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Visual Attitude Estimation for Low-Cost Personal Remote Sensing Systems

[+] Author Affiliations
Tobias Fromm, Long Di, YangQuan Chen

Utah State University, Logan, UT

Holger Voos

University of Luxembourg, Luxembourg, Luxembourg

Paper No. DETC2011-47742, pp. 901-908; 8 pages
doi:10.1115/DETC2011-47742
From:
  • ASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 3: 2011 ASME/IEEE International Conference on Mechatronic and Embedded Systems and Applications, Parts A and B
  • Washington, DC, USA, August 28–31, 2011
  • Conference Sponsors: Design Engineering Division and Computers and Information in Engineering Division
  • ISBN: 978-0-7918-5480-8
  • Copyright © 2011 by ASME

abstract

Remote Sensing using unmanned aerial vehicles (UAV) is gathering a lot of attention at the moment by researchers and developers, especially in terms of low-cost aircrafts which still maintain sufficient accuracy and performance. This paper introduces a low-cost approach to increase airworthiness by using a forward-looking camera to estimate the attitude of a UAV. It not only focuses on using machine learning to classify ground and sky, but also uses image processing and software engineering methods to make it fault-tolerant and really applicable on a miniature UAV. Additionally, it is able to interface with an autopilot framework to being used productively on flight missions.

Copyright © 2011 by ASME

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