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Achieving autonomous inclined landing would be an important step towards quadrotors which are able to land anywhere and under any conditions. If a quadrotor is able to safely land anywhere, even when a landing platform is not available, this would open up many useful applications. Firstly, the quadrotor could safely land whenever its battery levels get low or when contact with an operator is lost. Secondly, the quadrotor could be used for different applications, such as reconnaissance, search and rescue, infrastructure or delivery services. There are many challenges to the field of autonomous inclined quadrotor landing. Firstly, landing safely on an inclined surface without the use of a perching mechanism requires that the quadrotor has a low approach velocity. The quadrotor should also land at the same angle as the inclination of the landing surface. To meet these constraints, the quadrotor will be required to perform an agile landing maneuver. Furthermore, the quadrotor will also have to estimate its attitude, position and velocity towards the platform during the landing maneuver. Due to the agile landing maneuver, landmark-based localization of the quadrotor will be more difficult, since these methods require the quadrotor's on-board camera to be directed at a certain landmark which can be used for guidance. Current methods for autonomous inclined landing either use external sensors or a landing mechanism to deal with the presented challenges. During this project, an algorithm is developed which can estimate the quadrotor's attitude, position and velocity during the landing maneuver, while using only on-board sensors. State estimations are generated using two sources: a landmark-based localization algorithm and a Visual-Inertial Odometry (VIO) algorithm. The landmark-based localization algorithm uses markers placed near the landing surface to determine the quadrotor's attitude and position relative to the, Mechanical Engineering | Vehicle Engineering | Cognitive Robotics

Simulation environments are useful for a wide range of applications and their functionalities continue to improve every year. The aim of this thesis project was to create a simulation environment with high levels of realism and assess its capabilities through the use case of generating distributed drone traffic rules. This thesis project was executed at the company Almende in cooperation with its sub-company DoBots. The distributed drone traffic rule generation use case was a contribution to the ADACORSA project which Almende takes part in. The goals of the thesis were the following. A simulation environment incorporating elements of realism was created using the software tools Almende has experience with. The capabilities of this environment were tested through the said use case. According to company requirements, this process was realised using an incremental complexity approach, and it utilized machine learning techniques. It was expected that the incremental complexity approach would help speed up the learning process of more complex scenarios, while machine learning would provide the benefit of smart automation and impartiality to solutions. For this process, a model was also devised for creating such rules, incorporating the incremental complexity approach and a standard machine learning technique. Finally, the benefits of the incremental complexity approach were also assessed. The four building blocks of the implemented simulation environment were Gazebo, PX4, ROS2 and the iris drone model. The code was built upon the OpenAI ROS software package, with extensive modifications. The main work done during the implementation consisted of multiple parts. The original software package was cleaned of unnecessary elements, the PX4 software and the iris drone model were integrated into the environment and the simulation speed was increased. The whole setup was migrated from ROS to ROS2. The use of multiple drones in the same environment was also solve, Mechanical Engineering | Vehicle Engineering | Cognitive Robotics

[ES] Este TFM se centra en la implementación del piloto automático de código libre PX4 en un UAS ("Unmanned Aircraft System") de tipo VTOL ("Vertical Take Off and Landing") de largo alcance. El proceso consiste en la verificación del piloto automático mediante la ejecución, en primer lugar, de simulaciones de tipo "Software In The Loop" y "Hardware In The Loop" y pruebas de vuelo con una aeronave de menor alcance, para llevar a cabo una posterior simulación equivalente e implementación del firmware en la aeronave más avanzada de largo alcance., [EN] This Final Master's Thesis is focused on the implementation of an open source autopilot in a long range VTOL (Vertical Take Off and Landing) UAS (Unmanned Aircraft System). The process consists in the verification of the autopilot, by first running Software In The Loop and Hardware In The Loop simulations and flight tests with a short range test aircraft, and afterwards an equivalent simulation and implementation on a more advanced long range vehicle., [CA] Aquest TFM es centra en la implementació d’un pilot automàtic de codi lliure en un UAS ("Unmanned Aircraft System") de tipus VTOL ("Vertical Take Off and Landing") de llarg abast. El procés consistix en la verificació del pilot automàtic mitjançant l’execució en primer lloc de simulacions de tipus "Software In The Loop" y "Hardware In The Loop" i proves de vol amb una aeronau de minor abast, per a dur a terme una posterior simulació equivalent i implementació en l’aeronau més avançada de llarg abast

[ES] Este TFM se centra en la implementación del piloto automático de código libre PX4 en un UAS ("Unmanned Aircraft System") de tipo VTOL ("Vertical Take Off and Landing") de largo alcance. El proceso consiste en la verificación del piloto automático mediante la ejecución, en primer lugar, de simulaciones de tipo "Software In The Loop" y "Hardware In The Loop" y pruebas de vuelo con una aeronave de menor alcance, para llevar a cabo una posterior simulación equivalente e implementación del firmware en la aeronave más avanzada de largo alcance., [EN] This Final Master's Thesis is focused on the implementation of an open source autopilot in a long range VTOL (Vertical Take Off and Landing) UAS (Unmanned Aircraft System). The process consists in the verification of the autopilot, by first running Software In The Loop and Hardware In The Loop simulations and flight tests with a short range test aircraft, and afterwards an equivalent simulation and implementation on a more advanced long range vehicle., [CA] Aquest TFM es centra en la implementació d’un pilot automàtic de codi lliure en un UAS ("Unmanned Aircraft System") de tipus VTOL ("Vertical Take Off and Landing") de llarg abast. El procés consistix en la verificació del pilot automàtic mitjançant l’execució en primer lloc de simulacions de tipus "Software In The Loop" y "Hardware In The Loop" i proves de vol amb una aeronau de minor abast, per a dur a terme una posterior simulació equivalent i implementació en l’aeronau més avançada de llarg abast

[ES] Este TFM se centra en la implementación del piloto automático de código libre PX4 en un UAS ("Unmanned Aircraft System") de tipo VTOL ("Vertical Take Off and Landing") de largo alcance. El proceso consiste en la verificación del piloto automático mediante la ejecución, en primer lugar, de simulaciones de tipo "Software In The Loop" y "Hardware In The Loop" y pruebas de vuelo con una aeronave de menor alcance, para llevar a cabo una posterior simulación equivalente e implementación del firmware en la aeronave más avanzada de largo alcance., [EN] This Final Master's Thesis is focused on the implementation of an open source autopilot in a long range VTOL (Vertical Take Off and Landing) UAS (Unmanned Aircraft System). The process consists in the verification of the autopilot, by first running Software In The Loop and Hardware In The Loop simulations and flight tests with a short range test aircraft, and afterwards an equivalent simulation and implementation on a more advanced long range vehicle., [CA] Aquest TFM es centra en la implementació d’un pilot automàtic de codi lliure en un UAS ("Unmanned Aircraft System") de tipus VTOL ("Vertical Take Off and Landing") de llarg abast. El procés consistix en la verificació del pilot automàtic mitjançant l’execució en primer lloc de simulacions de tipus "Software In The Loop" y "Hardware In The Loop" i proves de vol amb una aeronau de minor abast, per a dur a terme una posterior simulació equivalent i implementació en l’aeronau més avançada de llarg abast

Drones have been used by the military since mid-1970 but the development of autonomous systems from the turn of the millennium and onward has opened the area of UAV to civil service and the public immensely. Today UAV technology saves lives in Search And Rescue operations, complements and supports full scale vehicles at the Police force and assists in surveys and documentation of ground and forests. UAS contributes in areas where manned aircraft can’t reach, is too expensive and where the noise from full scale crafts would drown the scream in a search operation. From an environmental point of view UAS is far ahead of manned flight in electrification and its smaller size and lower maintenance saves scarce resources. The development of drones covers a wide area of expertise from traditional aeronautics, electronics, control theory, software development, air law and Artificial Intelligence. There are a few organizations and companies that dominate the field but as a new science UAS is not established such as computer science and has few research authorities among universities. This paper is an explorative research of UAS use within Swedish civil service. Interviews based on a selection of authorities, picked from an expert group at Lund University, have made the foundation of this qualitative study. This research covers: How UAS is implemented, legal aspects, collaboration and vision. To ensure a structured and systematic analysis, established organizational theory with Value-chain, Power–Interest-matrix and Strategic Capability have been used. Key factors of UAS history & development, open control systems and aeronautic culture are also covered. With added support from UAS-lawyer and Transportstyrelsen an introduction of drone law finalize the chapter of theory. Workshops at Ljungbyhed have been held during a week in spring 2022, covering Human Factors and SAR UAS. Numerous presentations from leading Swedish UAS authorities contributed with additional views to ensure

Drones have been used by the military since mid-1970 but the development of autonomous systems from the turn of the millennium and onward has opened the area of UAV to civil service and the public immensely. Today UAV technology saves lives in Search And Rescue operations, complements and supports full scale vehicles at the Police force and assists in surveys and documentation of ground and forests. UAS contributes in areas where manned aircraft can’t reach, is too expensive and where the noise from full scale crafts would drown the scream in a search operation. From an environmental point of view UAS is far ahead of manned flight in electrification and its smaller size and lower maintenance saves scarce resources. The development of drones covers a wide area of expertise from traditional aeronautics, electronics, control theory, software development, air law and Artificial Intelligence. There are a few organizations and companies that dominate the field but as a new science UAS is not established such as computer science and has few research authorities among universities. This paper is an explorative research of UAS use within Swedish civil service. Interviews based on a selection of authorities, picked from an expert group at Lund University, have made the foundation of this qualitative study. This research covers: How UAS is implemented, legal aspects, collaboration and vision. To ensure a structured and systematic analysis, established organizational theory with Value-chain, Power–Interest-matrix and Strategic Capability have been used. Key factors of UAS history & development, open control systems and aeronautic culture are also covered. With added support from UAS-lawyer and Transportstyrelsen an introduction of drone law finalize the chapter of theory. Workshops at Ljungbyhed have been held during a week in spring 2022, covering Human Factors and SAR UAS. Numerous presentations from leading Swedish UAS authorities contributed with additional views to ensure

Recent developments have enabled the mass production of cheap, high-performance multirotors. As a result of this, the multirotor has found a large variety of different uses. Testing new algorithms using real-life flights is costly in terms of time and potentially in terms of materials in the case of a crash. Simulators have quickly gained prominence as a tool in algorithm development. The accuracy of these simulators is vital to ensure the step from simulated flights to real-life testing is as small as possible. Current simulator models are held back due to a lack of properly identified multirotor coefficients. Often, the coefficients from a different multirotor are used, even if the new multirotor is vastly different in shape and size. Additionally, most researchers do not have a sufficient overview of which parts of the simulator are most important in providing an accurate simulator environment. This research will give an overview of the different parts that influence the simulator results. The simulation of the motor controllers and rotor aerodynamics is identified as a major contributor to inaccuracies. The coefficients used in these two components will be found by performing a system identification process of the NXP HoverGames quadcopter. This identification process entails determining the mass, dimensions, inertia, motor response and thrust, torque, rotor drag and rolling moment coefficients. Experiments will be performed to find the correct coefficient values and to evaluate the impact that each effect has on the simulator's performance. A focus is put on ease of repeatability, such that other researchers can use the same process for their specific multirotor. The theoretical background behind each effect in the motor controller and rotor aerodynamics models is discussed. This theoretical knowledge is used to perform experiments to find the coefficients for each effect and validate them. As a result, new coefficients for the motor controlle

This work was born with the intention of giving an alternative solution to those professionals exposed to polluting gases, especially those who have to do daily inspections in homes to check the proper combustion of boilers risking their own health. From this problem arises the idea of doing this review using drone technology, increasingly used and known, in order to generate a map for the control of emissions (carbon monoxide) without direct contact. The work includes the methodology used to date. The most suitable type of drone for this application is studied and mounted together with all the necessary hardware. Once assembled, we create the software and see how it works thanks to different tests and flight simulations. Finally, we study the current regulations, the results obtained and the possible improvements that we can add in order to increase the efficiency and safety of the measuring equipment.

A redundant fast prototyping autopilot solution for unmanned aerial systems has been developed and successfully tested outdoors. While its low-level backbone is executed in a Raspberry Pi R 3 + NAVIO2 R with a backup autopilot, the computational power of an Intel R NUC mini-computer is employed to implement complex functionalities directly in Simulink R , thus including in-flight debugging, tuning and monitoring. Altogether, the presented tool provides a flexible and user-friendly high-level environment with enhanced computational capabilities, which drastically reduces the prototyping timespans of complex algorithms –between 50% and 75%, according to our long and proven experience in aerial robotics–, while preventing incidents thanks to its redundant design with a human-in-the-loop pilot on the reliable PX4. Three typical outdoor cases are carried out for validation in real-life scenarios, all mounted in a DJI c F550 platform. Full integration results and telemetry for more than 50 hours of outdoor flight tests are provided.

[ES] El presente trabajo tiene como objetivo el desarrollo de un entorno de simulación SITL (Software In The Loop) para la aeronave no tripulada del proyecto HERMES-UPV, haciendo uso del firmware de control de vuelo PX4 Autopilot. Para ello, se establece el modelo matemático de la dinámica de la aeronave que se simula mediante la herramienta Simulink. A esta simulación se le dota de una interfaz gráfica gracias al simulador de vuelo FlightGear. Por su parte, PX4 Autopilot proporciona el sistema de navegaciónn y control, el cual es posible modificar y adaptar para distintas plataformas hardware y llevar a cabo simulaciones HITL (Hardware In The Loop) y ensayos en vuelo real., [EN] The present project has as purpose the development of a SITL (Software In The Loop) simulation enviroment for the unmanned aircraft of HERMES-UPV project, making use of the flight control firmware PX4 Autopilot. To do so, it¿s established the mathematical model of the aircraft dynamics which is simulated by the toolbox Simulink. This simulation is equipped with a graphical interface thanks to the flight simulator FlightGear. PX4 Autopilot provide the navegation and control system, which is possible to be modificated and adapted for different hardware platforms and perform HITL (Hardware In The Loop) simulations and real flight tests.

[ES] El presente trabajo tiene como objetivo el desarrollo de un entorno de simulación SITL (Software In The Loop) para la aeronave no tripulada del proyecto HERMES-UPV, haciendo uso del firmware de control de vuelo PX4 Autopilot. Para ello, se establece el modelo matemático de la dinámica de la aeronave que se simula mediante la herramienta Simulink. A esta simulación se le dota de una interfaz gráfica gracias al simulador de vuelo FlightGear. Por su parte, PX4 Autopilot proporciona el sistema de navegaciónn y control, el cual es posible modificar y adaptar para distintas plataformas hardware y llevar a cabo simulaciones HITL (Hardware In The Loop) y ensayos en vuelo real., [EN] The present project has as purpose the development of a SITL (Software In The Loop) simulation enviroment for the unmanned aircraft of HERMES-UPV project, making use of the flight control firmware PX4 Autopilot. To do so, it¿s established the mathematical model of the aircraft dynamics which is simulated by the toolbox Simulink. This simulation is equipped with a graphical interface thanks to the flight simulator FlightGear. PX4 Autopilot provide the navegation and control system, which is possible to be modificated and adapted for different hardware platforms and perform HITL (Hardware In The Loop) simulations and real flight tests.

[ES] El presente trabajo tiene como objetivo el desarrollo de un entorno de simulación SITL (Software In The Loop) para la aeronave no tripulada del proyecto HERMES-UPV, haciendo uso del firmware de control de vuelo PX4 Autopilot. Para ello, se establece el modelo matemático de la dinámica de la aeronave que se simula mediante la herramienta Simulink. A esta simulación se le dota de una interfaz gráfica gracias al simulador de vuelo FlightGear. Por su parte, PX4 Autopilot proporciona el sistema de navegaciónn y control, el cual es posible modificar y adaptar para distintas plataformas hardware y llevar a cabo simulaciones HITL (Hardware In The Loop) y ensayos en vuelo real., [EN] The present project has as purpose the development of a SITL (Software In The Loop) simulation enviroment for the unmanned aircraft of HERMES-UPV project, making use of the flight control firmware PX4 Autopilot. To do so, it¿s established the mathematical model of the aircraft dynamics which is simulated by the toolbox Simulink. This simulation is equipped with a graphical interface thanks to the flight simulator FlightGear. PX4 Autopilot provide the navegation and control system, which is possible to be modificated and adapted for different hardware platforms and perform HITL (Hardware In The Loop) simulations and real flight tests.

A redundant fast prototyping autopilot solution for unmanned aerial systems has been developed and successfully tested outdoors. While its low-level backbone is executed in a Raspberry Pi R 3 + NAVIO2 R with a backup autopilot, the computational power of an Intel R NUC mini-computer is employed to implement complex functionalities directly in Simulink R , thus including in-flight debugging, tuning and monitoring. Altogether, the presented tool provides a flexible and user-friendly high-level environment with enhanced computational capabilities, which drastically reduces the prototyping timespans of complex algorithms –between 50% and 75%, according to our long and proven experience in aerial robotics–, while preventing incidents thanks to its redundant design with a human-in-the-loop pilot on the reliable PX4. Three typical outdoor cases are carried out for validation in real-life scenarios, all mounted in a DJI c F550 platform. Full integration results and telemetry for more than 50 hours of outdoor flight tests are provided.

The mission control of a fixed-wings UAV is slightly more complex compared to other models like quad-rotors or unicycles since the dynamic of a fixed-wing aircraft does not allow rapid direction changes or stop-rotate-go type of movements. Those restriction needs to be taken into consideration when building a mission control system, moreover, the problem increases in complexity when the goal is to fly in formation with several UAVs, indeed during its development, we have to handle also the scalability of the communication link and the robustness of the formation during harsh weather conditions and disturbances. In this research we propose a solution based on a vector field This vector field is computed based on the leader attitude and the followers positions. From the vector field, the follower can calculate the heading and the speed that it has to keep in order to reach the formation. To reach this solution, we first defined a desired heading and ground speed, then, by defining the goals of the UAV and the dynamic of the UAV we found the commanded heading and the commanded ground speed for each follower. The stability of the result is checked by dividing the convergence problem into two smaller problems and applying the Lyapunov stability theory. The solution is fully implemented using state of the art technology in embedded and autopilots for UAV. The system was physically simulated with ROS in Gazebo. At the end, the performances are compared to another state of the art solution, in which VFF outperformed in most of the cases, Electrical Engineer | Embedded Systems

A redundant fast prototyping autopilot solution for unmanned aerial systems has been developed and successfully tested outdoors. While its low-level backbone is executed in a Raspberry Pi R 3 + NAVIO2 R with a backup autopilot, the computational power of an Intel R NUC mini-computer is employed to implement complex functionalities directly in Simulink R , thus including in-flight debugging, tuning and monitoring. Altogether, the presented tool provides a flexible and user-friendly high-level environment with enhanced computational capabilities, which drastically reduces the prototyping timespans of complex algorithms –between 50% and 75%, according to our long and proven experience in aerial robotics–, while preventing incidents thanks to its redundant design with a human-in-the-loop pilot on the reliable PX4. Three typical outdoor cases are carried out for validation in real-life scenarios, all mounted in a DJI c F550 platform. Full integration results and telemetry for more than 50 hours of outdoor flight tests are provided.

A redundant fast prototyping autopilot solution for unmanned aerial systems has been developed and successfully tested outdoors. While its low-level backbone is executed in a Raspberry Pi R 3 + NAVIO2 R with a backup autopilot, the computational power of an Intel R NUC mini-computer is employed to implement complex functionalities directly in Simulink R , thus including in-flight debugging, tuning and monitoring. Altogether, the presented tool provides a flexible and user-friendly high-level environment with enhanced computational capabilities, which drastically reduces the prototyping timespans of complex algorithms –between 50% and 75%, according to our long and proven experience in aerial robotics–, while preventing incidents thanks to its redundant design with a human-in-the-loop pilot on the reliable PX4. Three typical outdoor cases are carried out for validation in real-life scenarios, all mounted in a DJI c F550 platform. Full integration results and telemetry for more than 50 hours of outdoor flight tests are provided.

A redundant fast prototyping autopilot solution for unmanned aerial systems has been developed and successfully tested outdoors. While its low-level backbone is executed in a Raspberry Pi R 3 + NAVIO2 R with a backup autopilot, the computational power of an Intel R NUC mini-computer is employed to implement complex functionalities directly in Simulink R , thus including in-flight debugging, tuning and monitoring. Altogether, the presented tool provides a flexible and user-friendly high-level environment with enhanced computational capabilities, which drastically reduces the prototyping timespans of complex algorithms –between 50% and 75%, according to our long and proven experience in aerial robotics–, while preventing incidents thanks to its redundant design with a human-in-the-loop pilot on the reliable PX4. Three typical outdoor cases are carried out for validation in real-life scenarios, all mounted in a DJI c F550 platform. Full integration results and telemetry for more than 50 hours of outdoor flight tests are provided.

The mission control of a fixed-wings UAV is slightly more complex compared to other models like quad-rotors or unicycles since the dynamic of a fixed-wing aircraft does not allow rapid direction changes or stop-rotate-go type of movements. Those restriction needs to be taken into consideration when building a mission control system, moreover, the problem increases in complexity when the goal is to fly in formation with several UAVs, indeed during its development, we have to handle also the scalability of the communication link and the robustness of the formation during harsh weather conditions and disturbances. In this research we propose a solution based on a vector field This vector field is computed based on the leader attitude and the followers positions. From the vector field, the follower can calculate the heading and the speed that it has to keep in order to reach the formation. To reach this solution, we first defined a desired heading and ground speed, then, by defining the goals of the UAV and the dynamic of the UAV we found the commanded heading and the commanded ground speed for each follower. The stability of the result is checked by dividing the convergence problem into two smaller problems and applying the Lyapunov stability theory. The solution is fully implemented using state of the art technology in embedded and autopilots for UAV. The system was physically simulated with ROS in Gazebo. At the end, the performances are compared to another state of the art solution, in which VFF outperformed in most of the cases, Electrical Engineering | Embedded Systems

This paper contains the guidelines on the development of an Automatic Dependent Surveillance - Broadcast (ADS-B) information receiver for commercial unmanned aerial systems (UAS) autopilots. The obtained system is low cost thanks to the use of a software-defined radio (SDR) device and a single-board computer (SBC). The industry's leading brand for UAS is DJI, which works with closed-source autopilots and will begin to incorporate ADS-B reception into its high-end UAS. For the rest of UAS, the PX4 and ArduPilot autopilots stand out, which are open source and use the MAVLink protocol. Compatible with MAVLink, on the market only the pingRX component of uAvionix can receive ADS-B information, but it is not low cost. Therefore, a market niche is expected, which is what motivates the development of the system. The received ADS-B information is compiled, processed, and sent from the SBC, using a self-developed program. This is the differentiating element of this work, since it manages to integrate the two fields: ADS-B, coming from conventional aviation; and MAVLink, designed for UAS. The reception is achieved using the SDR device with the incorporation of specific theory about ADS B decoding. Contributions from radio amateurs, who often use this type of information for air traffic monitoring applications, are also included. On the other hand, stable communication between the SBC and the autopilot in MAVLink protocol is achieved. For this, libraries in Python previously provided by the MAVLink developer community are implemented. The correct operation of the proposed system is checked by viewing the transmitted air traffic information at an autopilot¿s ground control station (GCS). A translation of the rest of the document can be requested from the author.

This research project contains a comparison between serveral autopilot systems for un-manned vehicles, focusing on the most relevant open hardware and open-source softwareplatforms. The main subjects studied are the controller boards created by Pixhawk andthe software developing organizations Dronecode and Ardupilot. Specifically, the boardsPixhawk 4 and Pixhawk 2.1 Cube are analized, toghether with the firmwares PX4 (byDronecode) and Ardupilot, nowadays some of the most common options among researchunmanned system projects. The main goal is to provide useful information related to all ofthis components and to determine which ones are more convenient based on the kind ofvehicle and its usage.The project is composed by both a theoretical and an experimental part. First of all, anin-depth research is performed related to the chosen controller boards and software plat-forms, concluding which are the benefits and drawbacks of each one. Secondly, multiplefield tests are done with two different unmanned systems, one of them aerial and the otherone ground-based. The tests are basically autonomous missions that have to be followedby those vehicles and they are repeated in the same conditions with each one of the Pix-hawk controller boards loaded with both PX4 and Ardupilot firmwares. Finally, a Matlabanallysis is done with the data extracted in the tests., Los sistemas no tripulados de uso civil han experimentado un gran crecimiento y evoluci ´on tecnol ´ogica en los ´ultimos a˜nos, especialmente desde la popularizaci ´on de los drones. Una de las piezas fundamentales de estos sistemas son los mecanismos de pilotaje autom´ atico, que tienen la capacidad de dirigir el veh´ıculo siguiendo rutas y planes preestablecidos mediante el uso de sensores y elementos de detecci´on del entorno. En general, est ´an compuestos por un computador conocido como placa controladora y por un software con el que gestiona cualquier tipo de tarea para la que est´e programado. En este proyecto se lleva a cabo una comparativa entre autopilotos para veh´ıculos no tripulados, centr ´andose en las plataformas de hardware y software de c´odigo abierto m´as relevantes. Se estudian los est ´andares de placas controladoras creados por la organizaci ´on Pixhawk, as´ı como los dos desarrolladores de software libre Dronecode y Ardupilot. En concreto se eval ´uan las diferencias entre las placas Pixhawk 4 y Pixhawk 2.1 Cube, adem´as de los dos firmwares PX4 (de Dronecode) y Ardupilot, que son algunas de las opciones m´as comunes en sistemas no tripulados dentro del ´ambito de la investigaci ´on. El objetivo principal es proporcionar informaci´on ´ util sobre todos estos elementos y determinar cuales conviene m´as usar dependiendo del tipo de veh´ıculo y de las aplicaciones que se les quiera dar. El estudio consta de una parte te ´ orica y otra pr ´ actica. En primer lugar se investigan en profundidad las placas controladoras y las plataformas de software mencionadas, concluyendo cuales son las ventajas y desventajas que tienen entre si. Por otro lado, la parte experimental consiste en pruebas realizadas con diferentes tipos de sistemas no tripulados, uno a´ereo y otro terrestre. Dichas pruebas son recorridos que cada veh´ıculo tiene que seguir autom´aticamente y que se repiten con las dos placas de Pixhawk junto a los firmwares de PX4 y Ardupilot en igu

Formation flying is a phenomenon observed very often in the natural world, e.g. birds flying in a flock. The past decade has given a lot of emphasis on the research for the control of autonomous Unmanned Aerial Vehicles (UAVs) of the fixed-wing kind, in an effort to emulate the behavior of natural flocks. Emulating this behavior requires the construction of path following and formation control laws with the capability of adapting to changing situations, in a similar way as natural flocks can do. This thesis is devoted to studying Adaptive Vector Field Guidance laws and Adaptive Formation laws for fixed-wing UAVs. Formation control relies on an adaptive hierarchical formation control method for uncertain heterogeneous nonlinear agents with Euler-Lagrange (EL) dynamics. It is shown that various formations (T-V-Y formations) can be established using this method, tested using a Matlab/Simulink environment. Additionally, a distinguishing feature of this thesis is the development of a 3D-Simulation platform to perform a hardware in the loop (HITL) simulations (i.e. using the control hardware on board of an actual UAV): a Raspberry Pi is used to run the formation control algorithm and to communicate with a Pixhawk Cube autopilot board which contains the low-level control algorithm. The autopilot board is then connected to a 3D Simulator (Gazebo) and Ground Control System (QGroundControl). The proposed HITL platform promises to facilitate the testing and validation of guidance and formation laws in a much more realistic way than a Matlab/Simulink environment can do.

El mercado de los drones ha evolucionado mucho estos últimos años y cada vez se encuentra más presente en diferentes sectores. Por esto mismo, se tiene que asegurar la fiabilidad y la seguridad de estas aeronaves. El objetivo de este trabajo de final de grado es la creación de un entorno de simulación para multicopteros. La plataforma de simulación se basa en Gazebo junto a ROS como middleware entre el simulador y el dron. Para validar el control de navegación del drone, se utilizará la placa Pixhawk con su software de control de vuelo de código abierto PX4 mediante el uso de la técnica de simulación hardware in the loop., The drone market has evolved a lot in recent years and we are finding it more and more present in different sectors. For this reason, the reliability and safety of these aircraft must be ensured. The purpose of this end-of-grade paper is to create a simulation environment for multicopters. The simulation is based on Gazebo together with ROS as middleware between the simulation and the drone. To validate the drone navigation control, a real board (Pixhack) with its open source flight control software PX4 will be used, creating a hardware-in-the-loop approach.

Formation flying is a phenomenon observed very often in the natural world, e.g. birds flying in a flock. The past decade has given a lot of emphasis on the research for the control of autonomous Unmanned Aerial Vehicles (UAVs) of the fixed-wing kind, in an effort to emulate the behavior of natural flocks. Emulating this behavior requires the construction of path following and formation control laws with the capability of adapting to changing situations, in a similar way as natural flocks can do. This thesis is devoted to studying Adaptive Vector Field Guidance laws and Adaptive Formation laws for fixed-wing UAVs. Formation control relies on an adaptive hierarchical formation control method for uncertain heterogeneous nonlinear agents with Euler-Lagrange (EL) dynamics. It is shown that various formations (T-V-Y formations) can be established using this method, tested using a Matlab/Simulink environment. Additionally, a distinguishing feature of this thesis is the development of a 3D-Simulation platform to perform a hardware in the loop (HITL) simulations (i.e. using the control hardware on board of an actual UAV): a Raspberry Pi is used to run the formation control algorithm and to communicate with a Pixhawk Cube autopilot board which contains the low-level control algorithm. The autopilot board is then connected to a 3D Simulator (Gazebo) and Ground Control System (QGroundControl). The proposed HITL platform promises to facilitate the testing and validation of guidance and formation laws in a much more realistic way than a Matlab/Simulink environment can do.

Cílem diplomové práce je upravit komerčně vyráběný dron DJI Matrice 100 a nahradit jeho řídicí jednotku jednotkou Pixhawk a jeho příslušenstvím, které jsou vyvíjeny pod svobodnou licencí. Následně se zabývá výběrem vhodného firmwaru pro Pixhawk, taktéž vyvíjeného pod svobodnou licencí a jeho konfigurací na daném zařízení. Další část práce se věnuje možnostem použití Robotického operačního systému, zkráceně ROS, resp. jeho knihoven MAVROS na palubním počítači Raspberry Pi. S využitím MAVROS zkoumá možnosti programového řízení letu dronu a to jak v prostředí simulace, tak i v prostředí reálném., The aim of this thesis is to modify commercially produced drone DJI Matrice 100 and replace its original control unit by open source Pixhawk and its accessories. Subsequently, it deals with the selection of suitable open source firmware for Pixhawk and its configuration on the device. Another part is dedicated to the possibilities of using the Robotic Operating System (ROS) and its Mavros libraries on the onboard computer Raspberry Pi. By using Mavros, it examines the possibilities of drone flight control, both in the simulation environment and in the real environment.

Tato bakalářská práce se zaměřuje na problematiku navigace dronu v neznámém 3D prostředí s využitím stereokamery a algoritmů pro sledování trasy a vyhýbání se překážkám. Práce kombinuje framework ROS2 (Robot Operating System), autopilot PX4 a simulátor Gazebo k vytvoření prostředí pro vývoj a testování těchto algoritmů., This bachelor thesis focuses on the issue of drone navigation in an unknown 3D space with the use of stereocamera and algorithms for tracking and obstacle avoidance. It combines ROS2 (Robot Operating System) framework, PX4 autopilot and Gazebo simulator to create an enviroment suitable for development and testing of said algorithms.

Tato práce se zabývá metodami pro řešení problematiky navigace a pohybu autonomních prostředků mezi překážkami. Práce nejprve obecně popisuje algoritmy pro plánování pohybu a vyhýbání se překážkám. Dále se práce zabývá firmwarem PX4 pro řízení UAV. V rámci práce byl navrhnut vlastní algoritmus pro vyhýbání se překážkám určený pro UAV. Použitým senzorem pro detekci překážek je stereokamera. Tento algoritmus byl implementován v jazyce Python s použitím frameworku ROS a otestován v simulačním prostředí Gazebo. Výsledky jsou diskutovány., This thesis deals with methods for the problem of navigation and movement of autonomous vehicles between obstacles. The thesis first describes in general terms algorithms for motion planning and obstacle avoidance. Then, the thesis discusses the PX4 firmware for UAV control. The thesis proposes a custom obstacle avoidance algorithm designed for UAVs. The sensor used for obstacle detection is a stereo camera. This algorithm was implemented in Python using the ROS framework and tested in the Gazebo simulation environment. The results are discussed.

Tato bakalářská práce se zabývá plánováním pohybu dronu v neznámém prostředí. Aby mohl dron vnímat své okolí musí být vybaven potřebným senzorickým vybavením. V práci je diskutováno možné senzorické vybavení vhodné pro koordinaci letu a řešení kolizí. Také jsou zde popsány a využity softwary pro zpracování dat ze senzorů a plánování pohybu dronu. Pro experiment v této práci byl využit LiDAR a stereokamera. Data z obou senzorů jsou zde prostřednictvím softwaru ROS spojena do jednoho celku a zobrazována v simulačním prostředí RViz. Tato data jsou vhodná pro následné využití při plánování pohybu dronu a řešení kolizí., This bachelor thesis deals with drone flight planning in an unknown environment. In order for a drone to be able to perceive its environment, it must be equipped with the necessary sensory equipment. This thesis discusses possible sensor equipment suitable for flight coordination and collision avoidance. Also, software for sensor data processing and drone motion planning are described and used here. LiDAR and depth camera were used for the experiment in this thesis. In the experiment the data from both sensors are fused together through ROS software and displayed in RViz simulation environment. This data are suitable for subsequent use in drone motion planning and collision avoidance.

Cílem diplomové práce je upravit komerčně vyráběný dron DJI Matrice 100 a nahradit jeho řídicí jednotku jednotkou Pixhawk a jeho příslušenstvím, které jsou vyvíjeny pod svobodnou licencí. Následně se zabývá výběrem vhodného firmwaru pro Pixhawk, taktéž vyvíjeného pod svobodnou licencí a jeho konfigurací na daném zařízení. Další část práce se věnuje možnostem použití Robotického operačního systému, zkráceně ROS, resp. jeho knihoven MAVROS na palubním počítači Raspberry Pi. S využitím MAVROS zkoumá možnosti programového řízení letu dronu a to jak v prostředí simulace, tak i v prostředí reálném., The aim of this thesis is to modify commercially produced drone DJI Matrice 100 and replace its original control unit by open source Pixhawk and its accessories. Subsequently, it deals with the selection of suitable open source firmware for Pixhawk and its configuration on the device. Another part is dedicated to the possibilities of using the Robotic Operating System (ROS) and its Mavros libraries on the onboard computer Raspberry Pi. By using Mavros, it examines the possibilities of drone flight control, both in the simulation environment and in the real environment.

Diplomová práce se zabývá problematikou simulace misí bezpilotních letadel ve virtuálním prostředí. Cílem práce je demonstrovat základní i pokročilejší autonomní letecké mise v simulovaném prostředí Gazebo - ROS 2. Důraz práce je kladen na stabilitu softwarového řešení a stabilitu komunikace mezi kritickými komponenty letecké mise., The master thesis deals with the issue of simulation of unmanned aircraft missions in a virtual environment. The aim of the work is to demonstrate basic and more advanced autonomous aerial missions in the simulated environment Gazebo - ROS 2. The work emphasizes the stability of the software solution and the stability of the communication between critical components of the aerial mission.

Tato práce se zabývá metodami pro řešení problematiky navigace a pohybu autonomních prostředků mezi překážkami. Práce nejprve obecně popisuje algoritmy pro plánování pohybu a vyhýbání se překážkám. Dále se práce zabývá firmwarem PX4 pro řízení UAV. V rámci práce byl navrhnut vlastní algoritmus pro vyhýbání se překážkám určený pro UAV. Použitým senzorem pro detekci překážek je stereokamera. Tento algoritmus byl implementován v jazyce Python s použitím frameworku ROS a otestován v simulačním prostředí Gazebo. Výsledky jsou diskutovány., This thesis deals with methods for the problem of navigation and movement of autonomous vehicles between obstacles. The thesis first describes in general terms algorithms for motion planning and obstacle avoidance. Then, the thesis discusses the PX4 firmware for UAV control. The thesis proposes a custom obstacle avoidance algorithm designed for UAVs. The sensor used for obstacle detection is a stereo camera. This algorithm was implemented in Python using the ROS framework and tested in the Gazebo simulation environment. The results are discussed.

Tato práce se zabývá metodami pro řešení problematiky navigace a pohybu autonomních prostředků mezi překážkami. Práce nejprve obecně popisuje algoritmy pro plánování pohybu a vyhýbání se překážkám. Dále se práce zabývá firmwarem PX4 pro řízení UAV. V rámci práce byl navrhnut vlastní algoritmus pro vyhýbání se překážkám určený pro UAV. Použitým senzorem pro detekci překážek je stereokamera. Tento algoritmus byl implementován v jazyce Python s použitím frameworku ROS a otestován v simulačním prostředí Gazebo. Výsledky jsou diskutovány., This thesis deals with methods for the problem of navigation and movement of autonomous vehicles between obstacles. The thesis first describes in general terms algorithms for motion planning and obstacle avoidance. Then, the thesis discusses the PX4 firmware for UAV control. The thesis proposes a custom obstacle avoidance algorithm designed for UAVs. The sensor used for obstacle detection is a stereo camera. This algorithm was implemented in Python using the ROS framework and tested in the Gazebo simulation environment. The results are discussed.

Tato práce se zabývá vytvořením platformy pro testování stabilizačních a řídicích algoritmů pro UAV. Byl vybrán vhodný model letadla, do kterého byla navržena struktura řídicí a výkonové elektroniky. Byla provedena rešerše vhodných algoritmů a vybrané algoritmy byly implementovány. Pro implementované algoritmy byly pomocí simulace navrženy parametry regulátorů. Následně byl celý systém testován v letu., Main topic of this thesis is creation of platform for testing stabilization and control algorithms for UAV. For chosen suitable model plane was designed a structure of control and power electronics. Research of suitable algorithms was made and some of them were implemented. For this algorithms gains were designed, using simulation. The whole system was tested and validated in flight.

PX4 platforma je jedna z nepoužívanějších softwarových balíčků pro řízení bezpilotníhosystému. Používá MAVLink protokol pro komunikaci mezi autopilotem, pozemní stanicía dalšími zařízeními v MAVLink síti. Je speciálně navržen pro bezpilotní systémy použí-vající rádia s nízkou datovou propustností. S rostoucím počtem těchto zařízení docházírovněž k růstu počtu útoků na tyto systémy. Tato diplomová práce obsahuje analízua popis bezpečnostních nedostatků v telemetrické komunikaci platformy PX4 běžící naprotokolu MAVLink. Na základě těchto nedostatků byla dále navržená a implementovánabezpečnostní řešení. Tato implementace zahrnuje šifrování, řízení přístupu, autentizacia systém pro výměnu klíčů. Bezpečnostní implementace je postavená na knihovně Mo-noCypher. Všechny části práce jsou naprogramováno v jazyce C. Cílem autora je sdíletvýsledky, kterých dosáhl s komunitou kolem paltformy PX4. Proto během finální částipráce vznikl pull request do veřejného repozitáře., PX4 platform is one of the most common software packages used to control unmanned systems. It uses the MAVLink protocol for communication between the autopilot, ground control station or other devices in the MAVLink network. This protocol is specially designed to suit unmanned systems using radio with low passthrough. With the rising number of unmanned systems, the number of cyber attacks on these devices is also increasing. This diploma thesis presents an analysis of the MAVLink protocol and PX4 platform, and describes possible security vulnerabilities in telemetry connection. Based on these findings, a security implementation was created. This implementation contains encryption, access control, authentication and a key exchange system. Security implementation is based on the MonoCypher cryptography library. The whole implementation was programmed in C language. Author's goal was to share results with the community around PX4 platform. Therefore, pull requests have been created to the public repository during the final part of thesis.

Tato práce se zabývá vytvořením platformy pro testování stabilizačních a řídicích algoritmů pro UAV. Byl vybrán vhodný model letadla, do kterého byla navržena struktura řídicí a výkonové elektroniky. Byla provedena rešerše vhodných algoritmů a vybrané algoritmy byly implementovány. Pro implementované algoritmy byly pomocí simulace navrženy parametry regulátorů. Následně byl celý systém testován v letu., Main topic of this thesis is creation of platform for testing stabilization and control algorithms for UAV. For chosen suitable model plane was designed a structure of control and power electronics. Research of suitable algorithms was made and some of them were implemented. For this algorithms gains were designed, using simulation. The whole system was tested and validated in flight.

PX4 platforma je jedna z nepoužívanějších softwarových balíčků pro řízení bezpilotníhosystému. Používá MAVLink protokol pro komunikaci mezi autopilotem, pozemní stanicía dalšími zařízeními v MAVLink síti. Je speciálně navržen pro bezpilotní systémy použí-vající rádia s nízkou datovou propustností. S rostoucím počtem těchto zařízení docházírovněž k růstu počtu útoků na tyto systémy. Tato diplomová práce obsahuje analízua popis bezpečnostních nedostatků v telemetrické komunikaci platformy PX4 běžící naprotokolu MAVLink. Na základě těchto nedostatků byla dále navržená a implementovánabezpečnostní řešení. Tato implementace zahrnuje šifrování, řízení přístupu, autentizacia systém pro výměnu klíčů. Bezpečnostní implementace je postavená na knihovně Mo-noCypher. Všechny části práce jsou naprogramováno v jazyce C. Cílem autora je sdíletvýsledky, kterých dosáhl s komunitou kolem paltformy PX4. Proto během finální částipráce vznikl pull request do veřejného repozitáře., PX4 platform is one of the most common software packages used to control unmanned systems. It uses the MAVLink protocol for communication between the autopilot, ground control station or other devices in the MAVLink network. This protocol is specially designed to suit unmanned systems using radio with low passthrough. With the rising number of unmanned systems, the number of cyber attacks on these devices is also increasing. This diploma thesis presents an analysis of the MAVLink protocol and PX4 platform, and describes possible security vulnerabilities in telemetry connection. Based on these findings, a security implementation was created. This implementation contains encryption, access control, authentication and a key exchange system. Security implementation is based on the MonoCypher cryptography library. The whole implementation was programmed in C language. Author's goal was to share results with the community around PX4 platform. Therefore, pull requests have been created to the public repository during the final part of thesis.

Tato bakalářská práce se zaměřuje na problematiku navigace dronu v neznámém 3D prostředí s využitím stereokamery a algoritmů pro sledování trasy a vyhýbání se překážkám. Práce kombinuje framework ROS2 (Robot Operating System), autopilot PX4 a simulátor Gazebo k vytvoření prostředí pro vývoj a testování těchto algoritmů., This bachelor thesis focuses on the issue of drone navigation in an unknown 3D space with the use of stereocamera and algorithms for tracking and obstacle avoidance. It combines ROS2 (Robot Operating System) framework, PX4 autopilot and Gazebo simulator to create an enviroment suitable for development and testing of said algorithms.

Tato práce se zabývá metodami pro řešení problematiky navigace a pohybu autonomních prostředků mezi překážkami. Práce nejprve obecně popisuje algoritmy pro plánování pohybu a vyhýbání se překážkám. Dále se práce zabývá firmwarem PX4 pro řízení UAV. V rámci práce byl navrhnut vlastní algoritmus pro vyhýbání se překážkám určený pro UAV. Použitým senzorem pro detekci překážek je stereokamera. Tento algoritmus byl implementován v jazyce Python s použitím frameworku ROS a otestován v simulačním prostředí Gazebo. Výsledky jsou diskutovány., This thesis deals with methods for the problem of navigation and movement of autonomous vehicles between obstacles. The thesis first describes in general terms algorithms for motion planning and obstacle avoidance. Then, the thesis discusses the PX4 firmware for UAV control. The thesis proposes a custom obstacle avoidance algorithm designed for UAVs. The sensor used for obstacle detection is a stereo camera. This algorithm was implemented in Python using the ROS framework and tested in the Gazebo simulation environment. The results are discussed.

Tato práce se zabývá metodami pro řešení problematiky navigace a pohybu autonomních prostředků mezi překážkami. Práce nejprve obecně popisuje algoritmy pro plánování pohybu a vyhýbání se překážkám. Dále se práce zabývá firmwarem PX4 pro řízení UAV. V rámci práce byl navrhnut vlastní algoritmus pro vyhýbání se překážkám určený pro UAV. Použitým senzorem pro detekci překážek je stereokamera. Tento algoritmus byl implementován v jazyce Python s použitím frameworku ROS a otestován v simulačním prostředí Gazebo. Výsledky jsou diskutovány., This thesis deals with methods for the problem of navigation and movement of autonomous vehicles between obstacles. The thesis first describes in general terms algorithms for motion planning and obstacle avoidance. Then, the thesis discusses the PX4 firmware for UAV control. The thesis proposes a custom obstacle avoidance algorithm designed for UAVs. The sensor used for obstacle detection is a stereo camera. This algorithm was implemented in Python using the ROS framework and tested in the Gazebo simulation environment. The results are discussed.

Tato bakalářská práce se zabývá plánováním pohybu dronu v neznámém prostředí. Aby mohl dron vnímat své okolí musí být vybaven potřebným senzorickým vybavením. V práci je diskutováno možné senzorické vybavení vhodné pro koordinaci letu a řešení kolizí. Také jsou zde popsány a využity softwary pro zpracování dat ze senzorů a plánování pohybu dronu. Pro experiment v této práci byl využit LiDAR a stereokamera. Data z obou senzorů jsou zde prostřednictvím softwaru ROS spojena do jednoho celku a zobrazována v simulačním prostředí RViz. Tato data jsou vhodná pro následné využití při plánování pohybu dronu a řešení kolizí., This bachelor thesis deals with drone flight planning in an unknown environment. In order for a drone to be able to perceive its environment, it must be equipped with the necessary sensory equipment. This thesis discusses possible sensor equipment suitable for flight coordination and collision avoidance. Also, software for sensor data processing and drone motion planning are described and used here. LiDAR and depth camera were used for the experiment in this thesis. In the experiment the data from both sensors are fused together through ROS software and displayed in RViz simulation environment. This data are suitable for subsequent use in drone motion planning and collision avoidance.

Tato práce se zabývá metodami pro řešení problematiky navigace a pohybu autonomních prostředků mezi překážkami. Práce nejprve obecně popisuje algoritmy pro plánování pohybu a vyhýbání se překážkám. Dále se práce zabývá firmwarem PX4 pro řízení UAV. V rámci práce byl navrhnut vlastní algoritmus pro vyhýbání se překážkám určený pro UAV. Použitým senzorem pro detekci překážek je stereokamera. Tento algoritmus byl implementován v jazyce Python s použitím frameworku ROS a otestován v simulačním prostředí Gazebo. Výsledky jsou diskutovány., This thesis deals with methods for the problem of navigation and movement of autonomous vehicles between obstacles. The thesis first describes in general terms algorithms for motion planning and obstacle avoidance. Then, the thesis discusses the PX4 firmware for UAV control. The thesis proposes a custom obstacle avoidance algorithm designed for UAVs. The sensor used for obstacle detection is a stereo camera. This algorithm was implemented in Python using the ROS framework and tested in the Gazebo simulation environment. The results are discussed.

Tato bakalářská práce se zabývá plánováním pohybu dronu v neznámém prostředí. Aby mohl dron vnímat své okolí musí být vybaven potřebným senzorickým vybavením. V práci je diskutováno možné senzorické vybavení vhodné pro koordinaci letu a řešení kolizí. Také jsou zde popsány a využity softwary pro zpracování dat ze senzorů a plánování pohybu dronu. Pro experiment v této práci byl využit LiDAR a stereokamera. Data z obou senzorů jsou zde prostřednictvím softwaru ROS spojena do jednoho celku a zobrazována v simulačním prostředí RViz. Tato data jsou vhodná pro následné využití při plánování pohybu dronu a řešení kolizí., This bachelor thesis deals with drone flight planning in an unknown environment. In order for a drone to be able to perceive its environment, it must be equipped with the necessary sensory equipment. This thesis discusses possible sensor equipment suitable for flight coordination and collision avoidance. Also, software for sensor data processing and drone motion planning are described and used here. LiDAR and depth camera were used for the experiment in this thesis. In the experiment the data from both sensors are fused together through ROS software and displayed in RViz simulation environment. This data are suitable for subsequent use in drone motion planning and collision avoidance.

Diplomová práce se zabývá problematikou simulace misí bezpilotních letadel ve virtuálním prostředí. Cílem práce je demonstrovat základní i pokročilejší autonomní letecké mise v simulovaném prostředí Gazebo - ROS 2. Důraz práce je kladen na stabilitu softwarového řešení a stabilitu komunikace mezi kritickými komponenty letecké mise., The master thesis deals with the issue of simulation of unmanned aircraft missions in a virtual environment. The aim of the work is to demonstrate basic and more advanced autonomous aerial missions in the simulated environment Gazebo - ROS 2. The work emphasizes the stability of the software solution and the stability of the communication between critical components of the aerial mission.

Tato práce se zabývá vytvořením platformy pro testování stabilizačních a řídicích algoritmů pro UAV. Byl vybrán vhodný model letadla, do kterého byla navržena struktura řídicí a výkonové elektroniky. Byla provedena rešerše vhodných algoritmů a vybrané algoritmy byly implementovány. Pro implementované algoritmy byly pomocí simulace navrženy parametry regulátorů. Následně byl celý systém testován v letu., Main topic of this thesis is creation of platform for testing stabilization and control algorithms for UAV. For chosen suitable model plane was designed a structure of control and power electronics. Research of suitable algorithms was made and some of them were implemented. For this algorithms gains were designed, using simulation. The whole system was tested and validated in flight.

PX4 platforma je jedna z nepoužívanějších softwarových balíčků pro řízení bezpilotníhosystému. Používá MAVLink protokol pro komunikaci mezi autopilotem, pozemní stanicía dalšími zařízeními v MAVLink síti. Je speciálně navržen pro bezpilotní systémy použí-vající rádia s nízkou datovou propustností. S rostoucím počtem těchto zařízení docházírovněž k růstu počtu útoků na tyto systémy. Tato diplomová práce obsahuje analízua popis bezpečnostních nedostatků v telemetrické komunikaci platformy PX4 běžící naprotokolu MAVLink. Na základě těchto nedostatků byla dále navržená a implementovánabezpečnostní řešení. Tato implementace zahrnuje šifrování, řízení přístupu, autentizacia systém pro výměnu klíčů. Bezpečnostní implementace je postavená na knihovně Mo-noCypher. Všechny části práce jsou naprogramováno v jazyce C. Cílem autora je sdíletvýsledky, kterých dosáhl s komunitou kolem paltformy PX4. Proto během finální částipráce vznikl pull request do veřejného repozitáře., PX4 platform is one of the most common software packages used to control unmanned systems. It uses the MAVLink protocol for communication between the autopilot, ground control station or other devices in the MAVLink network. This protocol is specially designed to suit unmanned systems using radio with low passthrough. With the rising number of unmanned systems, the number of cyber attacks on these devices is also increasing. This diploma thesis presents an analysis of the MAVLink protocol and PX4 platform, and describes possible security vulnerabilities in telemetry connection. Based on these findings, a security implementation was created. This implementation contains encryption, access control, authentication and a key exchange system. Security implementation is based on the MonoCypher cryptography library. The whole implementation was programmed in C language. Author's goal was to share results with the community around PX4 platform. Therefore, pull requests have been created to the public repository during the final part of thesis.

Cílem diplomové práce je upravit komerčně vyráběný dron DJI Matrice 100 a nahradit jeho řídicí jednotku jednotkou Pixhawk a jeho příslušenstvím, které jsou vyvíjeny pod svobodnou licencí. Následně se zabývá výběrem vhodného firmwaru pro Pixhawk, taktéž vyvíjeného pod svobodnou licencí a jeho konfigurací na daném zařízení. Další část práce se věnuje možnostem použití Robotického operačního systému, zkráceně ROS, resp. jeho knihoven MAVROS na palubním počítači Raspberry Pi. S využitím MAVROS zkoumá možnosti programového řízení letu dronu a to jak v prostředí simulace, tak i v prostředí reálném., The aim of this thesis is to modify commercially produced drone DJI Matrice 100 and replace its original control unit by open source Pixhawk and its accessories. Subsequently, it deals with the selection of suitable open source firmware for Pixhawk and its configuration on the device. Another part is dedicated to the possibilities of using the Robotic Operating System (ROS) and its Mavros libraries on the onboard computer Raspberry Pi. By using Mavros, it examines the possibilities of drone flight control, both in the simulation environment and in the real environment.

Tato bakalářská práce se zabývá plánováním pohybu dronu v neznámém prostředí. Aby mohl dron vnímat své okolí musí být vybaven potřebným senzorickým vybavením. V práci je diskutováno možné senzorické vybavení vhodné pro koordinaci letu a řešení kolizí. Také jsou zde popsány a využity softwary pro zpracování dat ze senzorů a plánování pohybu dronu. Pro experiment v této práci byl využit LiDAR a stereokamera. Data z obou senzorů jsou zde prostřednictvím softwaru ROS spojena do jednoho celku a zobrazována v simulačním prostředí RViz. Tato data jsou vhodná pro následné využití při plánování pohybu dronu a řešení kolizí., This bachelor thesis deals with drone flight planning in an unknown environment. In order for a drone to be able to perceive its environment, it must be equipped with the necessary sensory equipment. This thesis discusses possible sensor equipment suitable for flight coordination and collision avoidance. Also, software for sensor data processing and drone motion planning are described and used here. LiDAR and depth camera were used for the experiment in this thesis. In the experiment the data from both sensors are fused together through ROS software and displayed in RViz simulation environment. This data are suitable for subsequent use in drone motion planning and collision avoidance.

Diplomová práce se zabývá problematikou simulace misí bezpilotních letadel ve virtuálním prostředí. Cílem práce je demonstrovat základní i pokročilejší autonomní letecké mise v simulovaném prostředí Gazebo - ROS 2. Důraz práce je kladen na stabilitu softwarového řešení a stabilitu komunikace mezi kritickými komponenty letecké mise., The master thesis deals with the issue of simulation of unmanned aircraft missions in a virtual environment. The aim of the work is to demonstrate basic and more advanced autonomous aerial missions in the simulated environment Gazebo - ROS 2. The work emphasizes the stability of the software solution and the stability of the communication between critical components of the aerial mission.

Diplomová práce se zabývá problematikou simulace misí bezpilotních letadel ve virtuálním prostředí. Cílem práce je demonstrovat základní i pokročilejší autonomní letecké mise v simulovaném prostředí Gazebo - ROS 2. Důraz práce je kladen na stabilitu softwarového řešení a stabilitu komunikace mezi kritickými komponenty letecké mise., The master thesis deals with the issue of simulation of unmanned aircraft missions in a virtual environment. The aim of the work is to demonstrate basic and more advanced autonomous aerial missions in the simulated environment Gazebo - ROS 2. The work emphasizes the stability of the software solution and the stability of the communication between critical components of the aerial mission.