Enhancing 3D Visual Odometry with Single-Camera Stereo Omnidirectional Systems

We explore low-cost solutions for efficiently improving the 3D pose estimation problem of a single camera moving in an unfamiliar environment. The visual odometry (VO) task -- as it is called when using computer vision to estimate egomotion -- is of particular interest to mobile robots as well as humans with visual impairments. The payload capacity of small robots like micro-aerial vehicles (drones) requires the use of portable perception equipment, which is constrained by size, weight, energy consumption, and processing power. Using a single camera as the passive sensor for the VO task satisfies these requirements, and it motivates the proposed solutions presented in this thesis. To deliver the portability goal with a single off-the-shelf camera, we have taken two approaches: The first one, and the most extensively studied here, revolves around an unorthodox camera-mirrors configuration (catadioptrics) achieving a stereo omnidirectional system (SOS). The second approach relies on expanding the visual features from the scene into higher dimensionalities to track the pose of a conventional camera in a photogrammetric fashion. The first goal has many interdependent challenges, which we address as part of this thesis: SOS design, projection model, adequate calibration procedure, and application to VO. We show several practical advantages for the single-camera SOS due to its complete 360-degree stereo views, that other conventional 3D sensors lack due to their limited field of view. Since our omnidirectional stereo (omnistereo) views are captured by a single camera, a truly instantaneous pair of panoramic images is possible for 3D perception tasks. Finally, we address the VO problem as a direct multichannel tracking approach, which increases the pose estimation accuracy of the baseline method (i.e., using only grayscale or color information) under the photometric error minimization as the heart of the “direct” tracking algorithm. Currently, this solution has been tested on standard monocular cameras, but it could also be applied to an SOS. We believe the challenges that we attempted to solve have not been considered previously with the level of detail needed for successfully performing VO with a single camera as the ultimate goal in both real-life and simulated scenes

Modélisation et développement d'une plateforme intelligente pour la capture d'images panoramiques cylindriques

In most robotic applications, vision systems can significantly improve the perception of the environment. The panoramic view has particular attractions because it allows omnidirectional perception. However, it is rarely used because the methods that provide panoramic views also have significant drawbacks. Most of these omnidirectional vision systems involve the combination of a matrix camera and a mirror, rotating matrix cameras or a wide angle lens. The major drawbacks of this type of sensors are in the great distortions of the images and the heterogeneity of the resolution. Some other methods, while providing homogeneous resolutions, also provide a huge data flow that is difficult to process in real time and are either too slow or lacking in precision. To address these problems, we propose a smart panoramic vision system that presents technological improvements over rotating linear sensor methods. It allows homogeneous 360 degree cylindrical imaging with a resolution of 6600 × 2048 pixels and a precision turntable to synchronize position with acquisition. We also propose a solution to the bandwidth problem with the implementation of a feature etractor that selects only the invariant feaures of the image in such a way that the camera produces a panoramic view at high speed while delivering only relevant information. A general geometric model has been developped has been developped to describe the image formation process and a caligration method specially designed for this kind of sensor is presented. Finally, localisation and structure from motion experiments are described to show a practical use of the system in SLAM applications.Dans la plupart des applications de robotique, un système de vision apporte une amélioration significative de la perception de l’environnement. La vision panoramique est particulièrement intéressante car elle rend possible une perception omnidirectionnelle. Elle est cependant rarement utilisée en pratique à cause des limitations technologiques découlant des méthodes la permettant. La grande majorité de ces méthodes associent des caméras, des miroirs, des grands angles et des systèmes rotatifs ensembles pour créer des champs de vision élargis. Les principaux défauts de ces méthodes sont les importantes distorsions des images et l’hétérogénéité de la résolution. Certaines autres méthodes permettant des résolutions homogènes, prodiguent un flot de données très important qui est difficile à traiter en temps réel et sont soit trop lents soit manquent de précision. Pour résoudre ces problèmes, nous proposons la réalisation d’une caméra panoramique intelligente qui présente plusieurs améliorations technologiques par rapport aux autres caméras linéaires rotatives. Cette caméra capture des panoramas cylindriques homogènes avec une résolution de 6600 × 2048 pixels. La synchronisation de la capture avec la position angulaire est possible grâce à une plateforme rotative de précision. Nous proposons aussi une solution au problème que pose le gros flot de données avec l’implémentation d’un extracteur de primitives qui sélectionne uniquement les primitives invariantes des images pour donner un système panoramique de vision qui ne transmet que les données pertinentes. Le système a été modélisé et une méthode de calibrage spécifiquement conçue pour les systèmes cylindriques rotatifs est présentée. Enfin, une application de localisation et de reconstruction 3D est décrite pour montrer une utilisation pratique dans une application de type Simultaneous Localization And Mapping ( SLAM )