Air Vehicle. J Intell Robot Syst 47, 361–382 (2006). https://doi.org/10.1007/s10846-006-9088-7

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  • DOI: https://doi.org/10.1007/s10846-006-9088-7

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