Stereovision Correction Using Modal Analysis

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Date
2010-04-07
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Publisher
Virginia Tech
Abstract

Presently, aerial photography remains a popular method for surveillance of landscapes, and its uses continually grow as it is used to monitor trends in areas such as plant distribution and urban construction. The use of computer vision, or more specifically stereo vision, is one common method of gathering this information. By mounting a stereo vision system on the wings of an unmanned aircraft it becomes very useful tool. This technique however, becomes less accurate as stereo vision baselines become longer, aircraft wing spans are increased, and aircraft wings become increasingly flexible. Typically, ideal stereo vision systems involve stationary cameras with parallel fields of view. For an operational aircraft with a stereo vision system installed, stationary cameras can not be expected because the aircraft will experience random atmospheric turbulence in the form of gusts that will excite the dominate frequencies of the aircraft.

A method of stereo image rectification has been developed for cases where cameras that will be allowed to deflect on the wings of an fixed wing aircraft that is subjected to random excitation. The process begins by developing a dynamic model the estimates the behavior of a flexible stereo vision system and corrects images collected at maximum deflection. Testing of this method was performed on a flexible stereo vision system subjected to resonance excitation where a reduction in stereo vision distance error is shown. Successful demonstration of this ability is then repeated on a flying wing aircraft by the using a modal survey to understand its behavior. Finally, the flying wing aircraft is subjected to random excitation and a least square fit of the random excitation signal is used to determine points of maximum deflection suitable for stereo image rectification. Using the same techniques for image rectification in resonance excitation, significant reductions in stereo distance errors are shown.

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Keywords
Stereo Vision, Modal Analysis, Drone aircraft, Photogrammetry, Gust Response
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