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Tabletop Object Detection
Timko, Martin ; Veľas, Martin (referee) ; Kapinus, Michal (advisor)
The aim of this thesis is to design and create a module for robotic platform PR2. This module has to detect objects in front of the robot on a table and enable various operations with these objects. This thesis describes methods of object detection which were used in the implementation of the module. The thesis also describes the methods used for design and implementation of this module. The module testing and evaluation of results are mentioned at the end of the thesis.
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Cell transplantation methods in cardiology
Kukhta, Dziyana ; Hežová,, Reneta (referee) ; Skopalík, Josef (advisor)
Tato diplomová práce se zabývá tkáňovým inženýrstvím, zejména tvorbou homogenní, izotropní a planární vrstvy buněk srdečního svalu pomocí dvou technologii:”scaffold-based” a ”scaffold-free”. Nejprve popsaný histologie srdeční stěny, buňky srdečního svalu a buněčné kultury. Následuje popis tkáňového inženýrství, který zahrnuje technologii “cell sheet” a tkáňové inženýrství na bázi scaffoldů. Na konci teoretické části je popsána aplikace tkáňového inženýrství a buněčná vizualizace. Praktická část věnovaná tvorbě planární buněčné vrstvy z kardiomyocytů a fibroblastů s využitím informací z teoretické části.
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Object Detection in the Laser Scans Using Convolutional Neural Networks
Marko, Peter ; Beran, Vítězslav (referee) ; Veľas, Martin (advisor)
This thesis is aimed at detection of lines of horizontal road markings from a point cloud, which was obtained using mobile laser mapping. The system works interactively in cooperation with user, which marks the beginning of the traffic line. The program gradually detects the remaining parts of the traffic line and creates its vector representation. Initially, a point cloud is projected into a horizontal plane, crating a 2D image that is segmented by a U-Net convolutional neural network. Segmentation marks one traffic line. Segmentation is converted to a polyline, which can be used in a geo-information system. During testing, the U-Net achieved a segmentation accuracy of 98.8\%, a specificity of 99.5\% and a sensitivity of 72.9\%. The estimated polyline reached an average deviation of 1.8cm.
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Causes of Premature Capacity Loss of Lead-Acid Accumulators Operating in PSoC Mode in Hybrid Electric Vehicles
Bilko, Radek ; Jareš, Petr (referee) ; Dostál, Zdeněk (referee) ; Bača, Petr (advisor)
This thesis is completion of whole stage of researches and it is a result of existing need of increase efficiency, utilization rate and service life of lead acid batteries VRLA planned for utilization in hybrid electric vehicles in mode of partial state-of-charge PSoC. During the application of mode PSoC at lead acid battery occurs irreversible sulfation of negative electrodes and thus to loss their charging capability. This phenomenon, according to the latest trend called PCL3, isn´t connected with subsequently referred effects PCL1, PCL2, show up on positive electrodes. Result of this thesis is finding a new types of additives, determine their optimum amount and size in such a way that innovated composition of negative active materials be able to resist sulfation of negative electrode during operation in mode PSoC. Part of the effort to clarify actions ongoing on negative active material and causes non-returnable sulfation electrodes is also monitoring of structural changes electrode active material by using environmental scanning electron microscope, which helped to clarify processes related with loss of capacity in mode PSoC. Special attention during reserches was focused on study of the properties contact layers between collector and electrodes active material and itself active materials lead-acid battery druring exploitation. There were gain new information about influence repeated cycling of (charging, discharging) the critical area of the electrodes. Measurements was carried out on specially prepared experimental electrodes DC Difference Method, this enabled obtain data in situ.
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Tabletop Object Detection
Varga, Tomáš ; Zemčík, Pavel (referee) ; Španěl, Michal (advisor)
This work describes the issue of tabletop object detection in point cloud. Point cloud is recorded with Kinect sensor. Designed solution uses algorithm RANSAC for plane detection, algorithm Euclidean clustering for segmentation and ICP algorithm for object detection. Algorithm ICP is modified and mainly it can detect rotational symetric objects and objects without any transformation against it's models. The final package is build on platform ROS. The achieved results with own dataset are good despite of the limited functionality of the detector.
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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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Automated System for Components Scanning
Hřib, Jan ; Boštík, Ondřej (referee) ; Jirgl, Miroslav (advisor)
The aim of this thesis is to design an automated scanning system for components for the purpose of inspecting their dimensions and tolerances. The theoretical introduction provides the reader with basic information on the topic of 3D scanning. The work also includes the design of own scanning system. The greatest attention is paid to the design of a program using the PCL library. The aim of the program is automatic processing of data from a 3D scanner and evaluation of the required dimensions of the scanned component. The final part of the work is devoted to testing the proposed solution.
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Calibration of Robotic Workspace
Uhlíř, Jan ; Veľas, Martin (referee) ; Kapinus, Michal (advisor)
This work is concerned by the issue of calibrating a robotic workplace, including the localization of a calibration object for the purpose of calibrating a 2D or 3D camera, a robotic arm and a scene of robotic workplace. At first, the problems related to the calibration of the aforementioned elements were studied. Further, an analysis of suitable methods for performing these calibrations was performed. The result of this work is application of ROS robotic system providing methods for three different types of calibration programs, whose functionality is experimentally verified at the end of this work.
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3D Model of a Room Using Kinect
Zemek, Martin ; Veľas, Martin (referee) ; Španěl, Michal (advisor)
This thesis is about finding significant planar surfaces in point cloud and their conversion to polygons. Which is important step for making a 3D model of a room. Input is point cloud, which was recorded by Kinect v2 sensor. Tool for capturing one snapshot from Kinect is included in this thesis. For recording more detailed point cloud is needed external program. Some of the programs are mentioned further in this thesis. For plane detection is used RANSAC. Inliers are divided using Euclidean Cluster Extraction. These clusters are converted to polygon using convex or concave hull. Application is capable of working with one snapshot or bigger point cloud assembled by registration of particular snapshots and detect primary and secondary planar surfaces. For the largest plane points can be prepared for creation of a texture and dimensions of this plan can be printed in CLI.
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Basic Shapes Detection in Point Clouds
Eldes, Pavol ; Materna, Zdeněk (referee) ; Španěl, Michal (advisor)
This thesis deals with the topic of simple geometric shapes detection from point-clouds with a special interest in the influence of point normals on speed and quality of produced results. Its main product is an application that demonstrates detection of planes, spheres and cylinders. Detection is done using the RANSAC paradigm that is modified in this thesis to allow it to work with multiple models simultaneously. Another modification presented in this thesis focuses on enforcing stricter candidate shapes selection conditions for detection models.
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