Aircraft Attitude Estimation Using Panoramic Images

This thesis investigates the problem of reliably estimating attitude from panoramic imagery in cluttered environments. Accurate attitude is an essential input to the stabilisation systems of autonomous aerial vehicles. A new camera system which combines a CCD camera, UltraViolet (UV) filters and a panoramic mirror-lens is designed. Drawing on biological inspiration from the Ocelli organ possessed by certain insects, UV filtered images are used to enhance the contrast between the sky and ground and mitigate the effect of the sun. A novel method for real–time horizon-based attitude estimation using panoramic image that is capable of estimating an aircraft pitch and roll at a low altitude in the presence of sun, clouds and occluding features such as tree, building, is developed. Also, a new method for panoramic sky/ground thresholding, consisting of a horizon– and a sun–tracking system which works effectively even when the horizon line is difficult to detect by normal thresholding methods due to flares and other effects from the presence of the sun in the image, is proposed. An algorithm for estimating the attitude from three–dimensional mapping of the horizon projected onto a 3D plane is developed. The use of optic flow to determine pitch and roll rates is investigated using the panoramic image and image interpolation algorithm (I2A). Two methods which employ sensor fusion techniques, Extended Kalman Filter (EKF) and Artificial Neural Networks (ANNs), are used to fuse unfiltered measurements from inertial sensors and the vision system. The EKF estimates gyroscope biases and also the attitude. The ANN fuses the optic flow and horizon–based attitude to provide smooth attitude estimations. The results obtained from different parts of the research are tested and validated through simulations and real flight tests

FREQUENCY DOMAIN CHARACTERIZATION OF OPTIC FLOW AND VISION-BASED OCELLAR SENSING FOR ROTATIONAL MOTION

The structure of an animal’s eye is determined by the tasks it must perform. While vertebrates rely on their two eyes for all visual functions, insects have evolved a wide range of specialized visual organs to support behaviors such as prey capture, predator evasion, mate pursuit, flight stabilization, and navigation. Compound eyes and ocelli constitute the vision forming and sensing mechanisms of some flying insects. They provide signals useful for flight stabilization and navigation. In contrast to the well-studied compound eye, the ocelli, seen as the second visual system, sense fast luminance changes and allows for fast visual processing. Using a luminance-based sensor that mimics the insect ocelli and a camera-based motion detection system, a frequency-domain characterization of an ocellar sensor and optic flow (due to rotational motion) are analyzed. Inspired by the insect neurons that make use of signals from both vision sensing mechanisms, advantages, disadvantages and complementary properties of ocellar and optic flow estimates are discussed

Attitude estimation using horizon detection in thermal images

The lack of redundant attitude sensors represents a considerable yet common vulnerability in many low-cost unmanned aerial vehicles. In addition to the use of attitude sensors, exploiting the horizon as a visual reference for attitude control is part of human pilots' training. For this reason, and given the desirable properties of image sensors, quite a lot of research has been conducted proposing the use of vision sensors for horizon detection in order to obtain redundant attitude estimation onboard unmanned aerial vehicles. However, atmospheric and illumination conditions may hinder the operability of visible light image sensors, or even make their use impractical, such as during the night. Thermal infrared image sensors have a much wider range of operation conditions and their price has greatly decreased during the last years, becoming an alternative to visible spectrum sensors in certain operation scenarios. In this paper, two attitude estimation methods are proposed. The first method consists of a novel approach to estimate the line that best fits the horizon in a thermal image. The resulting line is then used to estimate the pitch and roll angles using an infinite horizon line model. The second method uses deep learning to predict attitude angles using raw pixel intensities from a thermal image. For this, a novel Convolutional Neural Network architecture has been trained using measurements from an inertial navigation system. Both methods presented are proven to be valid for redundant attitude estimation, providing RMS errors below 1.7° and running at up to 48 Hz, depending on the chosen method, the input image resolution and the available computational capabilities

A Continuous-Time Nonlinear Observer for Estimating Structure from Motion from Omnidirectional Optic Flow

Various insect species utilize certain types of self-motion to perceive structure in their local environment, a process known as active vision. This dissertation presents the development of a continuous-time formulated observer for estimating structure from motion that emulates the biological phenomenon of active vision. In an attempt to emulate the wide-field of view of compound eyes and neurophysiology of insects, the observer utilizes an omni-directional optic flow field. Exponential stability of the observer is assured provided the persistency of excitation condition is met. Persistency of excitation is assured by altering the direction of motion sufficiently quickly. An equal convergence rate on the entire viewable area can be achieved by executing certain prototypical maneuvers. Practical implementation of the observer is accomplished both in simulation and via an actual flying quadrotor testbed vehicle. Furthermore, this dissertation presents the vehicular implementation of a complimentary navigation methodology known as wide-field integration of the optic flow field. The implementation of the developed insect-inspired navigation methodologies on physical testbed vehicles utilized in this research required the development of many subsystems that comprise a control and navigation suite, including avionics development and state sensing, model development via system identification, feedback controller design, and state estimation strategies. These requisite subsystems and their development are discussed

DragonflEYE: a passive approach to aerial collision sensing

"This dissertation describes the design, development and test of a passive wide-field optical aircraft collision sensing instrument titled 'DragonflEYE'. Such a ""sense-and-avoid"" instrument is desired for autonomous unmanned aerial systems operating in civilian airspace. The instrument was configured as a network of smart camera nodes and implemented using commercial, off-the-shelf components. An end-to-end imaging train model was developed and important figures of merit were derived. Transfer functions arising from intermediate mediums were discussed and their impact assessed. Multiple prototypes were developed. The expected performance of the instrument was iteratively evaluated on the prototypes, beginning with modeling activities followed by laboratory tests, ground tests and flight tests. A prototype was mounted on a Bell 205 helicopter for flight tests, with a Bell 206 helicopter acting as the target. Raw imagery was recorded alongside ancillary aircraft data, and stored for the offline assessment of performance. The ""range at first detection"" (R0), is presented as a robust measure of sensor performance, based on a suitably defined signal-to-noise ratio. The analysis treats target radiance fluctuations, ground clutter, atmospheric effects, platform motion and random noise elements. Under the measurement conditions, R0 exceeded flight crew acquisition ranges. Secondary figures of merit are also discussed, including time to impact, target size and growth, and the impact of resolution on detection range. The hardware was structured to facilitate a real-time hierarchical image-processing pipeline, with selected image processing techniques introduced. In particular, the height of an observed event above the horizon compensates for angular motion of the helicopter platform.

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

Aerial Vehicles

This book contains 35 chapters written by experts in developing techniques for making aerial vehicles more intelligent, more reliable, more flexible in use, and safer in operation.It will also serve as an inspiration for further improvement of the design and application of aeral vehicles. The advanced techniques and research described here may also be applicable to other high-tech areas such as robotics, avionics, vetronics, and space

Workshop on Advanced Technologies for Planetary Instruments, part 1

This meeting was conceived in response to new challenges facing NASA's robotic solar system exploration program. This volume contains papers presented at the Workshop on Advanced Technologies for Planetary Instruments on 28-30 Apr. 1993. This meeting was conceived in response to new challenges facing NASA's robotic solar system exploration program. Over the past several years, SDIO has sponsored a significant technology development program aimed, in part, at the production of instruments with these characteristics. This workshop provided an opportunity for specialists from the planetary science and DoD communities to establish contacts, to explore common technical ground in an open forum, and more specifically, to discuss the applicability of SDIO's technology base to planetary science instruments

Biologically Inspired Visual Control of Flying Robots

Insects posses an incredible ability to navigate their environment at high speed, despite having small brains and limited visual acuity. Through selective pressure they have evolved computationally efficient means for simultaneously performing navigation tasks and instantaneous control responses. The insect’s main source of information is visual, and through a hierarchy of processes this information is used for perception; at the lowest level are local neurons for detecting image motion and edges, at the higher level are interneurons to spatially integrate the output of previous stages. These higher level processes could be considered as models of the insect's environment, reducing the amount of information to only that which evolution has determined relevant. The scope of this thesis is experimenting with biologically inspired visual control of flying robots through information processing, models of the environment, and flight behaviour. In order to test these ideas I developed a custom quadrotor robot and experimental platform; the 'wasp' system. All algorithms ran on the robot, in real-time or better, and hypotheses were always verified with flight experiments. I developed a new optical flow algorithm that is computationally efficient, and able to be applied in a regular pattern to the image. This technique is used later in my work when considering patterns in the image motion field. Using optical flow in the log-polar coordinate system I developed attitude estimation and time-to-contact algorithms. I find that the log-polar domain is useful for analysing global image motion; and in many ways equivalent to the retinotopic arrange- ment of neurons in the optic lobe of insects, used for the same task. I investigated the role of depth in insect flight using two experiments. In the first experiment, to study how concurrent visual control processes might be combined, I developed a control system using the combined output of two algorithms. The first algorithm was a wide-field optical flow balance strategy and the second an obstacle avoidance strategy which used inertial information to estimate the depth to objects in the environment - objects whose depth was significantly different to their surround- ings. In the second experiment I created an altitude control system which used a model of the environment in the Hough space, and a biologically inspired sampling strategy, to efficiently detect the ground. Both control systems were used to control the flight of a quadrotor in an indoor environment. The methods that insects use to perceive edges and control their flight in response had not been applied to artificial systems before. I developed a quadrotor control system that used the distribution of edges in the environment to regulate the robot height and avoid obstacles. I also developed a model that predicted the distribution of edges in a static scene, and using this prediction was able to estimate the quadrotor altitude