| Type of Document |
Master's Thesis |
| Author |
Parks, Matthew Raymond
|
| Author's Email Address |
maparks@vt.edu |
| URN |
etd-07012006-011840 |
| Title |
Vision-Based Self-Motion Estimation in a Fixed-Wing Aerial Vehicle |
| Degree |
Master of Science |
| Department |
Electrical and Computer Engineering |
| Advisory Committee |
| Advisor Name |
Title |
| Abbott, A. Lynn |
Committee Chair |
| Kachroo, Pushkin |
Committee Member |
| Wyatt, Christopher L. |
Committee Member |
|
| Keywords |
- Optic Flow
- Computer Vision
- Motion Estimation
- Matching
- Feature Tracking
|
| Date of Defense |
2006-01-20 |
| Availability |
unrestricted |
Abstract
This paper describes a complete algorithm to estimate the motion of a fixed-wing aircraft
given a series of digitized flight images. The algorithm was designed for fixed-wing
aircraft because carefully procured flight images and corresponding navigation data were
available to us for testing. After image pre-processing, optic flow data is determined by
automatically finding and tracking good features between pairs of images. The image
coordinates of matched features are then processed by a rigid-object linear optic
flow-motion estimation algorithm. Input factors are weighed to provide good testing
techniques. Error analysis is performed with simulation data keeping these factors in mind
to determine the effectiveness of the optic flow algorithm. The output of this program is
an estimate of rotation and translation of the imaged environment in relation to the camera,
and thereby the airplane. Real flight images from NASA test flights are used to confirm the
accuracy of the algorithm. Where possible, the estimated motion parameters are compared
with recorded flight instrument data to confirm the correctness of the algorithm. Results
show that the algorithm is accurate to within a degree provided that enough optic flow
feature points are tracked.
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56K Modem |
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etd.pdf |
2.00 Mb |
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