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Localisation et cartographie simultanées par ajustement de faisceaux local : propagation d'erreurs et réduction de la dérive à l'aide d'un odomètre

Abstract : The present work is about localisation of vehicle using computer vision methods. In this context, the camera trajectory and the 3D structure of the scene is estimated by a monocular visual odometry method based on local bundle adjustment. This thesis contributions are some improvements of this method. The uncertainty of the estimated position was not provided by the local bundle adjustment method. Indeed, this uncertainty is crucial in a multi-sensorial fusion system to use optimally the estimated position. A study of the uncertainty propagation in this visual odometry method has been done and an uncertainty calculus method has been designed to comply with real time performance. By the way, monocular visual localisation methods are known to have serious drift issues on long trajectories (some kilometers). This error mainly comes from bad propagation of the scale factor. To limit this drift and improve the quality of the given position, we proposed two data fusion methods between an odometer and the visual method. Finally, the two improvements presented here allow us to use visual localisation method in real urban environment on long trajectories under real time constraints.
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Alexandre Eudes. Localisation et cartographie simultanées par ajustement de faisceaux local : propagation d'erreurs et réduction de la dérive à l'aide d'un odomètre. Autre. Université Blaise Pascal - Clermont-Ferrand II, 2011. Français. ⟨NNT : 2011CLF22112⟩. ⟨tel-00662438⟩

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