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Estimation de mouvement d'un drone à partir d'un capteur stéréo hybride

Abstract : Motion and velocity are two of the most important parameters to be known for an Unmanned Aerial Vehicle (UAV) especially during critical maneuvers such as landing or steady flight. In this paper, we present mixed stereoscopic vision system made of a fish-eye camera and a perspective camera for motion estimation. Contrary to classical stereoscopic systems based on feature matching between cameras, we propose an algorithm which tracks and exploits points in each camera independently. The omnidirectional view estimates the orientation of the motion while the perspective view contribute to estimate the scale of the translation and brings accuracy. By fusing points tracked in each camera and knowing the rotation between two consecutive positions, we can estimate robustly the translation and the velocity using the two-points algorithm. Then motion is filtered by Kalman filter to remove bad estimations. By experimental results on UAV, we validate the approach.
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Submitted on : Monday, June 6, 2011 - 1:20:16 AM
Last modification on : Sunday, June 26, 2022 - 12:42:33 AM
Long-term archiving on: : Sunday, December 4, 2016 - 6:44:45 AM


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  • HAL Id : inria-00598255, version 1


Damien Eynard, Pascal Vasseur, Cédric Demonceaux, Vincent Fremont. Estimation de mouvement d'un drone à partir d'un capteur stéréo hybride. ORASIS - Congrès des jeunes chercheurs en vision par ordinateur, INRIA Grenoble Rhône-Alpes, Jun 2011, Praz-sur-Arly, France. ⟨inria-00598255⟩



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