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Browse the Map on Your Mobile Device by Moving the Device
Andraško, Daniel ; Herout, Adam (referee) ; Beran, Vítězslav (advisor)
This work deals with the creation of a mobile application that allows its user to view the map and move around it, without touching the screen, just by moving the device. The theoretical part of the thesis describes in more detail the inertial measurement unit and visual odometry , which can be used to determine the movement of the device. Next, a Kalman filter is described, which is used to refine the measured values of the accelerometer sensor. This sensor is part of an inertial measuring unit. The practical part of thesis describes the design of the mobile application and the implementation of the design. The end of thesis contains a description and evaluation of testing the final application on real users.
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Methods of dynamical analysis of portfolio composition
Meňhartová, Ivana ; Hanzák, Tomáš (advisor) ; Cipra, Tomáš (referee)
Title: Methods of dynamical analysis of portfolio composition Author: Ivana Meňhartová Department: Department of Probability and Mathematical Statistics Supervisor: Mgr. Tomáš Hanzák, KPMS, MFF UK Abstract: In the presented thesis we study methods used for dynamic analysis of portfolio based on it's revenues. The thesis focuses on Kalman filter and local- ly weighted regression as two basic methods for dynamic analysis. It describes in detail theory for these methods as well as their utilization and it discusses their proper settings. Practical applications of both methods on artificial data and real data from Prague stock-exchange are presented. Using artificial data we demonstrate practical importance of Kalman filter's assumptions. Afterwards we introduce term multicolinearity as a possible complication to real data applicati- ons. At the end of the thesis we compare results and usage of both methods and we introduce possibility of enhancing Kalman filter by projection of estimations or by CUSUM tests (change detection tests). Keywords: Kalman filter, locally weighted regression, multicollinearity, CUSUM test
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Estimating implicit inflation target of the ECB
Melioris, Libor ; Horváth, Roman (advisor) ; Geršl, Adam (referee)
Existing estimations of implicit inflation target are primarily based on the assumption of parameter stability over time horizon. This work relaxes this assumption and proposes alternative framework based on time-varying parameter model. We aim on behaviour of European Central Bank in order to compare its official proclamations of price stability levels with our implicit estimations. We will also examine how two pillar strategy of European Central Bank is practically used.
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Estimating of motion models and its parameters to identify target trajectory
Benko, Matej ; Eliaš, Michal (referee) ; Žák, Libor (advisor)
Táto práca sa zaoberá odstraňovaním šumu, ktorý vzniká z tzv. multilateračných meraní leteckých cieľov. Na tento účel bude využitá najmä teória Bayesovských odhadov. Odvodí sa aposteriórna hustota skutočnej (presnej) polohy lietadla. Spolu s polohou (alebo aj rýchlosťou) lietadla bude odhadovaná tiež geometria trajektórie lietadla, ktorú lietadlo v aktuálnom čase sleduje a tzv. procesný šum, ktorý charakterizuje ako moc sa skutočná trajektória môže od tejto líšiť. Odhad spomínaného procesného šumu je najdôležitejšou časťou tejto práce. Je odvodený prístup maximálnej vierohodnosti a Bayesovský prístup a ďalšie rôzne vylepšenia a úpravy týchto prístupov. Tie zlepšujú odhad pri napr. zmene manévru cieľa alebo riešia problém počiatočnej nepresnosti odhadu maximálnej vierohodnosti. Na záver je ukázaná možnosť kombinácie prístupov, t.j. odhad spolu aj geometrie aj procesného šumu.
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Radar Sensor for Active Cruise Control
Lacek, Richard ; Zemčík, Pavel (referee) ; Maršík, Lukáš (advisor)
The aim of the work was to design the implementation of adaptive cruise control with the help of radar as a sensor to evaluate the surroundings in front of the vehicle. The solution used the VCDS-Lite application to determine the current vehicle speed and the Medium Range Radar demo, from Texas Instruments, to capture the surroundings in front of the vehicle with AWR1843 radar. Using these two applications was evaluated the environment in front of the vehicle from which the instruction for a driver was derived. The result of the work is an application that displays the current vehicle speed along with the current adaptive cruise control instruction. In addition to setting the speed, the application also provides a setting of the time interval from the vehicle that follows.
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Robot Positioning Based on Sensor Measurements
Čakloš, Ondrej ; Žák, Marek (referee) ; Rozman, Jaroslav (advisor)
The goal of this thesis is to create a program, that will be receiving measurements from robot's sensors and fuse them together. Afterwards use this data fusion of chosen sensors to estimate location of a robot. As a solution for these problems I have used my knowledge of Kalman filters, especially extended one. If messages from sensor measurements are well formulated, Kalman filter can perform fusion of measurements together with estimating the actual position of a robot. Filter can receive measurements from multiple sources and even from duplicities. The estimated states have proven themselves reasonably accurate for successful robot localization in space.
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Robot Positioning Based on Sensor Measurements
Čakloš, Ondrej ; Uhlíř, Václav (referee) ; Rozman, Jaroslav (advisor)
The goal of this thesis is to create a program, that will be receiving measurements from robot's sensors, provide sensor fusion and estimate position of robot based on this fusion. For solving I used knowledge about probabilistic robotics, robotic operating system, information fusion, filtering especially extended Kalman filter and robot localization. I created an application of extended Kalman filter as a result. Filter listen to messages from robot sensors, providing a sensor fusion and estimating position of the robot in environment. Filter can receive measurements from multiple sources. The estimated states have proven themselves reasonably accurate for successful robot localization in space.
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Vehicle speed estimation
Roštek, Martin ; Kumpán, Pavel (referee) ; Krejsa, Jiří (advisor)
Rýchlosť vozidla je jednou z kľúčových stavových premenných, ktorej znalosť je potrebná v reálnom čase a s vysokou presnosťou, aby mohla slúžiť ako vstupná veličina pre systémy kontroly dynamiky vozidla. Jej priame meranie vo vozidle je však finančne náročné. Riešením tohoto problému môže byť použitie meraní zo senzorov bežne dostupných na palube vozidla a ich následný prepočet na rýchlosť vozidla. Tieto merania sú však veľmi zaťažené procesným šumom, čo vyplýva z komplexnosti pohybu vozidla. Preto je nutné vyvinúť algoritmus so schopnosťou vysporiadať sa s týmito negatívnymi vplyvmi. Algoritmus prezentovaný v tejto práci odhaduje pozdĺžnu rýchlosť vozidla s použitím meraní uhlových rýchlostí štyroch kolies, pozdĺžnej akcelerácie, momentov motora, rýchlosti otáčania okolo zvislej osi a natočenia volantu. Algoritmus bol testovaný na veľkom počte situácií považovaných za kritické na odhad rýchlosti vozidla, ako napríklad prudká akcelerácia na vozovke s nízkym koeficientom trenia, núdzové brzdenie s aktiváciou ABS, či jazda v kopci s kolesami v preklze, prinášajúc uspokojujúce výsledky.
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