<p>Solar-powered Unmanned Aerial Vehicles (UAVs) solve the problem of loiter time as aircrafts can fly as long as sufficient illumination and reserve battery power is available. However, Solar-powered UAVs still face the problem of excessive wingspan to increase solar capture area, which detracts from maneuverability and portability. As a result, a feature of merit for solar UAVs has emerged that strives to reduce the wingspan of such UAVs. The purpose of this project is to improve energy use efficiency by applying a distributed propulsion system to reduce the wingspan of solar-powered UAVs and increase payload. The research focuses on optimizing a new design analysis method applied to the distributed propulsion system and further employs the novel application of solar arrays on both top and bottom of the wings. The design methodology will result in a 2.1-meter wingspan, which is the shortest at 2020, for a 24-hour duration solar-powered UAV.</p><br>

Veículos Aéreos não tripulados (VANTs) vêm sendo cada vez mais utilizados em diversos países, tanto na área militar como na civil. O cenário considerado nesse estudo é o de um VANT realizando captura de vídeo em tempo real, transmitindo-o a uma base terrestre por meio de rede sem fio. O problema consiste no fato de não ser possível garantir uma taxa de transmissão contínua, com banda estável. Isso ocorre devido a fatores como a velocidade da aeronave (da ordem centenas de km/h), irregularidades de terreno (impedindo a linha de visada do enlace de transmissão), ou do clima, como tempestades que podem interferir na transmissão da RF. Por fim, os movimentos que o VANT pode realizar no vôo (Rolagem, Arfagem ou Guinada) podem prejudicar a disponibilidade do link. Dessa forma, é necessário que seja realizada adaptação de vídeo de acordo com a banda disponível. Assim, quando a qualidade do enlace for degradada, deverá ser realizada uma redução no tamanho do vídeo, evitando a interrupção na transmissão. Por outro lado, a adaptação também deverá fazer com que a banda disponível seja utilizada, evitando o envio de vídeos com qualidade inferior à que seria possível para determinado valor de largura de banda. Nesse trabalho será considerada a faixa de valores de largura de banda de 8 Mbps até zero. Para realizar a adaptação será utilizado o padrão H.264/AVC com codificação escalável / Unmanned Aerial Vehicles (UAVs) are being increasingly used in several countries, both in the military and civilian areas. In this study we consider an UAV equipped with a camera, capturing video for a real-time transmission to a ground-base using wireless network. The problem is that its not possible to ensure a continuous transmission rate, with stable bandwidth. That occurs due to factors like the speed of the aircraft, irregularities of terrain, or the weather (as storms, heat and fog, for instance, can interfere with RF transmission). Finally, the movements that the UAV can perform in flight (Roll, pitch and yaw) can impair link availability. Thus, it is necessary to perform an adaptation of video according to the available bandwidth. When the link quality is degraded, a reduction in the resolution of the video must be performed , avoiding interruption of the transmission. Additionally, adaptation must also provide that all the available bandwidth is used, avoiding sending the video with lower quality that would be possible for a given value bandwidth. In this work we propose a system which can vary the total amount of data being transmitted, by adjusting the compression parameters of the video. We manage to produce a system which uses the range from 8 Mbps up to zero. We use the H.264/AVC Codec, with scalable video coding

Cette thèse s'intéresse à la réalisation autonome de plans de vol cinématographiques par un quadrotor équipé d'une caméra. Ces plans de vol consistent en une série de points de passage à rejoindre successivement, en adoptant diverses méthodes de prise de vue et en respectant des références de vitesses ainsi que des couloirs de vols. Une étude approfondie de la dynamique du quadrotor est tout d'abord proposée et utilisée pour construire un modèle linéarisé du drone autour de l'équilibre de vol stationnaire. L'analyse de ce modèle linéaire permet de mettre en évidence l'impact de l'inertie des rotors du drone dans sa dynamique, notamment l'apparition d'un comportement à non minimum de phase en roulis ou tangage, lorsque les moteurs sont inclinés. Dans un second temps, deux algorithmes de génération de trajectoires lisses, faisables et adaptées à la cinématographie sont proposés. La faisabilité de la trajectoire est garantie par le respect de contraintes sur ses dérivées temporelle, adaptées pour la cinématographie et obtenue grâce à l'étude du modèle non linéaire du drone. Le premier repose sur une optimisation bi-niveaux d'une trajectoire polynomiale par morceaux, dans le but de trouver la plus rapide des trajectoires à minimum de jerk permettant d'accomplir la mission. Le second algorithme consiste en la génération de trajectoires B-spline non-uniformes à durée minimale. Pour les deux solutions, une étude de l’initialisation du problème d'optimisation est présentée, de même qu'une analyse de leurs avantages et limitations. Pour ce faire, elles sont notamment confrontées à des simulations et vols extérieurs. Enfin, une loi de commande prédictive est proposée pour asservir les mouvements de la caméra embarquée de manière douce et précise. / This thesis focuses on the autonomous performance of cinematographic flight plans by camera equipped quadrotors. These flight plans consist in a series of waypoints to join while adopting various camera behaviors, along with speed references and flight corridors. First, an in depth study of the nonlinear dynamics of the drone is proposed, which is then used to derive a linear model of the system around the hovering equilibrium. An analysis of this linear model allows us to emphasize the impact of the inertia of the propellers when the latter are tilted, such as the apparition of a nonminimum phase behavior of the pitch or roll dynamics. Then, two algorithms are proposed to generate smooth and feasible cinematographic trajectories. The feasibility of the trajectory is ensured by constraints on its time derivatives, suited for cinematography and obtained with the use of the nonlinear model of the drone. The first algorithm proposed in this work is based on a bi-level optimization of a piecewise polynomial trajectory, in order to find the fastest feasible minimum jerk trajectory to perform the flight plan. The second algorithm consists in the generation of feasible, minimum time, non-uniform B-spline trajectories. For both solutions, a study of the initilization of the optimization problem is proposed, as well as a discussion about their advantages and limitations. To this aim, they are notably confronted to simulations and outdoor flight experiments. Finally, a predictive control law is proposed to smoothly and accurately control the onboard camera.

In recent years, advances in small unmanned aerial vehicle (UAV) technology have transformed the use cases of these aircraft from hobby flying to industrial and business applications. These maneuverable, easily deployed tools can be retrofitted with a myriad of sensors and equipment, which make them suitable to perform a variety of specialized tasks. With increasing UAV capabilities, the function of small UAVs can be extended from pure monitoring or surveillance to the dual objective of monitoring an environment for events and addressing the events in some way. This thesis seeks to explore a subdomain of the dual objective problem described, referred to in this thesis as the multi-UAV persistent search and retrieval task with stochastic target appearance (PSR-STA), in which UAVs continuously search an area over a long period of time for targets of interest, which appear according to a probabilistic model, to retrieve and deliver them to a collector location. The advent of high-speed computers and agent-based modeling theory enable the simulation of multi-UAV PSR-STA. However, it can be complicated to combine parts of multi-UAV PSR-STA such as motion models and multi-UAV coordination into one integrated system, and even after they are combined successfully, it is difficult to analyze the system except with simple comparison tools. This thesis 1) proposes a framework that builds a foundation for understanding how to simulate and analyze multi-UAV PSR-STA through prescribing important design decisions and methods for simulation and 2) identifies metrics, analysis tools, and trends related to overall system effectiveness for multi-UAV PSR-STA. A case study of multi-UAV park cleanup is implemented where many simulations with input parameters chosen by a latin hypercube design of experiments are examined, algorithms for choosing the locations of collectors and charging stations based on probabilistic information are proposed, and the differences in effectiveness between four coverage search patterns are analyzed. Measures are highlighted that provide insight into performance variability over time and space. Line charts and the discrete Fourier transform are used to understand temporal patterns inherent in the data. Principal component analysis is used to analyze relevant spatial patterns in effectiveness, and a random forest surrogate model with a profiler is used to explore the non-linear influence of input parameters on the spatial patterns. The trellis chart or figure of figures method is presented for visualizing spatial and temporal data across many simulations. A second set of experiments based on the park cleanup case study are performed and examined to verify the benefits of these methods.

The thesis introduces an innovative UAV detection system. The commercial UAV market is booming. Meanwhile, the risks and threats from improper UAV usages are also booming. CUAS is to protect the public and facilities. The problem is a lack of an intelligent platform which can adapt many sensors for UAV detection. The hypothesis is that, the system can track the UAV’s movement by applying the multi-agent system (MAS) to UAV route track. The experiment proves that the multi-agent system benefits for the UAV track. <br>

Various remote sensing methods are being utilized to assess fundamental properties of forest stands, such as the height of trees, already for decades. Nevertheless, the use of Unmanned Aerial Vehicles in the combination with Structure from Motion software for these purposes, experiences its boom right now and thus not many pertinent studies exist yet. Such system producing image-based point clouds was utilized in this work to gain the canopy elevation data. To identify individual trees and to extract their height from these remote sensing data, a unique software tool called 'UAV Forest Explorer' was developed. Twenty forest study plots was established to acquire the field measurements ground truth data about almost 1 500 trees to thoroughly test the tool and calculate demanded statistics. The research proved, that the tool is fully applicable on all types of forest stands.

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This work introduces a design and implementation of using multiple unmanned aerial vehicles (UAVs) to achieve cooperative formation flight based on the personal remote sensing platforms developed by the author and the colleagues in the Center for Self-Organizing and Intelligent Systems (CSOIS). The main research objective is to simulate the multiple UAV system, design a multi-agent controller to achieve simulated formation flight with formation reconfiguration and real-time controller tuning functions, implement the control system on actual UAV platforms and demonstrate the control strategy and various formation scenarios in practical flight tests. Research combines analysis on flight control stabilities, develop- ment of a low-cost UAV testbed, mission planning and trajectory tracking, multiple sensor fusion research for UAV attitude estimations, low-cost inertial measurement unit (IMU) evaluation studies, AggieAir remote sensing platform and fail-safe feature development, al- titude controller design for vertical take-off and landing (VTOL) aircraft, and calibration and implementation of an air pressure sensor for wind profiling purposes on the developed multi-UAV platform. Definitions of the research topics and the plans are also addressed.

UAV/LiDAR-system har utvecklats snabbt under de senaste åren. De har blivit kompaktare och kan generera en hög punkttäthet med låg mätosäkerhet. Samtidigt har prisnivåerna sjunkit, vilket medfört att ett UAV/LiDAR-system nu kan införskaffas för några hundra tusen kronor. Det finns även mer avancerade UAV/LiDAR-system för ett par miljoner kronor.  Syftet med denna studie är att undersöka vilka skillnader som finns i kvalitet mellan två UAV/LiDAR-system i olika prisklasser. Framför allt kommer osäkerheter vid skapande av digitala terrängmodeller att studeras. De system som ingår i studien är drönaren DJI Matrice 300 RTK med LiDAR-sensorn DJI Zenmuse L1, och drönaren Microdrones md4-3000 kombinerad med LiDAR-modulen RIEGL miniVUX-1DL (mdLiDAR3000DL).  Undersökningen utfördes på en grustäkt i Rörberg utanför Gävle. En fri stationsetablering gjordes för att kunna mäta in stöd- och kontrollpunkter samt fem kontrollprofiler i terrängen. En flygning per drönare genomfördes över området. De erhållna punktmolnen bearbetades och jämfördes sedan mot kontrollpunkterna i höjdled. Även mängden brus i punktmolnen studerades. Därefter skapades digitala terrängmodeller som jämfördes mot kontrollprofilerna enligt metoden i SIS-TS 21144:2016.  Innan georeferering mot stödpunkter fanns det relativt stora skillnader mellan respektive punktmoln gällande avvikelsen i höjd. För DJI-punktmolnet blev till exempel medelavvikelsen 49 mm, medan mdLiDAR3000DL genererade en medelavvikelse på –21 mm. Efter brusreducering och inpassning av punktmolnen blev resultaten mer lika. Till exempel hade de två systemens punktmoln 13 mm i både standardavvikelse och RMS. Även de uppskattade brusmängderna var relativt lika. Den enda märkbara skillnaden var att mdLiDAR3000DL gav fler låga punkter procentuellt sett. Kontrollen av respektive DTM gav också ett jämnt resultat. DJI-systemets DTM hade en variationsvidd på 43 mm, medelavvikelsen 0 mm och standardavvikelsen 11 mm. MdLiDAR3000DL:s DTM hade 42 mm i variationsvidd, 0 mm i medelavvikelse och 8 mm i standardavvikelse.  Slutsatsen som kan dras är att det främst finns skillnader i osäkerhet innan någon databearbetning har genomförts. När punktmolnen brusreduceras och georefereras jämnas resultaten ut. Hanteringen av punktmoln har följaktligen en avgörande betydelse för osäkerheten i slutändan. Båda UAV/LiDAR- systemen kan därmed generera högkvalitativa slutprodukter. / UAV/LiDAR systems have developed rapidly in recent years. They are now more compact and can generate high point density with low uncertainty. The price level has also decreased, which entails that UAV/LiDAR systems are nowadays available for a few hundred thousand SEK. At the same time, more advanced UAV/LiDAR systems exist that cost a couple of million SEK.  The aim of this study is to investigate quality differences between two UAV/LiDAR systems in different price ranges. The focus will be on studying uncertainties when creating digital terrain models. The systems in question are the drone DJI Matrice 300 RTK with LiDAR sensor DJI Zenmuse L1, and the drone Microdrones md4-3000 combined with LiDAR sensor RIEGL miniVUX-1DL (mdLiDAR3000DL).  The study was made in a gravel pit in Rörberg outside of Gävle. A free station was set up to be able to measure ground control points (GCPs), check points, and five profiles in the terrain. One flight per drone was conducted over the area. The obtained point clouds were processed and later compared to the check points with respect to height deviations. Also, the noise level in the point clouds were studied. Digital terrain models were created and compared to the profiles according to the method in SIS-TS 21144:2016.  Before georeferencing against GCPs, there were relatively large differences between each point cloud in the height component. The DJI point cloud had for instance a mean deviation of 49 mm, while mdLiDAR3000DL generated a mean deviation of –21 mm. After noise reduction and fitting of the point clouds, the results were more even. For example, the two points clouds resulted in 13 mm in both standard deviation and RMS. Also, the estimated noise levels were rather similar. The only noticeable difference was that mdLiDAR3000DL generated a larger percentage of low points. The check of each DTM also resulted in similar results. The DTM of the DJI system reached a range of 43 mm, a mean deviation of 0 mm, and a standard deviation of 11 mm. The DTM of mdLiDAR3000DL obtained a 42 mm range, 0 mm mean deviation, and 8 mm standard deviation.  Mainly, there are differences in uncertainty before any data processing is carried out. When the point clouds are noise reduced and georeferenced, the results even out to a large extent. The handling of point clouds thus has decisive importance for the final uncertainty. Thus, both UAV/LiDAR systems can generate high-quality products.