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Robot Localization Using OpenStreet Map
Rajnoch, Zdeněk ; Veľas, Martin (referee) ; Rozman, Jaroslav (advisor)
Goal of this thesis is localization of mobile robot in OpenStreet map segment. Robot IMU, odometry and compass sensors are used for trajectory reconstruction, which is compared to reference GPS trajectory. Extended Monte Carlo localization and clusterization are used for robot localization. Software is implemented in C++ with ROS middleware.
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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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Controlling of Robot with Ackermann Steering
Fryč, Martin ; Žák, Marek (referee) ; Rozman, Jaroslav (advisor)
In this paper is described creation of a robot in Robot Operating system (ROS) withAckermann steering. It contains the principle of Ackermann steering geometry, search ofcontroller boards and basics of ROS structure. A RC car with connected PixHawk controlleris used as a basis of the robot. On the robot is placed an onboard computer Raspberry Pi3 with running ROS. This computer is connected to a laptop through Wi-Fi network. Theprocedure of starting up the robot and ROS is also described in this paper, as well asdesign of the graphical user interface (GUI) that will display sensory data and allow otherfunctionality. Another part of thesis explains principle of an optical encoder and how tocreate your own encoder which can detect rotation of a wheel. This is used to implementrobot odometry. The structure of ROS navigation library is analyzed with regards to itscommissioning. Implementation of the GUI and navigation library will follow in the masterthesis.
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Robotic Shopping Cart
Kuřátko, Jiří ; Beran, Vítězslav (referee) ; Materna, Zdeněk (advisor)
This bachelor’s thesis deals with the project of application about planning the robot’s movement in order to follow the specified person. At the beginning of the work, the Microsoft Kinect sensor which is used for sensing nearby objects is described. Hereinafter the possible methods how to identify human figures on the basis of depth data from the Microsoft Kinect sensor are discussed as well. The reader is also familiar with the methods determining the direction of arrival of acoustic signals. Last chapters of the work are dedicated to the motion control of the robot. Finally the complete implementation of the robot software for the platform of Robotic Operating System (ROS) is described.
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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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Wheelchair
Kutnar, Pavel ; Burian, František (referee) ; Šembera, Jaroslav (advisor)
Thesis describes the design, development and testing of new control unit of the wheelchair. Odometry, complete control of the wheelchair and a simple communication protocol provides to superior sytem an opportunity of autonomous control. The document contains a description of the wheelchair modifications, odometry theory including its application and a description of the unit itself. The basis of the electronic part is an ATmega16 microcontroller. Tests reveal problems of odometry and suggest possible improvements.
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Trilobot Upgrade
Polášek, Patrik ; Hrubý, Martin (referee) ; Rozman, Jaroslav (advisor)
The main aim of this work is to create a robot moving on wheels, create communication among all the sensors and microcomputers with the help of the Robot Operating System (ROS). Sensors are mounted on a plastic handle that is printed on 3D printer. The Arduino microcomputer manages low-level signals for reading sensor data and signals to control the engine, the another one and more powerful ODROID-XU4 microcomputer runs the core of ROS and a graphical application that allows controlling robot on the touchscreen.
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Odometry of Experimental Vehicle Car4
Štarha, Matěj ; Adámek, Roman (referee) ; Dobossy, Barnabás (advisor)
This thesis focuses on the creation of odometry for experimental vehicle Car4. First, necessary HW and SW improvements are carried out. A research of kinematic model and known algorithms for position estimation is then conducted. Two algorithms are implemented in Matlab and their functionality is verified using simulation followed by tests of the actual trajectory of the vehicle. The goal of this work is to create a basis for any following work on the vehicle, e.g. in autonomous driving.
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Application of SLAM algorithms for 4WS vehicle
Najman, Jan ; Krejsa, Jiří (referee) ; Grepl, Robert (advisor)
This paper deals with the application of SLAM algorithms on experimental four wheel vehicle Car4. The first part shows the basic functioning of SLAM including a description of the extended Kalman filter, which is one of its main components. Then there is a brief list of software tools available to solve this problem in the environment of MATLAB and an overview of sensors used in this work. The second part presents methodology and results of the testing of individual sensors and their combinations to calculate odometry and scan the surrounding space. It also shows the process of applying SLAM algorithms on Car4 vehicle using the selected sensors and the results of testing of the entire system in practice.
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