Kamerabasierte Verfahren zur Steuerung autonomer mobiler Roboter wurden in den letzten Jahren immer populärer. In dieser Arbeit wird der Einsatz eines Stereokamerasystems und eines Mono-Kamera-SLAM Verfahrens hinsichtlich der Unterstützung der Navigation eines autonomen Luftschiffes untersucht. Mit Hilfe von Sensordaten aus IMU, GPS und Kamera wird eine Positionsschätzung über eine Sensorfusion mit Hilfe des Extended und des Unscented Kalman Filters durchgeführt.

Made available in DSpace on 2014-12-17T14:55:11Z (GMT). No. of bitstreams: 1 ArmandoSS_TESE.pdf: 2110397 bytes, checksum: c6ade2a7219938325c34c1856e93d29f (MD5) Previous issue date: 2013-02-01 / In this Thesis, the development of the dynamic model of multirotor unmanned aerial vehicle with vertical takeoff and landing characteristics, considering input nonlinearities and a full state robust backstepping controller are presented. The dynamic model is expressed using the Newton-Euler laws, aiming to obtain a better mathematical representation of the mechanical system for system analysis and control design, not only when it is hovering, but also when it is taking-off, or landing, or flying to perform a task. The input nonlinearities are the deadzone and saturation, where the gravitational effect and the inherent physical constrains of the rotors are related and addressed. The experimental multirotor aerial vehicle is equipped with an inertial measurement unit and a sonar sensor, which appropriately provides measurements of attitude and altitude. A real-time attitude estimation scheme based on the extended Kalman filter using quaternions was developed. Then, for robustness analysis, sensors were modeled as the ideal value with addition of an unknown bias and unknown white noise. The bounded robust attitude/altitude controller were derived based on globally uniformly practically asymptotically stable for real systems, that remains globally uniformly asymptotically stable if and only if their solutions are globally uniformly bounded, dealing with convergence and stability into a ball of the state space with non-null radius, under some assumptions. The Lyapunov analysis technique was used to prove the stability of the closed-loop system, compute bounds on control gains and guaranteeing desired bounds on attitude dynamics tracking errors in the presence of measurement disturbances. The controller laws were tested in numerical simulations and in an experimental hexarotor, developed at the UFRN Robotics Laboratory / Nesta Tese, s?o apresentados os desenvolvimentos da modelagem din?mica de um ve?culo a?reo n?o tripulado multirrotor com capacidade de decolagem e pouso vertical, considerando as n?o linearidades de entrada e o desenvolvimento de um controlador robusto por backstepping. A formula??o do modelo din?mico ? expressa usando-se as leis de Newton-Euler, visando ? obten??o de uma melhor representa??o matem?tica do sistema mec?nico para a an?lise e projeto das leis de controle, n?o apenas quando est? pairando, como tamb?m de decolagem, de pouso, ou de voo executando uma tarefa. As n?o linearidades de entrada s?o a zona morta e a satura??o, onde o efeito gravitacional e as inerentes restri??es f?sicas dos rotores s?o relacionadas e abordadas. O microve?culo experimental est? equipado com uma unidade de medida inercial e um sonar, que devidamente instrumentada fornece as medidas da atitude e altitude. Foi desenvolvido um estimador em tempo real para atitude usando quat?rnios e baseado em filtro de Kalman estendido. Para a formula??o robusta do controlador, os sensores foram modelados como o valor real, que ? o valor ideal com a adi??o de um vi?s e mais um ru?do branco desconhecidos e limitados. Os controladores de atitude e altitude foram derivados usando-se o crit?rio globalmente uniformemente praticamente assintoticamente est?vel para sistemas reais, que permanece globalmente uniformemente assintoticamente est?vel se e somente se suas solu??es s?o globalmente uniformemente limitadas, lidando com a converg?ncia e estabilidade dentro de uma regi?o com raio n?o nula, levando em considera??o algumas suposi??es como as incertezas nas medi??es. A t?cnica de an?lise de Lyapunov foi usada para: provar a estabilidade do sistema em malha fechada; calcular os limites dos ganhos de controle, e, obter a garantia limitada pretendida sobre o erro de rastreamento da din?mica de atitude na presen?a de dist?rbios nas medi??oes. As leis de controle foram testadas em simula??es num?ricas e em um hexarrotor experimental, desenvolvido no Laborat?rio de Rob?tica da Universidade Federal do Rio Grande do Norte

Most mobile video-recording devices of today, e.g. cell phones and music players, make use of a Rolling Shutter camera. The camera captures video by recording every frame line-by-line from top to bottom leading to image distortion when either the target or camera is moving. Capturing video by hand also leads to visible frame-to-frame jitter. This thesis presents algorithms for estimation of camera orientations using accelerometer and gyroscope. These estimates can be used to reduce the image distortion caused by camera motion using image processing. In addition an adaptive low pass filtering algorithm used to produce a smooth camera motion is presented. Using the smooth motion the frame-to-frame jitter can be reduced. The algorithms are implemented on the iPod 4 and two output videos are evaluated in a blind experiment with 30 participants. Here, videos are compared to those of competing video stabilization software. The results indicate that the iPod 4 application performs equal or better than its competitors. Also the iPod 4 accelerometer and gyroscope are compared to high end reference sensors in terms of bias and variance. / Det är vanligt att dagens mobiltelefoner använder en kamera med rullande slutare för videoinspelning. Dessa kameror fångar varje bild rad för rad från topp till botten vilket leder till bilddistorsion när antingen målet eller kameran rör sig. Inspelade videor upplevs även som skakiga eftersom kameran ej är stilla under inspelningen. I detta examensarbete presenteras algoritmer för skattning av kamerans orientering med hjälp av accelerometer och gyroskop. Skattningarna används sedan för att reducera bilddistorsionen som uppstår då kameran rör sig. En adaptiv algoritm för lågpassfiltrering av kamerans rörelse presenteras. Den mjuka rörelsen som produceras används sedan för att reducera skakigheten i filmerna. Algoritmerna implementeras på iPod 4 och de resulterande filmerna utvärderas i ett blindtest med 30 deltagare. Filmerna jämförs med versioner stabiliserade av konkurrerande mjukvara. Resultaten visar att iPod-applikationen producerar ett lika bra eller bättre resultat än konkurrenterna. Accelerometern och gyroskopet på iPod 4 jämförs även med referenssensorer i den högre prisklassen.

Kamerabasierte Verfahren zur Steuerung autonomer mobiler Roboter wurden in den letzten Jahren immer populärer. In dieser Arbeit wird der Einsatz eines Stereokamerasystems und eines Mono-Kamera-SLAM Verfahrens hinsichtlich der Unterstützung der Navigation eines autonomen Luftschiffes untersucht. Mit Hilfe von Sensordaten aus IMU, GPS und Kamera wird eine Positionsschätzung über eine Sensorfusion mit Hilfe des Extended und des Unscented Kalman Filters durchgeführt.

Sensors are highly essential components in most modern control systems and are used in increasingly complex ways to improve system precision and reliability. Since they are generally susceptible to faults it is common to perform on-line fault diagnostics on sensor data to verify nominal behavior. This is especially important for safety critical systems where it can be imperative to identify, and react to, a fault before it increases in severity. An example of such a safety critical system is the propulsion control of a vehicle. In this thesis, three different model-based methods for Fault Detection and Isolation (FDI) are developed and tested with the aim of detecting and isolating sensor faults in the powertrain of an electric, center articulated, four-wheel-drive vehicle. First, kinematic models are derived that combine sensor data from all sensors related to propulsion. Second, the kinematic models are implemented in system observers to produce fault sensitive zero-mean residuals. Finally, fault isolation algorithms are derived, which detect and indicate different types of faults via evaluation of the observer residuals. The results show that all FDI methods can detect and isolate stochastic faults with high certainty, but that offset-type faults are hard to distinguish from modeling errors and are therefore easily attenuated by the system observers. Faults in accelerometer sensors need extra measures to be detectable, owing to the environment where the vehicle is typically operated. A nonlinear system model shows good conformity to the vehicle system, lending confidence to its further use as a driver for propulsion control.

Airborne angle-only geolocalization is the localization of objects on ground level from airborne vehicles (AV) using bearing measurements, namely azimuth and elevation. This thesis aims to introduce elevation data of the terrain to the airborne angle-only geolocalization problem and to demonstrate that it could be applicable for localization of jammers. Jammers are often used for deliberate interference with malicious intent which could interfere with the positioning system of a vehicle. It is important to locate the jammers to either avoid them or to remove them.    Three localization methods, i.e. the nonlinear least squares (NLS), the extended Kalman filter (EKF) and the unscented Kalman filter (UKF), are implemented and tested on simulated data. The methods are also compared to the theoretical lower bound, the Cramér-Rao Lower Bound (CRLB), to see if there is an efficient estimator. The simulated data are different scenarios where the number of AVs, the relative flight path of the AVs and the knowledge of the terrain can differ. Using the knowledge of the terrain elevation, the methods give more consistent localization than without it. Without elevation data, the localization relies on good geometry of the problem, i.e. the relative flight path of the AVs, while the geometry is not as critical when elevation data is available. However, the elevation data does not always improve the localization for certain geometries.    There is no method that is clearly better than the others when elevation data is used. The methods’ performances are very similar and they all converge to the CRLB but that could also be an advantage. This makes the usage of elevation data not restricted to a certain method and it leaves more up to the implementer which method they prefer.

Threaded fasteners tend to break and loosen when exposed to cyclic loads or potent temperature variations. Additionally, if the joint is held tightly to the structure, distortion will occur under thermal expansion issues. These complications can be prevented by identifying and regulating the clamping force to an appropriate degree – adapted to the properties of the joint. Torque-controlled tightening is a way of monitoring the clamping force, but it assumes constant friction and therefore has low accuracy, with an error of around 17% - 43%.This thesis investigates if the friction and clamping force can be estimated using the Extended and Unscented Kalman filters to increase the precision of the torque-controlled methodology. Before the investigation, data were collected for two widely used tightening strategies. The first tightening strategy is called Continuous Drive, where the angular velocity is kept at a constant speed while torque is increased. The second strategy is TurboTight, where the angular velocity starts at a very high speed and decreases with increased torque. The collected data were noisy and had to be filtered. A hybrid between a Butterworth lowpass filter and a Sliding Window was developed and exploited for noise cancellation.The investigations revealed that it was possible to use both the Extended and Unscented Kalman filers to estimate friction and clamping force in threaded fasteners. In Continuous Drive tightening, both the EKF and UKF performed well - with an averagequality factor of 81.87% and 88.38%, and with an average error (at max torque) of 3.54% and 4.09%, respectively. However, the TurboTight strategy was much more complex and had a higher order of statistical moments to account for. Thus, the UKF outperformed the EKF with an average quality factor of 93.02% relative to 24.49%, and with an average error (at max torque) of 3.50% compared to 4.19%

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The goal of this work was to calculate the mass in the bucket of a underground loaderfrom pressure data in the cylinders. Three different approaches to using a Kalman filter toestimate the loaded mass were tried and evaluated in MATLAB simulations. Of these, twogave promising results when tried on real data and a combination of the two methods issuggested as solution to the problem. The filters required a model for the mechanics of themachine which was also derived.

Automobile accidents are one of the leading causes of death and claim more than 40,000 lives annually in the US alone. A substantial portion of these accidents occur at road intersections. Stop signs and traffic signals are some of the intersection control devices used to increase safety and prevent collisions. However, these devices themselves can contribute to collisions, are costly, inefficient, and are prone to failure. This thesis proposes an adaptive, decentralized, cooperative collision avoidance (CCA) system that optimizes each vehicle's controls subject to the constraint that no collisions occur. Three major contributions to the field of collision avoidance have resulted from this research. First, a nonlinear 5-state variable vehicle model is expanded from an earlier model developed in [1]. The model accounts for internal engine characteristics and more realistically approximates vehicle behavior in comparison to idealized, linear models. Second, a set of constrained, coupled Extended Kalman Filters (EKF) are used to predict the trajectory of the vehicles approaching an intersection in real-time. The coupled filters support decentralized operation and ensure that the optimization algorithm bases its decisions on good, reliable estimates. Third, a vehicular network based on the new WAVE standard is presented that provides cooperative capabilities by enabling intervehicle communication. The system is simulated against today's common intersection control devices and is shown to be superior in minimizing average vehicle delay. / Master of Science