Automatic Determination of Validity of Input Data Used in Ellipsoid Fitting MARG Calibration Algorithms

Ellipsoid fitting algorithms are widely used to calibrate Magnetic Angular Rate and Gravity (MARG) sensors. These algorithms are based on the minimization of an error function that optimizes the parameters of a mathematical sensor model that is subsequently applied to calibrate the raw data. The convergence of this kind of algorithms to a correct solution is very sensitive to input data. Input calibration datasets must be properly distributed in space so data can be accurately fitted to the theoretical ellipsoid model. Gathering a well distributed set is not an easy task as it is difficult for the operator carrying out the maneuvers to keep a visual record of all the positions that have already been covered, as well as the remaining ones. It would be then desirable to have a system that gives feedback to the operator when the dataset is ready, or to enable the calibration process in auto-calibrated systems. In this work, we propose two different algorithms that analyze the goodness of the distributions by computing four different indicators. The first approach is based on a thresholding algorithm that uses only one indicator as its input and the second one is based on a Fuzzy Logic System (FLS) that estimates the calibration error for a given calibration set using a weighted combination of two indicators. Very accurate classification between valid and invalid datasets is achieved with average Area Under Curve (AUC) of up to 0.98.This work was partly supported by the MICINN under the TEC2012-34306 project, the MEEC under the TIN2012-32039 (hpMooN) and the Consejería de Innovación, Ciencia y Empresa (Junta de Andalucía, Spain) under the Excellence Projects P09-TIC-4530 and P11-TIC-7103

Wireless measurement module for vector calibration

Práca sa zaoberá kalibračnými metódami pre 3D snímače zrýchlenia a realizáciou návrhu bezdrôtového meracieho modulu pre vektorovú kalibráciu. V práci sú ďalej opísané princípy interpolácie elipsoidu a použitie týchto princípov pre kalibráciu snímača zrýchlenia. Práca obsahuje krátky prehľad princípov použitých v MEMS akcelerometroch. Opísané kalibračné metódy sú implementované v Android aplikácii. Ďalej je v práci popísaný komunikačná technológia Bluetooth Low Energy. Táto komunikačná technológia je použitá na prenos dát z meracieho modulu do chytrého zariadenia. Výsledkom tejto práce je Android aplikácia pre bezdrôtovú kalibráciu MEMS akcelerometra a prezentácie dosiahnutých praktických výsledkov kalibrácie.Thesis discuss calibration methods for 3D acceleration sensors and implementation of the design of wireless measurement module for vector calibration. In this thesis are described principles of ellipsoid fitting problem and uses of this principles for calibration of accelerometer. Thesis contains short overview of principles used in MEMS accelerometers. Described calibration methods were implemented in Android application. Furthermore, the thesis describes Bluetooth Low Energy wireless technology. This communication technology is used for transferring data from measurement module to smart device. The result of this thesis is Android application for wireless vector calibration of MEMS accelerometer and presentation of practical results of this calibration.

Sensors and Technologies in Spain: State-of-the-Art

The aim of this special issue was to provide a comprehensive view on the state-of-the-art sensor technology in Spain. Different problems cause the appearance and development of new sensor technologies and vice versa, the emergence of new sensors facilitates the solution of existing real problems. [...

Robust computational intelligence techniques for visual information processing

The third part is exclusively dedicated to the super-resolution of Magnetic Resonance Images. In one of these works, an algorithm based on the random shifting technique is developed. Besides, we studied noise removal and resolution enhancement simultaneously. To end, the cost function of deep networks has been modified by different combinations of norms in order to improve their training. Finally, the general conclusions of the research are presented and discussed, as well as the possible future research lines that are able to make use of the results obtained in this Ph.D. thesis.This Ph.D. thesis is about image processing by computational intelligence techniques. Firstly, a general overview of this book is carried out, where the motivation, the hypothesis, the objectives, and the methodology employed are described. The use and analysis of different mathematical norms will be our goal. After that, state of the art focused on the applications of the image processing proposals is presented. In addition, the fundamentals of the image modalities, with particular attention to magnetic resonance, and the learning techniques used in this research, mainly based on neural networks, are summarized. To end up, the mathematical framework on which this work is based on, ₚ-norms, is defined. Three different parts associated with image processing techniques follow. The first non-introductory part of this book collects the developments which are about image segmentation. Two of them are applications for video surveillance tasks and try to model the background of a scenario using a specific camera. The other work is centered on the medical field, where the goal of segmenting diabetic wounds of a very heterogeneous dataset is addressed. The second part is focused on the optimization and implementation of new models for curve and surface fitting in two and three dimensions, respectively. The first work presents a parabola fitting algorithm based on the measurement of the distances of the interior and exterior points to the focus and the directrix. The second work changes to an ellipse shape, and it ensembles the information of multiple fitting methods. Last, the ellipsoid problem is addressed in a similar way to the parabola

Low-Cost Sensors and Biological Signals

Many sensors are currently available at prices lower than USD 100 and cover a wide range of biological signals: motion, muscle activity, heart rate, etc. Such low-cost sensors have metrological features allowing them to be used in everyday life and clinical applications, where gold-standard material is both too expensive and time-consuming to be used. The selected papers present current applications of low-cost sensors in domains such as physiotherapy, rehabilitation, and affective technologies. The results cover various aspects of low-cost sensor technology from hardware design to software optimization

UAV perception for safe flight under physical interaction

Aplicat embargament des de la data de defensa fins al maig 2020The control of autonomous flying vehicles with navigation purposes is a challenging task. Complexity arises mainly due to the non-linearity and uncertainty inherently present in the flight mechanics and aircraft-air interactions. Recently, interest has grown for equipping unmanned vehicles with the capacity to interact with their environment, other vehicles or humans. This will enable interesting applications such as autonomous load carrying, aerial refueling or parcel delivering. Having measured the interaction wrenches ease the control problem which can be configured to reject disturbances or to take profit of them to fulfill mission objectives. This thesis will contribute to this area by providing perception solutions which use limited and low cost sensors that enable state and disturbance estimation for possible, but not restricted to, interaction scenarios. This thesis contain three parts. The first part, introduces basic concepts related to the navigation state, aircraft dynamics, and sensor models. In addition, the platform under study is presented and mathematical models associated to it are calibrated. The second part is devoted to the observability analysis and the design of state observers. Linear and non-linear observability analysis techniques are used to unveil that the state of quadrotors equipped with GPS, magnetometers an IMU sensors cannot be uniquely identified in some specific flight configurations. Results of this section are relevant because the conflicting flight configurations contain hover, a flight maneuverer central in many unmanned aerial missions of VtoL vehicles. For many possible singular configurations, insightful descriptions and interpretations of the solution space known as indistinguishable region is provided. Findings are verified in simulation scenarios where it can be seen how a filter fails to recover the true state of an aircraft when imposing the hover flight condition. We discuss then the design of Extended Kalman Filters for state estimation that considers the available sensors. Issues that are typically not reported in the literature, such as when to update or propagate in the estimator algorithm or which coordinate frame should be used to represent each state variable are discussed. This leads to the formulation of four potentially equivalent but different discrete event-based filters for which precise algorithmic expressions are given. We compare the results of the four filters in simulation under known favorable conditions for observability. In order to diminish the effect of flying in the conflicting observability configurations, we provide an alternative filter based on the Schmidt Kalman Filter (SKF). The proposed filter shares the structure of the EKF, behaves better in the instants that the EKF fails and provides similar results in the remaining conditions. The last part of the thesis deals with the estimation of external disturbances. Disturbance estimation results are based on the derivation of a linear model for the aircraft dynamics which then extended with a high order disturbance model to enable the estimation of fast varying disturbances. Two external disturbance estimators from the literature are reviewed and adapted to the new model. Also, two Kalman observers that exploit the linearity of the derived model are presented. A simulation comparison is provided demonstrating that the KF disturbance estimators outperform the other. In addition, this part presents a design methodology of generic quadratic bounded observers for linear systems with ellipsoidal bounded uncertainty. The derived observers maximize a user tunable compromise between the estimation convergence speed and the final volume containing the estimation error. An observer for disturbances acting on a flying platform is derived considering the high order disturbance model above mentioned. Finally, an analysis of the estimation performance with respect to the design parameters is presented.Esta tesis, contribuye en este área formulando soluciones de percepción que permiten la estimación del estado y perturbaciones externas en condiciones normales de vuelos así como casos de interacción para UAVs equipados con sensores limitados y de bajo coste. La tesis se estructura en tres partes. La primera de ellas introduce los conceptos básicos relacionados con el estado de navegación, la dinámica de la aeronave y modelos de sensores. Además, se presenta la plataforma de estudio así como los modelos matemáticos asociados a ella y su calibración. La segunda parte está destinada al análisis de observabilidad y el diseño de observadores de estado. Los resultados de esta sección son importantes porque dentro de las condiciones de vuelo conflictivas se encuentra el vuelo a punto fijo, una maniobra de vuelo central en muchas misiones de vehículos VToL. Se analizan estas condiciones críticas de vuelo y para ellas se deriva y describe el espacio de soluciones posible conocido como región indistinguible. Los resultados son verificados en simulación dónde se puede apreciar como un estimador de estado falla al intentar realizar su tarea cuando la aeronave está en vuelo a punto fijo. Seguidamente se presenta el diseño de filtros extendidos de Kalman (EKF) que proveen estimaciones del estado con la información limitada de los sensores disponibles. Se discuten conceptos que habitualmente no se presentan en la literatura como cuando actualizar o propagar en el algoritmo de estimación o que sistema de referencia se debe utilizar para representar adecuadamente las variables de estado. Esto lleva a la formulación algorítmica de cuatro filtros discretos basados en eventos, diferentes, pero en esencia equivalentes. Se derivan rutinas de inicialización para los filtros y se comparan los resultados en simulación bajo condiciones favorables de estimación. Con la idea de disminuir el efecto de volar en configuraciones de observabilidad conflictivas, se deriva un filtro alternativo basado en el filtro de Schmidt Kalman (SKF). El filtro propuesto comparte estructura con el EKF, tiene un mejor comportamiento allí dónde le EKF falla y una respuesta similar en el resto de condiciones de vuelo. La última parte de la tesis trata con la estimación de perturbaciones externas. Para ello se deriva un modelo lineal que relaciona fuerzas y momentos con velocidades junto a un modelo de alto orden para las perturbaciones. Se estudia su aplicación a dos modelos para la estimación de perturbaciones ya presentes en la literatura. Además, se proponen dos nuevos filtros de Kalman que se aprovechan de la linealidad del modelo. Se presenta una comparativa basada en la simulación de escenarios ideales así como realistas que demuestra que los filtros KF superan al resto. Esta misma parte de la tesis presenta el diseño genérico de estimadores "quadratic bounded" para sistemas dinámicos lineales cuya incertidumbre se encuentra acotada dentro de elipsoides. Estos estimadores maximizan un compromiso, ajustable por el usuario que contempla la velocidad de convergencia así como el volumen de la solución final que contiene el error de estimación. Se deriva un observador de perturbaciones para plataformas aéreas basado en el modelo de alto orden arriba mencionado. Finalmente, se presenta un análisis del desempeño de estimación en función de los parámetros de diseño del filtro.Postprint (published version

UAV perception for safe flight under physical interaction

The control of autonomous flying vehicles with navigation purposes is a challenging task. Complexity arises mainly due to the non-linearity and uncertainty inherently present in the flight mechanics and aircraft-air interactions. Recently, interest has grown for equipping unmanned vehicles with the capacity to interact with their environment, other vehicles or humans. This will enable interesting applications such as autonomous load carrying, aerial refueling or parcel delivering. Having measured the interaction wrenches ease the control problem which can be configured to reject disturbances or to take profit of them to fulfill mission objectives. This thesis will contribute to this area by providing perception solutions which use limited and low cost sensors that enable state and disturbance estimation for possible, but not restricted to, interaction scenarios. This thesis contain three parts. The first part, introduces basic concepts related to the navigation state, aircraft dynamics, and sensor models. In addition, the platform under study is presented and mathematical models associated to it are calibrated. The second part is devoted to the observability analysis and the design of state observers. Linear and non-linear observability analysis techniques are used to unveil that the state of quadrotors equipped with GPS, magnetometers an IMU sensors cannot be uniquely identified in some specific flight configurations. Results of this section are relevant because the conflicting flight configurations contain hover, a flight maneuverer central in many unmanned aerial missions of VtoL vehicles. For many possible singular configurations, insightful descriptions and interpretations of the solution space known as indistinguishable region is provided. Findings are verified in simulation scenarios where it can be seen how a filter fails to recover the true state of an aircraft when imposing the hover flight condition. We discuss then the design of Extended Kalman Filters for state estimation that considers the available sensors. Issues that are typically not reported in the literature, such as when to update or propagate in the estimator algorithm or which coordinate frame should be used to represent each state variable are discussed. This leads to the formulation of four potentially equivalent but different discrete event-based filters for which precise algorithmic expressions are given. We compare the results of the four filters in simulation under known favorable conditions for observability. In order to diminish the effect of flying in the conflicting observability configurations, we provide an alternative filter based on the Schmidt Kalman Filter (SKF). The proposed filter shares the structure of the EKF, behaves better in the instants that the EKF fails and provides similar results in the remaining conditions. The last part of the thesis deals with the estimation of external disturbances. Disturbance estimation results are based on the derivation of a linear model for the aircraft dynamics which then extended with a high order disturbance model to enable the estimation of fast varying disturbances. Two external disturbance estimators from the literature are reviewed and adapted to the new model. Also, two Kalman observers that exploit the linearity of the derived model are presented. A simulation comparison is provided demonstrating that the KF disturbance estimators outperform the other. In addition, this part presents a design methodology of generic quadratic bounded observers for linear systems with ellipsoidal bounded uncertainty. The derived observers maximize a user tunable compromise between the estimation convergence speed and the final volume containing the estimation error. An observer for disturbances acting on a flying platform is derived considering the high order disturbance model above mentioned. Finally, an analysis of the estimation performance with respect to the design parameters is presented.Esta tesis, contribuye en este área formulando soluciones de percepción que permiten la estimación del estado y perturbaciones externas en condiciones normales de vuelos así como casos de interacción para UAVs equipados con sensores limitados y de bajo coste. La tesis se estructura en tres partes. La primera de ellas introduce los conceptos básicos relacionados con el estado de navegación, la dinámica de la aeronave y modelos de sensores. Además, se presenta la plataforma de estudio así como los modelos matemáticos asociados a ella y su calibración. La segunda parte está destinada al análisis de observabilidad y el diseño de observadores de estado. Los resultados de esta sección son importantes porque dentro de las condiciones de vuelo conflictivas se encuentra el vuelo a punto fijo, una maniobra de vuelo central en muchas misiones de vehículos VToL. Se analizan estas condiciones críticas de vuelo y para ellas se deriva y describe el espacio de soluciones posible conocido como región indistinguible. Los resultados son verificados en simulación dónde se puede apreciar como un estimador de estado falla al intentar realizar su tarea cuando la aeronave está en vuelo a punto fijo. Seguidamente se presenta el diseño de filtros extendidos de Kalman (EKF) que proveen estimaciones del estado con la información limitada de los sensores disponibles. Se discuten conceptos que habitualmente no se presentan en la literatura como cuando actualizar o propagar en el algoritmo de estimación o que sistema de referencia se debe utilizar para representar adecuadamente las variables de estado. Esto lleva a la formulación algorítmica de cuatro filtros discretos basados en eventos, diferentes, pero en esencia equivalentes. Se derivan rutinas de inicialización para los filtros y se comparan los resultados en simulación bajo condiciones favorables de estimación. Con la idea de disminuir el efecto de volar en configuraciones de observabilidad conflictivas, se deriva un filtro alternativo basado en el filtro de Schmidt Kalman (SKF). El filtro propuesto comparte estructura con el EKF, tiene un mejor comportamiento allí dónde le EKF falla y una respuesta similar en el resto de condiciones de vuelo. La última parte de la tesis trata con la estimación de perturbaciones externas. Para ello se deriva un modelo lineal que relaciona fuerzas y momentos con velocidades junto a un modelo de alto orden para las perturbaciones. Se estudia su aplicación a dos modelos para la estimación de perturbaciones ya presentes en la literatura. Además, se proponen dos nuevos filtros de Kalman que se aprovechan de la linealidad del modelo. Se presenta una comparativa basada en la simulación de escenarios ideales así como realistas que demuestra que los filtros KF superan al resto. Esta misma parte de la tesis presenta el diseño genérico de estimadores "quadratic bounded" para sistemas dinámicos lineales cuya incertidumbre se encuentra acotada dentro de elipsoides. Estos estimadores maximizan un compromiso, ajustable por el usuario que contempla la velocidad de convergencia así como el volumen de la solución final que contiene el error de estimación. Se deriva un observador de perturbaciones para plataformas aéreas basado en el modelo de alto orden arriba mencionado. Finalmente, se presenta un análisis del desempeño de estimación en función de los parámetros de diseño del filtro