Sensor Fusion for Localization of Automated Guided Vehicles

Automated Guided Vehicles (AGVs) need to localize themselves reliably in order to perform their tasks efficiently. To that end, they rely on noisy sensor measurements that potentially provide erroneous location estimates if they are used directly. To prevent this issue, measurements from different kinds of sensors are generally used together. This thesis presents a Kalman Filter based sensor fusion approach that is able to function with asynchronous measurements from laser scanners, odometry and Inertial Measurement Units (IMUs). The method uses general kinematic equations for state prediction that work with any type of vehicle kinematics and utilizes state augmentation to estimate gyroscope and accelerometer biases. The developed algorithm was tested with an open source multisensor navigation dataset and real-time experiments with an AGV. In both sets of experiments, scenarios in which the laser scanner was fully available, partially available or not available were compared. It was found that using sensor fusion resulted in a smaller deviation from the actual trajectory compared to using only a laser scanner. Furthermore, in each experiment, using sensor fusion decreased the localization error in the time periods where the laser was unavailable, although the amount of improvement depended on the duration of unavailability and motion characteristic

Exploring space situational awareness using neuromorphic event-based cameras

The orbits around earth are a limited natural resource and one that hosts a vast range of vital space-based systems that support international systems use by both commercial industries, civil organisations, and national defence. The availability of this space resource is rapidly depleting due to the ever-growing presence of space debris and rampant overcrowding, especially in the limited and highly desirable slots in geosynchronous orbit. The field of Space Situational Awareness encompasses tasks aimed at mitigating these hazards to on-orbit systems through the monitoring of satellite traffic. Essential to this task is the collection of accurate and timely observation data. This thesis explores the use of a novel sensor paradigm to optically collect and process sensor data to enhance and improve space situational awareness tasks. Solving this issue is critical to ensure that we can continue to utilise the space environment in a sustainable way. However, these tasks pose significant engineering challenges that involve the detection and characterisation of faint, highly distant, and high-speed targets. Recent advances in neuromorphic engineering have led to the availability of high-quality neuromorphic event-based cameras that provide a promising alternative to the conventional cameras used in space imaging. These cameras offer the potential to improve the capabilities of existing space tracking systems and have been shown to detect and track satellites or ‘Resident Space Objects’ at low data rates, high temporal resolutions, and in conditions typically unsuitable for conventional optical cameras. This thesis presents a thorough exploration of neuromorphic event-based cameras for space situational awareness tasks and establishes a rigorous foundation for event-based space imaging. The work conducted in this project demonstrates how to enable event-based space imaging systems that serve the goals of space situational awareness by providing accurate and timely information on the space domain. By developing and implementing event-based processing techniques, the asynchronous operation, high temporal resolution, and dynamic range of these novel sensors are leveraged to provide low latency target acquisition and rapid reaction to challenging satellite tracking scenarios. The algorithms and experiments developed in this thesis successfully study the properties and trade-offs of event-based space imaging and provide comparisons with traditional observing methods and conventional frame-based sensors. The outcomes of this thesis demonstrate the viability of event-based cameras for use in tracking and space imaging tasks and therefore contribute to the growing efforts of the international space situational awareness community and the development of the event-based technology in astronomy and space science applications

Tracking Extended Objects in Noisy Point Clouds with Application in Telepresence Systems

We discuss theory and application of extended object tracking. This task is challenging as sensor noise prevents a correct association of the measurements to their sources on the object, the shape itself might be unknown a priori, and due to occlusion effects, only parts of the object are visible at a given time. We propose an approach to track the parameters of arbitrary objects, which provides new solutions to the above challenges, and marks a significant advance to the state of the art

Tracking Extended Objects in Noisy Point Clouds with Application in Telepresence Systems

We discuss theory and application of extended object tracking. This task is challenging as sensor noise prevents a correct association of the measurements to their sources on the object, the shape itself might be unknown a priori, and due to occlusion effects, only parts of the object are visible at a given time. We propose an approach to track the parameters of arbitrary objects, which provides new solutions to the above challenges, and marks a significant advance to the state of the art

High-Speed Vision and Force Feedback for Motion-Controlled Industrial Manipulators

Over the last decades, both force sensors and cameras have emerged as useful sensors for different applications in robotics. This thesis considers a number of dynamic visual tracking and control problems, as well as the integration of these techniques with contact force control. Different topics ranging from basic theory to system implementation and applications are treated. A new interface developed for external sensor control is presented, designed by making non-intrusive extensions to a standard industrial robot control system. The structure of these extensions are presented, the system properties are modeled and experimentally verified, and results from force-controlled stub grinding and deburring experiments are presented. A novel system for force-controlled drilling using a standard industrial robot is also demonstrated. The solution is based on the use of force feedback to control the contact forces and the sliding motions of the pressure foot, which would otherwise occur during the drilling phase. Basic methods for feature-based tracking and servoing are presented, together with an extension for constrained motion estimation based on a dual quaternion pose parametrization. A method for multi-camera real-time rigid body tracking with time constraints is also presented, based on an optimal selection of the measured features. The developed tracking methods are used as the basis for two different approaches to vision/force control, which are illustrated in experiments. Intensity-based techniques for tracking and vision-based control are also developed. A dynamic visual tracking technique based directly on the image intensity measurements is presented, together with new stability-based methods suitable for dynamic tracking and feedback problems. The stability-based methods outperform the previous methods in many situations, as shown in simulations and experiments

Outils d'analyse, de modélisation et de commande pour les radiocommunications Application aux amplificateurs de puissance

L'évolution croissante des télécommunications résulte de la combinaison de plusieurs facteurs comme les progrès de l'électronique, de la micro-électronique, de la radiofréquence mais aussi des avancées des techniques de communications numériques. Dans ce contexte, les études s'orientent de plus en plus vers l'amélioration de la couverture et de la qualité de service offertes aux usagers. C'est dans ce contexte que s'inscrivent les travaux exposés dans le cadre de cette Habilitation à Diriger des Recherches. Les problématiques soulevées concernent : - la connaissance et la maîtrise du comportement des composants en présence de signaux large bande, multiporteuses, - l'amélioration de la qualité des transmissions en tenant compte des aspects énergétiques, - la reconfigurabilité et l'adaptation des nouveaux systèmes à la multiplication des normes et des standards de communications. Pour chaque problématique, nous avons proposé des solutions théoriques et pratiques avec comme fil conducteur l'utilisation et la mise en \oe uvre d'outils issus de l'Automatique comme l'estimation paramétrique, la commande et la linéarisation, l'optimisation, etc. Concernant la modélisation des fonctions électroniques RF, je présente mes travaux concernant la prise en compte des effets statiques et dynamiques en temps continu et discret. Pour les circuits hautes fréquences qui se caractérisent par des constantes de temps avec des ordres de grandeurs divers, nous avons montré qu'il est important d'envisager la modélisation selon l'application visée et en déployant des outils d'estimation paramétrique adaptés. Des problématiques telles que la normalisation de l'espace paramétrique, l'initialisation, la convergence sont étudiées pour répondre aux caractéristiques des systèmes de radiocommunications.Dans le chapitre consacré à l'amélioration de la linéarité et du rendement, nous avons présenté des techniques de correction des imperfections des amplificateurs de puissances ainsi que des méthodes de traitement du signal qui permettent de réduire leurs impacts sur la transmission. Concernant la linéarisation, nous avons commencé par une comparaison d'une technique Feedback et d'un linéariseur à base d'une prédistorsion polynomiale sans mémoire. Cette étude a mis en évidence l'intérêt d'adjoindre de la mémoire sous forme de retards dans le linéariseur. Les fortes fluctuations des signaux multiporteuses, mesurées par le PAPR pour Peak-to-Average Power Ratio, contribuent aussi à dégrader le bilan énergétique de l'émetteur. La majorité des travaux sur la réduction du PAPR se limite à l'étude des performances en termes de gain de réduction, sans aborder la qualité de transmission en présence d'imperfections réalistes des éléments non-linéaires. C'est dans ce contexte que nous avons analysé cette problématique pour un système MIMO-OFDM en boucle fermée avec prise en compte du canal, des non-linéarités, des effets mémoires et des critères visuels permettant d'évaluer la qualité des transmissions de données multimédias.Le développement d'architectures entièrement numérique, reconfigurables est traité en dernière partie de ce cette HDR. Pour cette large thématique, nous proposons des améliorations pour des coefficients des modulateurs afin d'obtenir une fonction de transfert du bruit respectant un gabarit fréquentiel donné. La correction des erreurs de calcul dus aux coefficients du type 1/$2^L$. Cette correction est basée sur la ré-injection de l'erreur au sein de la boucle directe à travers un filtre numérique

UAV or Drones for Remote Sensing Applications in GPS/GNSS Enabled and GPS/GNSS Denied Environments

The design of novel UAV systems and the use of UAV platforms integrated with robotic sensing and imaging techniques, as well as the development of processing workflows and the capacity of ultra-high temporal and spatial resolution data, have enabled a rapid uptake of UAVs and drones across several industries and application domains.This book provides a forum for high-quality peer-reviewed papers that broaden awareness and understanding of single- and multiple-UAV developments for remote sensing applications, and associated developments in sensor technology, data processing and communications, and UAV system design and sensing capabilities in GPS-enabled and, more broadly, Global Navigation Satellite System (GNSS)-enabled and GPS/GNSS-denied environments.Contributions include:UAV-based photogrammetry, laser scanning, multispectral imaging, hyperspectral imaging, and thermal imaging;UAV sensor applications; spatial ecology; pest detection; reef; forestry; volcanology; precision agriculture wildlife species tracking; search and rescue; target tracking; atmosphere monitoring; chemical, biological, and natural disaster phenomena; fire prevention, flood prevention; volcanic monitoring; pollution monitoring; microclimates; and land use;Wildlife and target detection and recognition from UAV imagery using deep learning and machine learning techniques;UAV-based change detection

Overcoming the challenges of low-cost inertial navigation

Inertial navigation is always available as a base for multisensor navigation systems on, because it requires no external signals. However, measurement errors persist and grow with time so accurate calibration is crucial. Large systematic errors are present in the micro-electro-mechanical sensors (MEMS) whose low cost brings inertial navigation to many new applications. Using factory-calibrated MEMS another navigation technology can calibrate these errors with in-run estimation using a Kalman filter (KF). However, the raw systematic errors of low-cost MEMS are often too large for stable performance. This thesis contributes to knowledge in three areas. First, it takes a simple GNSS-inertial KF and examines the levels of the various systematic errors which cause the integration to fail. This allows the user to know how well calibrated the sensors need to be to use in-run calibration. Second, the thesis examines how the end-user could conduct a calibration: it analyses one method in detail showing how imperfections in the procedure affect the results and comparing calculation methods. This is important as frequently calibration methods are only validated by demonstrating consistent results for one particular sensor. These two are primarily accomplished using statistical Monte Carlo simulations. Third, techniques are examined by which an array of inertial sensors could be used to produce an output which is better than the simple array average. This includes methods that reduce the array’s sensitivity to environmental conditions, this is important because the sensors’ calibration typically depends strongly on temperature. Also included in the thesis are descriptions of experimental hardware and experiments which have been carried to support and unify the other parts of the thesis. Overall, this thesis’ contributions will help make low-cost inertial navigation systems more accurate and will allow system designers to concentrate effort where it will make the most difference