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2D Point-cloud segmentation for curve fitting
Šooš, Marek ; Krejsa, Jiří (referee) ; Králík, Jan (advisor)
The presented diploma thesis deals with the division of points into homogeneous groups. The work provides a broad overview of the current state in this topic and a brief explanation of the main segmentation methods principles. From the analysis of the articles are selected and programmed five algorithms. The work defines the principles of selected algorithms and explains their mathematical models. For each algorithm is also given a code design description. The diploma thesis also contains a cross comparison of segmentation capabilities of individual algorithms on created as well as on measured data. The results of the curves extraction are compared with each other graphically and numerically. At the end of the work is a comparison graph of time dependence on the number of points and the table that includes a mutual comparison of algorithms in specific areas.
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LIDAR and Stereocamera in Localization of Mobile Robots
Vyroubalová, Jana ; Drahanský, Martin (referee) ; Orság, Filip (advisor)
LIDAR (2D) has been widely used for mapping, localization and navigation in mobile robotics. However, its usage is limited to simple environments. This problem can be solved by adding more sensors and processing these data together. This paper explores a method how measurements from a stereo camera and LIDAR are fused to dynamical mapping. An occupancy grid map from LIDAR data is used as prerequisite and extended by a 2D grid map from stereo camera. This approach is based on the ground plane estimation in disparity map acquired from the stereo vision. For the ground plane detection, RANSAC and Least Squares methods are used. After obstacles determination, 2D occupancy map is generated. The output of this method is 2D map as a fusion of complementary maps from LIDAR and camera. Experimental results obtained from RUDA robot and MIT Stata Center Data Set are good enough to determine that this method is a benefit, although my implementation is still a prototype. In this paper, we present the applied methods, analyze the results and discuss the modifications and possible extensions to get better results.
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New features for real-time positioning system locator
Studený, Jakub ; Sekora, Jiří (referee) ; Kolářová, Jana (advisor)
The diploma thesis deals with the detection of falls and impacts, based on data obtained from inertial sensors, and by measuring the distance using a laser. The aim of this thesis is to extend the functionality of locators from Sewio. The thesis describes the procedure for designing algorithms for detection of falls and impacts. Then there is a procedure for development of hardware and software solution, for laser distance measurement by locator, together with presentation of achieved measurement results realized by locator after implementation of proposed solution. The work also emphasizes the minimization of energy consumption of individual solutions. In conclusion, there is a discussion of achieved results with evaluation of efficiency and usability of proposed solutions.
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Detection and Vizualization of Features in a Point Cloud
Kratochvíl, Jiří Jaroslav ; Mikeš, Josef (referee) ; Martišek, Dalibor (referee) ; Procházková, Jana (advisor)
The point cloud is an unorganized set of points with 3D coordinates (x, y, z) which represents a real object. These point clouds are acquired by the technology called 3D scanning. This scanning technique can be done by various methods, such as LIDAR (Light Detection And Ranging) or by utilizing recently developed 3D scanners. Point clouds can be therefore used in various applications, such as mechanical or reverse engineering, rapid prototyping, biology, nuclear physics or virtual reality. Therefore in this doctoral Ph.D. thesis, I focus on feature detection and visualization in a point cloud. These features represent parts of the object that can be described by the well--known mathematical model (lines, planes, helices etc.). The points on the sharp edges are especialy problematic for commonly used methods. Therefore, I focus on detection of these problematic points. This doctoral Ph.D. thesis presents a new algorithm for precise detection of these problematic points. Visualization of these points is done by a modified curve fitting algoritm with a new weight function that leads to better results. Each of the proposed methods were tested on real data sets and compared with contemporary published methods.
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Self-Driving of a Model Car
Hazucha, Ivan ; Šimek, Václav (referee) ; Bidlo, Michal (advisor)
The aim of this thesis is to demonstrate options for self-driving model cars, focused on local path planning methods and obstacle avoidance. As a part of the project, the model was supplemented by a computing platform Raspberry Pi and appropriate sensors. Specifically, a 2D LiDAR sensor was used for detection and measuring the distance of surrounding objects, an incremental rotary encoder for measuring the distance travelled and current speed, and a gyroscope to keep track of the vehicle's relative orientation. Subsequently, a control system was implemented. This system is able to receive and process sensor data, use it to estimate vehicle's current location, compute an optimal trajectory in an uncharted environment, and control the vehicle's actuators accordingly. The result is a functional model car able to navigate in an unknown environment and reach specified goals by following a trajectory, dynamically generated depending on the surrounding obstacles.
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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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Traffic Signs Detection and Localisation
Kudláč, Ondrej ; Španěl, Michal (referee) ; Veľas, Martin (advisor)
This thesis aims to design the traffic signs detection and localization system using RGB image and 3D LiDAR data leveraging the the existing solutions. Traffic sign detection is based on the shape analysis. Then, the LIDAR data are used for the localization of previously detected signs. The created solution consists of two main components: the detector and locator, each able to operate independently.
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Autonomous vehicles sensors - study search
Macejka, Kamil ; Krejsa, Jiří (referee) ; Věchet, Stanislav (advisor)
This bachelor’s thesis is aimed at current trends and hardware solutions in the field of autonomous vehicles (AVs). Firstly, the definition of AV is presented and levels of autonomy are listed according to several criteria. This is followed by a brief overview of the early stages and historical development of AVs and by an introduction of sensors needed for their operation. The following part focuses on AVs created at DARPA Grand Challenge competition, which inspire even present-day companies. Next chapter describes leading companies in the area AV development, their approach to sensor selection and placement and their main goals. Furthermore, possible real applications of AVs and current pilot projects are presented. In the last part, results of this research are used to design a custom experimental AV.
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Injection locked ring oscillator design for application in Direct Time of Flight LIDAR
Fránek, Jakub ; Háze, Jiří (referee) ; Kledrowetz, Vilém (advisor)
Diplomová práce přibližuje systémy LIDAR přímo měřící čas průletu a časově digitální převodníky určené k použití v těchto systémech. Představuje problematiku distribuce hodinových signálů napříč soubory časově digitálních převodníků v LIDAR systémech a věnuje se jednomu z nových řešení této problematiky, které je založené na injekcí zavěšených oscilátorech. Technika injekčního zavěšení oscilátorů je důkladně matematicky popsána. V programu Matlab byl vytvořen simulační model injekcí zavěšeného kruhového oscilátoru, který potvrzuje správnost uvedených analytických predikcí. Ve výrobní technologii ONK65 byl navržen injekcí zavěšený kruhový oscilátor stabilizovaný pomocí smyčky závěsu zpoždění, určený pro implementaci časově digitálního převodníku pro systém LIDAR. Navržený injekcí zavěšený kruhový oscilátor byl verifikován počítačovými simulacemi zohledňujícími vliv procesních, napěťových i teplotních variací. Oscilátor poskytuje specifikované časové rozlišení 50 pikosekund a dosahuje dvakrát nižší hodnoty fázového neklidu než ekvivalentní volnoběžný oscilátor v dané technologii.
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