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Real Time UAV Altitude, Attitude and Motion Estimation form Hybrid Stereovision

Abstract : Knowledge of altitude, attitude and motion is essential for an Unmanned Aerial Vehicle during crit- ical maneuvers such as landing and take-off. In this paper we present a hybrid stereoscopic rig composed of a fisheye and a perspective camera for vision-based navigation. In contrast to classical stereoscopic systems based on feature matching, we propose methods which avoid matching between hybrid views. A plane-sweeping approach is proposed for estimating altitude and de- tecting the ground plane. Rotation and translation are then estimated by decoupling: the fisheye camera con- tributes to evaluating attitude, while the perspective camera contributes to estimating the scale of the trans- lation. The motion can be estimated robustly at the scale, thanks to the knowledge of the altitude. We propose a robust, real-time, accurate, exclusively vision-based approach with an embedded C++ implementation. Although this approach removes the need for any non-visual sensors, it can also be coupled with an Inertial Measurement Unit.
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Damien Eynard, Pascal Vasseur, Cédric Demonceaux, Vincent Fremont. Real Time UAV Altitude, Attitude and Motion Estimation form Hybrid Stereovision. Autonomous Robots, Springer Verlag, 2012, 33 (1-2), pp.157-172. ⟨10.1007/s10514-012-9285-0⟩. ⟨hal-00716093⟩

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