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Theses

Système de Perception Visuel Embarqué appliqué à la Navigation Sûre de Véhicules

Abstract : This thesis addresses the problem of obstacle avoidance for semi- and autonomous terrestrial platforms in dynamic and unknown environments. Based on monocular vision, it proposes a set of tools that continuously monitors the way forward, proving appropriate road informations in real time. A horizon finding algorithm was developed to sky removal. This algorithm generates the region of interest from a dynamic threshold search method, allowing to dynamically investigate only a small portion of the image ahead of the vehicle, in order to road and obstacle detection. A free-navigable area is therefore represented from a multimodal 2D drivability road image. This multimodal result enables that a level of safety can be selected according to the environment and operational context. In order to reduce processing time, this thesis also proposes an automatic image discarding criteria. Taking into account the temporal coherence between consecutive frames, a new Dynamic Power Management methodology is proposed and applied to a robotic visual machine perception, which included a new environment observer method to optimize energy consumption used by a visual machine. This proposal was tested in different types of image texture (road surfaces), which includes free-area detection, reactive navigation and time-to-collision estimation. A remarkable characteristic of these methodologies is its independence of the image acquiring system and of the robot itself. This real-time perception system has been evaluated from different test-banks and also from real data obtained by two intelligent platforms. In semi-autonomous tasks, tests were conducted at speeds above 100 Km/h. Autonomous displacements were also carried out successfully. The algorithms presented here showed an interesting robustness.
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Submitted on : Monday, June 3, 2013 - 4:03:15 PM
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Arthur de Miranda Neto. Système de Perception Visuel Embarqué appliqué à la Navigation Sûre de Véhicules. Traitement des images [eess.IV]. Université de Technologie de Compiègne; Universidade de Campinas (UNICAMP), 2011. Français. ⟨tel-00829646⟩

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