Robust Attitude Estimation with Catadioptric Vision

International audienceAttitude (roll and pitch) is an essential data for the navigation of a UAV. Rather than using inertial sensors, we propose a catadioptric vision system allowing a fast, robust and accurate estimation of these angles. We show that the optimization of a sky/ground partitioning criterion associated with the specific geometric characteristics of the catadioptric sensor provides very interesting results. Experimental results obtained on real sequences are presented and compared with inertial sensors measures

Dynamic Programming and Skyline Extraction in Catadioptric Infrared Images

International audienceUnmanned Aerial Vehicles (UAV) are the subject of an increasing interest in many applications and a key requirement for autonomous navigation is the attitude/position stabilization of the vehicle. Some previous works have suggested using catadioptric vision, instead of traditional perspective cameras, in order to gather much more information from the environment and therefore improve the robustness of the UAV attitude/position estimation. This paper belongs to a series of recent publications of our research group concerning catadioptric vision for UAVs. Currently, we focus on the extraction of skyline in catadioptric images since it provides important information about the attitude/position of the UAV. For example, the DEM-based methods can match the extracted skyline with a Digital Elevation Map (DEM) by process of registration, which permits to estimate the attitude and the position of the camera. Like any standard cameras, catadioptric systems cannot work in low luminosity situations because they are based on visible light. To overcome this important limitation, in this paper, we propose using a catadioptric infrared camera and extending one of our methods of skyline detection towards catadioptric infrared images. The task of extracting the best skyline in images is usually converted in an energy minimization problem that can be solved by dynamic programming. The major contribution of this paper is the extension of dynamic programming for catadioptric images using an adapted neighborhood and an appropriate scanning direction. Finally, we present some experimental results to demonstrate the validity of our approach

Combining omnidirectional vision with polarization vision for robot navigation

La polarisation est le phénomène qui décrit les orientations des oscillations des ondes lumineuses qui sont limitées en direction. La lumière polarisée est largement utilisée dans le règne animal,à partir de la recherche de nourriture, la défense et la communication et la navigation. Le chapitre (1) aborde brièvement certains aspects importants de la polarisation et explique notre problématique de recherche. Nous visons à utiliser un capteur polarimétrique-catadioptrique car il existe de nombreuses applications qui peuvent bénéficier d'une telle combinaison en vision par ordinateur et en robotique, en particulier pour l'estimation d'attitude et les applications de navigation. Le chapitre (2) couvre essentiellement l'état de l'art de l'estimation d'attitude basée sur la vision.Quand la lumière non-polarisée du soleil pénètre dans l'atmosphère, l'air entraine une diffusion de Rayleigh, et la lumière devient partiellement linéairement polarisée. Le chapitre (3) présente les motifs de polarisation de la lumière naturelle et couvre l'état de l'art des méthodes d'acquisition des motifs de polarisation de la lumière naturelle utilisant des capteurs omnidirectionnels (par exemple fisheye et capteurs catadioptriques). Nous expliquons également les caractéristiques de polarisation de la lumière naturelle et donnons une nouvelle dérivation théorique de son angle de polarisation.Notre objectif est d'obtenir une vue omnidirectionnelle à 360 associée aux caractéristiques de polarisation. Pour ce faire, ce travail est basé sur des capteurs catadioptriques qui sont composées de surfaces réfléchissantes et de lentilles. Généralement, la surface réfléchissante est métallique et donc l'état de polarisation de la lumière incidente, qui est le plus souvent partiellement linéairement polarisée, est modifiée pour être polarisée elliptiquement après réflexion. A partir de la mesure de l'état de polarisation de la lumière réfléchie, nous voulons obtenir l'état de polarisation incident. Le chapitre (4) propose une nouvelle méthode pour mesurer les paramètres de polarisation de la lumière en utilisant un capteur catadioptrique. La possibilité de mesurer le vecteur de Stokes du rayon incident est démontré à partir de trois composants du vecteur de Stokes du rayon réfléchi sur les quatre existants.Lorsque les motifs de polarisation incidents sont disponibles, les angles zénithal et azimutal du soleil peuvent être directement estimés à l'aide de ces modèles. Le chapitre (5) traite de l'orientation et de la navigation de robot basées sur la polarisation et différents algorithmes sont proposés pour estimer ces angles dans ce chapitre. A notre connaissance, l'angle zénithal du soleil est pour la première fois estimé dans ce travail à partir des schémas de polarisation incidents. Nous proposons également d'estimer l'orientation d'un véhicule à partir de ces motifs de polarisation.Enfin, le travail est conclu et les possibles perspectives de recherche sont discutées dans le chapitre (6). D'autres exemples de schémas de polarisation de la lumière naturelle, leur calibrage et des applications sont proposées en annexe (B).Notre travail pourrait ouvrir un accès au monde de la vision polarimétrique omnidirectionnelle en plus des approches conventionnelles. Cela inclut l'orientation bio-inspirée des robots, des applications de navigation, ou bien la localisation en plein air pour laquelle les motifs de polarisation de la lumière naturelle associés à l'orientation du soleil à une heure précise peuvent aboutir à la localisation géographique d'un véhiculePolarization is the phenomenon that describes the oscillations orientations of the light waves which are restricted in direction. Polarized light has multiple uses in the animal kingdom ranging from foraging, defense and communication to orientation and navigation. Chapter (1) briefly covers some important aspects of polarization and explains our research problem. We are aiming to use a polarimetric-catadioptric sensor since there are many applications which can benefit from such combination in computer vision and robotics specially robot orientation (attitude estimation) and navigation applications. Chapter (2) mainly covers the state of art of visual based attitude estimation.As the unpolarized sunlight enters the Earth s atmosphere, it is Rayleigh-scattered by air, and it becomes partially linearly polarized. This skylight polarization provides a signi cant clue to understanding the environment. Its state conveys the information for obtaining the sun orientation. Robot navigation, sensor planning, and many other applications may bene t from using this navigation clue. Chapter (3) covers the state of art in capturing the skylight polarization patterns using omnidirectional sensors (e.g fisheye and catadioptric sensors). It also explains the skylight polarization characteristics and gives a new theoretical derivation of the skylight angle of polarization pattern. Our aim is to obtain an omnidirectional 360 view combined with polarization characteristics. Hence, this work is based on catadioptric sensors which are composed of reflective surfaces and lenses. Usually the reflective surface is metallic and hence the incident skylight polarization state, which is mostly partially linearly polarized, is changed to be elliptically polarized after reflection. Given the measured reflected polarization state, we want to obtain the incident polarization state. Chapter (4) proposes a method to measure the light polarization parameters using a catadioptric sensor. The possibility to measure the incident Stokes is proved given three Stokes out of the four reflected Stokes. Once the incident polarization patterns are available, the solar angles can be directly estimated using these patterns. Chapter (5) discusses polarization based robot orientation and navigation and proposes new algorithms to estimate these solar angles where, to the best of our knowledge, the sun zenith angle is firstly estimated in this work given these incident polarization patterns. We also propose to estimate any vehicle orientation given these polarization patterns. Finally the work is concluded and possible future research directions are discussed in chapter (6). More examples of skylight polarization patterns, their calibration, and the proposed applications are given in appendix (B). Our work may pave the way to move from the conventional polarization vision world to the omnidirectional one. It enables bio-inspired robot orientation and navigation applications and possible outdoor localization based on the skylight polarization patterns where given the solar angles at a certain date and instant of time may infer the current vehicle geographical location.DIJON-BU Doc.électronique (212319901) / SudocSudocFranceF

Airborne vision-based attitude estimation and localisation

Vision plays an integral part in a pilot's ability to navigate and control an aircraft. Therefore Visual Flight Rules have been developed around the pilot's ability to see the environment outside of the cockpit in order to control the attitude of the aircraft, to navigate and to avoid obstacles. The automation of these processes using a vision system could greatly increase the reliability and autonomy of unmanned aircraft and flight automation systems. This thesis investigates the development and implementation of a robust vision system which fuses inertial information with visual information in a probabilistic framework with the aim of aircraft navigation. The horizon appearance is a strong visual indicator of the attitude of the aircraft. This leads to the first research area of this thesis, visual horizon attitude determination. An image processing method was developed to provide high performance horizon detection and extraction from camera imagery. A number of horizon models were developed to link the detected horizon to the attitude of the aircraft with varying degrees of accuracy. The second area investigated in this thesis was visual localisation of the aircraft. A terrain-aided horizon model was developed to estimate the position, altitude as well as attitude of the aircraft. This gives rough positions estimates with highly accurate attitude information. The visual localisation accuracy was improved by incorporating ground feature-based map-aided navigation. Road intersections were detected using a developed image processing algorithm and then they were matched to a database to provide positional information. The developed vision system show comparable performance to other non-vision-based systems while removing the dependence on external systems for navigation. The vision system and techniques developed in this thesis helps to increase the autonomy of unmanned aircraft and flight automation systems for manned flight