Student projects and final assignments

Final work under mentorship: dr. Dušan Gleich, dr. Andrej Sarjaš

Description: The master's thesis presents the development and testing of a rocket system for autonomous vertical landing using an electric ducted fan (EDF) propulsion system and thrust vector control. It includes a review of existing technologies, control theory and the practical construction of a prototype. The focus is on the design of mechanical assemblies and the implementation of stabilization algorithms. The system is based on a cascaded controller architecture. The result is a functioning prototype capable of autonomous hovering and controlled landing. The thesis contributes to the development of cost-effective research platforms for testing vertical landing technologies.

Description: This master’s thesis presents a hardware-in-the-loop (HIL) framework for the implementation of adaptive control of nonlinear systems. Several control strategies are investigated, such as backstepping, sliding mode control (SMC), PD control, and a proposed hybrid approach. For simulation purposes, a brushless DC motor is modeled as a second-order system in Simulink, while the control algorithms are executed on a Beckhoff Programmable Logic Controller communicating via the ADS protocol. The study evaluates the performance and robustness of the implemented methods, demonstrating the effectiveness of the HIL approach for real-time validation of advanced control strategies.

Description: This master's thesis presents a method for drone detection that using a system that integrates an optical camera and a radar. In the visual subsystem, objects were detected with the YOLOv8 algorithm, implementeed on the energy-efficient NVIDIA Jetson Orin Nano platform, enabling real-time processing. The radar subsystem is based on an FMCW radar exploiting the Doppler effect, operating at 10 GHz with a 500 MHz bandwidth, which allows precise range and velocity estimation. Experimental results showed that combining visual and radar data increases the robustness and reliability of drone detection in diverse environmental conditions.

Description: This master’s thesis examines the development and construction of a two-wheeled robot capable of self-balancing, navigating uneven terrain, and overcoming various obstacles. The primary goal was to design a system that integrates mechanical design, control algorithms, and sensing for stable and agile movement. The mechanical structure includes a robust frame, drive system, and power supply, optimized to minimize changes in the center of mass during motion. The control system is based on an LQI controller for balancing, complemented by algorithms for agile driving and upper body motion. The thesis presents simulations, implementation on an STM32 microcontroller, and experimental testing. The results show that the robot achieves stable balancing, responsive driving, and robustness to disturbances, confirming the suitability of the chosen design and control approaches.

Description: The thesis addresses the thrust vector control of an air fan, which affects the inclination of the entire mechanism. Thrust vector control is accomplished by a thrust vectoring mechanism (gimbal) and is used in aviation, especially in military fighter jets for enhancing the maneuverability of the aircraft. The concepts described can also be used as a foundation for designing thrust vector control with rocket propulsion systems. The thesis contains a description of the thrust vector control concept with examples of 3D modeling. Lastly, it includes the design and implementation of a closed-loop system. The results demonstrate the effectiveness of thrust vector control in increasing the maneuverability of the aircraft.

Description: In our diploma thesis, we created a robotic manipulator. For this purpose, we developed algorithms for performing point-to-point and linear motion. When performing these motions, we used square, cubic, and sinusoidal path profiles. We created a graphical interface for controlling the robotic manipulator. We upgraded the robot with a camera. Using a neural network and machine vision, we created an application where the top of the robot follows the user's hand. We previously simulated the motion algorithms and path profiles using the MSC Adams program.

Description: The doctoral dissertation presents the development of an air-coupled georadar for the detection of explosive devices below the ground surface with combination of an unmanned aerial vehicle. As the weight and autonomy of such an unmanned aerial vehicle is extremely critical this requires special care in the development of such a georadar system. For this purpose, a georadar is developed that emits a continuous wave and works on the Stepped Frequency Continuous Wave (SFCW) method. The use of this method, as well as a carefully designed receiver based on a hybrid analog-digital superheterodyne architecture, eliminated the need of a transmitter power amplifier. Such an approach has enabled us to create a complete system using integrated electronic components which ensure low power consumption and compact design. Nevertheless, the system offers a resolution in a few centimeters, which allows the detection of even the smallest explosive devices. The system was tested in a laboratory environment as well as on a test polygon in combination with a commercial unmanned aerial vehicle. In order to ensure even greater detection success, we introduced the use of polarization, which extends the existing georadar image to multichannel. Furthermore, we also developed a system for eliminating unwanted reflections, which removes the echo signals already on of the receiver input, and enables to higher the receiver gain to make the weak scatter of targets of interest more visible.

Description: The master's thesis describes the design of the two-drone system, the development of control algorithms and the generation of trajectories. The basic equations of geographical calculations are given, which represent the basic building blocks of the algorithms. Three control algorithms have been developed, which are the flyover algorithm between two defined coordinates, the circular turning maneuver algorithm and the algorithm for generating the trajectory of the slave aircraft, defined on the basis of the trajectory of the master aircraft. The proposed solution enables the synchronous flight of aircraft intended for bistatic radar. The composition of the system, component functionality and interconnection are described. The evolving wireless network protocol IEEE 802.11ah is implemented for communication between aircraft. The developed control algorithms are tested in a simulation environment and on a real system.

Description: The purpose of this master's thesis is establishment of an RTK system with ability to operate in three different modes and development of a user interface to mark the desired area, generate the shortest route and display RTK receiver's real time coordinates. The thesis is divided into two parts. The first part shows complete process of configuring RTK devices, setting up the base station, transmitting RTK correction via radio communication and the use of UBX protocol. The process of creating a user interface including the most important sections of the algorithm, the implementation of the ROS system and field measurement results are presented in the second part.

Description: The master's thesis is based on the processing of satellite images and the use of deep convolutional neural networks. In the content there is described research work in the field of polarimetric SAR. The purpose of the work is to design and manufacture a system, that could be able to process a satellite image so that soil moisture can be determined from it. To evaluate this, we used deep convolutional neural networks, which we believe could prove very useful. In the developing process, we used programs for processing atmospheric images using polarimetry. such as PolSARpro and SNAP. The Python programming language in the Visual Studio environment was used to further process the images and design the deep convolutional neural network.

Description: The master's thesis describes and presents the process of face detection and recognition using radar and lidar techniques. The first part describes the operation of the radar and presents the procedures for placing targets in the visible area of the radar and processing signals to obtain the final image. The second part shows the process of capturing images of perceived faces with Kinect and training of the model with Siamese neural network for face recognition. The conclusion presents the results of research and verification of face detection and recognition with radar and Kinect.

Description: The master‘s thesis describes hand fingers recognitions problematic, with which we could in a background manage different tasks and processes. It is designed to provide a solution of same problematic using two different approaches and provide theirs advantages and disadvantages. It directly analyzes this problematic using Pattern image matching technology. We were looking for a pattern in image, with which we could detect and classify hand fingers gesture. Using Deep learning technology, an artificial intelligence has been used to search for a pattern in image, but for this we needed a large image database with solved cases of fingers classification. Findings arising from this thesis give good basis to researchers and engineers to make further development and implementation of image recognitions systems based on Machine visions or Deep learning technology.

Description: The final work describes the network control of an air levitation system by implementing two control algorithms on a remote computer and effect of network control on the controller performance. The content of the thesis describes the component of air levitation, mathematical modeling, implementation of simulations with the Matlab / Simulink software package, implementation of the PID controller and the controller based on the sliding mode. The work includes a comparison of control in network and non-network mode of closed-loop control. The goal of the task is to design the controllers so that they will be able to control the system via the UDP communication protocol with delays..

Description: The aim of the master's thesis was to recognize breathing and heart rate. We used radar technology in three different transmitting modes and propagating EM waves. All three methods provided a theoretical starting point in the measurement. The used operation modes are frequency-modulated continuous wave, stepped frequency continuous wave, and pulsed. Finally, based on the measurements, we evaluated the suitability of all implementation procedures in Radar as follows. Signal processing for all systems was performed in MATLAB program.

Description: This master’s thesis presents an estimation of objects external coordinates using two cameras. The system in this way allows us contactless determination of external object coordinates. We present to use an evaluate accuracy estimate of the external coordinates. The knowledge that we have gained from the first system we also used to estimate the external orientation coordinates of human head. Beginning chapters describe the basics of digital photography and theoretical background of lens distortion, when an image was acquired with a camera. Outlined is also the procedure for modeling the lens distortion. The sections covers the design of a marker. The biggest challenge in this approach was to achieve accuracy of markers position and its estimation within 20 ms. Next sections describe the method for estimation the external coordinates of head orientation, and the problems that have arisen during the thesis. The last chapters presents measurement results. Conclusion concludes the thesis.