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The design of a quadrocopter for food delivery
Gryc, Matěj ; Čípek, Pavel (referee) ; Skurka, Šimon (advisor)
Online delivery of hot food to the customer's home has become standard. However, as a result of the covid-19 pandemic, methods of safe delivery that do not require interpersonal contact are now being sought. The use of drones, which are already being used in some countries to transport goods and materials, seems promising. This bachelor thesis deals with the design and assembly of a quadcopter designed for food delivery. First, the frame was designed, which was largely fabricated using 3D printing. Based on calculations, the electronics including batteries and motors were selected. Then the mechanism by which the food transport will be mediated was designed. Once constructed, the functionality of the quadcopter and delivery mechanism was tested. Finally, the design was evaluated and possible improvements were mentioned.
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Drone position stabilization methods using image data
Koukal, Ondřej ; Raichl, Petr (referee) ; Janoušek, Jiří (advisor)
This bachelor’s thesis focuses on the design of an unmanned aircraft stabilization system. The purpose of this system is to determine the exact position of the unmanned aircraft in space based on image data from two cameras in real time. The theoretical part describes the image processing methods and the algorithm for determining the position of the unmanned aircraft. The practical part describes the implementation and testing of the system.
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Aerial Refueling
Ďurďovič, Dušan ; Horpatzká, Michaela (referee) ; Dubnický, Lukáš (advisor)
This thesis is focused on aerial refueling. This paper describes brief history of development for both methods, aplication of both methods and also their construction description on both tanker and receiving aircraft. Last chapter focuses on current development of these methods and concepts for possible future aplication in aerospace engineering.
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Tracking People in Video Captured from a Drone
Lukáč, Jakub ; Orság, Filip (referee) ; Goldmann, Tomáš (advisor)
Práca rieši možnosť zaznamenávať pozíciu osôb v zázname z kamery drona a určovať ich polohu. Absolútna pozícia sledovanej osoby je odvodená vzhľadom k pozícii kamery, teda vzhľadom k umiestneniu drona vybaveného príslušnými senzormi. Zistené dáta sú po ich spracovaní vykreslené ako príslušné cesty v grafe. Práca si ďalej dáva za cieľ využiť dostupné riešenia čiastkových problémov: detekcia osôb v obraze, identifikácia jednotlivých osôb v čase, určenie vzdialenosti objektu od kamery, spracovanie potrebných senzorových dát. Následne využiť preskúmané metódy a navrhnúť riešenie, ktoré bude v reálnom čase pracovať na uvedenom probléme. Implementačná časť spočíva vo využití akcelerátoru Intel NCS v spojení s Raspberry Pi priamo ako súčasť drona. Výsledný systém je schopný generovať výstup o polohe detekovaných osôb v zábere kamery a príslušne ho prezentovať.
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Visualization Tool for Drone Pilot in Microsoft HoloLens 2
Kyjac, Martin ; Herout, Adam (referee) ; Bambušek, Daniel (advisor)
When piloting a drone, the pilot must monitor both the drone itself and various flight data. This activity requires constant concentration and even less inattention can lead to an accident. Especially when flying at greater distances, the pilot can very easily lose track of where the drone is located, which side it is heading to, or how high it is. To verify this information, it is necessary in common applications to tilt the head and thus lose sight of the drone because this data is located on the controller, which the pilot holds in his hands. This context switching is very impractical. The goal of this application is to visualize this data using augmented reality displayed through Microsoft Hololens 2. All necessary flight data is displayed using holograms at the exact same position where the drone itself is in the sky, so the pilot does not have to switch between contexts. It is also much easier to display various elements of the mission in this way. Normally in such cases, the pilot has to somehow interpret the data from the 2D map into reality, which can be challenging. However, with augmented reality, this data can be displayed directly into the real world.
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Drone swarm control
Kolísek, Josef ; Marcoň, Petr (referee) ; Janoušek, Jiří (advisor)
This thesis focuses on the drone swarm control and the using in practice. It is about the interconnection of several control units of drones and subsequent coordination in the air. The work is divided into theoretical part and practical part. The practical part describes the possibilities of drone swarm flying and coordination of multiple drones. Possible ways of communication and transmission of telemetry data for control using the MAVLink protocol. The next part describes the possibilities of controlling multiple units from one central point and creating flight instructions. The practical part deals with the realization of the software for synchronized flight of two unmanned aircraft and their connection with the ground control station for the transmission of flight instructions. The last part of the work deals with evaluation of the control, compliance of the established flight plan and the proposal of other possibilities for improvement with the solution of deficiencies.
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Laws Concerning Drone Use in the Real Estate Practice
Klementová, Tereza ; Jandásková, Tereza (referee) ; Klika, Pavel (advisor)
This thesis focuses explores the laws for drone use in the real estate practice. In each chapter, the legislation for the commercial use of drones is described for the following states - the Czech Republic, Slovakia, France, Belgium, the Great Britain and the United States of America. In the final chapter there is a comparison of different law aspects from all studied countries.
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Anti-Drone Perimeter Protection
Janík, Roman ; Dvořák, Michal (referee) ; Drahanský, Martin (advisor)
Developement of drone technology brings opportunities for many fields of human activity, but simultaneously brings security threats. A need to effectively face these threats arises. In this work is described the problematics and state-of-the-art methods for object detection in a video captured by moving camera. A system for detecting and locating a drone or a flock of drones has been proposed. Algorithm for detection is based on convolutional neural network, specifically on SSD algorithm. The convolutional neural network was trained on self-made dataset. The system was implemented using OpenCV library with possible algorithm acceleration on GPU using OpenCL. Created solution was tested on video.
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