Made available in DSpace on 2015-04-11T14:02:52Z (GMT). No. of bitstreams: 1 milton.pdf: 1235914 bytes, checksum: dff60afa3cc8a29da9cf209d407c7d8f (MD5) Previous issue date: 2013-03-26 / The three Attitude Parameters or Critical Flight Parameters - Attack, Yaw and Roll - are the angles that describe the rotational movements of an aerial vehicle in three-dimensional space. From the estimate of these angles, we can accomplish the stabilization of flight. The need for it varies for each type of aerial vehicle in inverse proportion to the stability provided by their mechanical characteristics. Moreover, the association of critical angles with other flight parameters, such as altitude and velocity, enables the description of all vehicle movements, and consequently, the execution of a flight path predetermined. Critical Flight Parameters can be inferred by electromechanical inertial sensors, Global Positioning System or by visual perception. Several authors mention that the electromechanical sensors fail and Global Positioning System are unavailable for some period of time under various environmental conditions, leading to loss of orientation and, in the case of unmanned vehicles, several accidents, given the lack of support from a pilot on these situations. In this work two techniques are integrated to estimate these parameters, based on Robotic Vision: the first one is based on the position and inclination of the Horizon about the aerial vehicle; and the second one is based on the estimation of optical flow of the scene viewed by the aerial vehicle. The use of optical flow provides the estimation of Yaw Parameter, which is not got at Horizon approach. It also enables the estimation of Critical Flight Parameters when the Horizon is not present. Both techniques are associated with camera parameters and integrated to provide more robustness to the flight angles estimation. Experiments conducted using real images of fixed-wing aircraft flight proved the method efficacy in open and unstructured envinroment. / Os três Parâmetros de Atitude ou Parâmetros Críticos de Voo Ataque, Guinada e Rolagem são os ângulos que descrevem os movimentos rotacionais de um veículo aéreo no espaço tridimensional. A partir da estimativa destes ângulos, pode-se realizar a estabilização de voo, cuja necessidade varia para cada tipo de veículo aéreo em proporção inversa à estabilidade proporcionada pelas suas características mecânicas. Além disto, a associação dos ângulos críticos de voo com outros parâmetros, como altitude e velocidade, possibilita a descrição de todos os movimentos do veículo, e consequentemente, a execução de uma rota de voo pré-determinada. Os ângulos críticos de voo podem ser inferidos por sensores eletromecânicos inerciais, pelo Sistema de Posicionamento Global ou por percepção visual. Diversos autores citam que os sensores eletromecânicos falham e o Sistema de Posicionamento Global fica indisponível por algum intervalo de tempo sob diversas condições ambientais, ocasionando a perda da orientação e, nos casos de veículos nãotripulados, acidentes e perdas de veículos, dada a falta do apoio de um piloto nestas situações. Neste trabalho são integradas duas técnicas de estimativa destes parâmetros, baseadas em Visão Robótica: a primeira é baseada na posição e inclinação do Horizonte com relação ao veículo aéreo; a segunda é baseada na estimativa do Fluxo Óptico da cena frontal ao veículo aéreo. O uso do Fluxo Óptico possibilita a estimativa do Parâmetro de Guinada, que não é realizada na abordagem baseada no Horizonte. Também possibilita a estimativa dos Parâmetros Críticos de Voo quando o Horizonte não está presente. As duas técnicas são associadas a parâmetros da câmera e integradas para dar mais robustez à estimativa dos ângulos de voo. Experimentos realizados usando-se imagens reais de voos de veículos aéreos de asa fixa provaram a eficiência do método em ambiente aberto e não-estruturado.

Submitted by Renata Lopes (renatasil82@gmail.com) on 2017-10-02T19:31:50Z No. of bitstreams: 1 felipedesouzadelgado.pdf: 2621698 bytes, checksum: f2d2c40acc8fdf80a70c9f39aabc0cc9 (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2017-10-09T19:46:37Z (GMT) No. of bitstreams: 1 felipedesouzadelgado.pdf: 2621698 bytes, checksum: f2d2c40acc8fdf80a70c9f39aabc0cc9 (MD5) / Made available in DSpace on 2017-10-09T19:46:37Z (GMT). No. of bitstreams: 1 felipedesouzadelgado.pdf: 2621698 bytes, checksum: f2d2c40acc8fdf80a70c9f39aabc0cc9 (MD5) Previous issue date: 2017-08-24 / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Esta dissertação apresenta a produção de redes de período longo em fibras ópticas por descargas de arcos elétricos e o seu uso em aplicações de sensoriamento de corrente em veículos aéreos não tripulados. Os aspectos teóricos fundamentais para o entendimento das redes de período longo são apresentados. Além disso, discutiu-se os diferentes tipos de acoplamentos de energia que podem ocorrer em uma rede de período longo e também, os mecanismos responsáveis pela formação dessas redes produzidas por descargas de arco elétrico. A fabricação de redes de período longo utilizando a técnica de arco elétrico foi descrita e o comportamento da perda dependente da polarização das redes produzidas foi investigado. Além disso, é apresentado um novo método para a produção de redes de período longo com perda dependente da polarização reduzida. Constatou-se que por meio de alterações no ângulo de incidência das descargas elétricas na fibra óptica em relação à um ponto de referência, é possível promediar os efeitos induzidos pontualmente por cada descarga de arco elétrico e assim, reduzir a perda dependente da polarização intrínseca dessas redes. Por fim, é apresentada a aplicação de uma rede produzida por arco elétrico combinada a um ímã de neodímio, compondo um novo dispositivo de sensoriamento para medir a corrente elétrica exigida pelos motores elétricos de um veículo aéreo não tripulado. / This dissertation presents the fabrication of long-period fiber gratings through electric arc discharges and their application in current sensing in unmanned aerial vehicles. The theoretical aspects of long-period gratings are presented. Besides, we discussed the different types of coupling that could occur in a long-period fiber grating, as well as the mechanisms responsible for the formation of the gratings produced by electric arc discharges. The manufacture process of the long-period gratings using the electric arc technique was described and the behavior of the polarization dependent loss of these gratings was investigated. In addition, a new method for the production of long period gratings with reduced polarization dependent loss is introduced. It has been found that by changing the incidence angle of the electric discharges in the optical fiber in relation to a reference point, it is possible to average the effects induced by each electric arc discharge and, therefore, reducing the intrinsic polarization dependent loss of these gratings. Finally, the application of a grating produced by electric arc combined with a neodymium permanent magnet is presented. This combination allows us to measure the electric current required by a motor of an unmanned aerial vehicle.

Orientadores: Paulo Augusto Valente Ferreira, Ely Carneiro de Paiva / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação / Made available in DSpace on 2018-08-04T03:59:44Z (GMT). No. of bitstreams: 1 Faria_BrunoGuedes_M.pdf: 2340545 bytes, checksum: 440ff7a9aa46f5a39514e81423363750 (MD5) Previous issue date: 2005 / Resumo: Nos últimos anos tem-se observado um crescente interesse de empresas e instituições de pesquisa pelo desenvolvimento de veículos robóticos, dotados de diferentes níveis de capacidade de operação autônoma, objetivando a execução de diversas tarefas. Dentro deste contexto o CenPRA, Centro de Pesquisas Renato Archer, propôs o Projeto AURORA. O Projeto AURORA (Autonomous Unmanned Remote mOnitoring Robotic Airship) tem como seu principal objetivo o desenvolvimento de protótipos de veículos aéreos tele-operados, e a obtenção de veículos telemonitorados, através do desenvolvimento de sistemas com graus de autonomia crescentes. Para que se possam agregar níveis crescentes de autonomia ao veículo, é essencial incrementar seu sistema de controle e navegação de maneira gradativa. Por esse motivo o aprimoramento das estratégias de controle do sistema é essencial. Assim, é primordial possuir um modelo fidedigno do sistema físico em questão, pois somente dessa forma é possível elaborar leis de controle e testá-las imediatamente em simulação antes de partir para os ensaios práticos no veículo real. Além disso, um modelo adequado é essencial para a simulação do vôo do dirigível de forma a permitir a análise preliminar de seu comportamento diante de uma nova missão. O principal objetivo deste trabalho é a implementação e validação de metodologias para a identificação do modelo dinâmico longitudinal do dirigível. Foram abordadas três metodologias para a identificação do modelo dinâmico do dirigível: a identificação estacionária, que identifica os coeficientes aerodinâmicos do dirigível a partir de um vôo estacionário, a identificação dinâmica, que identifica esses coeficientes e a dinâmica linearizada do veículo a partir de um vôo com entradas de perturbação conhecidas e, finalmente, a identificação por meio de estratégias evolutivas, que procura otimizar alguns parâmetros do modelo dinâmico. As três metodologias foram testadas, validadas e comparadas através de ensaios de simulação, utilizando-se o simulador do dirigível AS800 do Projeto AURORA / Abstract: In recent years many research institutions and companies have been demonstrating a growing interest in the development of unmanned aerial vehicles with different autonomous operation levels in order to allow for the performance of many types of tasks. Within this context, CenPRA (Renato Archer Research Center) proposed the Project AURORA. Project AURORA (Autonomous Unmanned Remote Monitoring Robotic Airship) aims at the development of unmanned airships remotely operated with a view to the creation of an autonomous flight airship by the incorporation of increasing levels of autonomy. In order to increase the vehicle autonomy level, the development of a proportionally enhanced control and navigation systems is essential. It is extremely important to have a very accurate model of the physical airship system, given that this is the only way to design control laws for the vehicle and test them in simulation before performing actual flight tests. Moreover, an accurate model is essential to predict the vehicle behavior in simulation before any real flight demanding a new type of mission. The definition of identification methodologies for the AS800 airship system identification is the main scope of this work. Three methodologies were considered to allow the airship dynamic model identification: stationary identification, which identifies aerodynamic coefficients from stationary stabilized flight conditions; dynamic identification, which identifies these coefficients and the vehicle linear dynamics from the application of known inputs into the system; and, finally, through evolution strategies, which uses an evolutionary approach for the optimization of the aerodynamic coefficients of the dynamic model. All the methodologies were tested, validated and compared through simulation experiments by using the AS800 airship simulator of the Project AURORA / Mestrado / Automação / Mestre em Engenharia Elétrica

[pt] Esta dissertação apresenta uma abordagem para a coordenação de enxames de Veículos Aéreos Não Tripulados (VANT), baseada na comunicação via Internet provida pelas redes de telefonia móvel. Um grande número de atividades pode ser coberto com uma missão conjunta de VANTs voando em formação, como a vigilância e monitoramento de grandes eventos, tarefas de busca e salvamento, controle de pestes agrárias, fiscalização e conservação florestal, inspeção de oleodutos e redes de distribuição elétrica ou mesmo em missões militares de ataque e reconhecimento. A coordenação de enxame de VANTs pode ser fatorada na comunicação entre os membros do enxame e o algoritmo de controle e interrelacionamento entre os membros. A solução proposta consiste no uso de smartphones acoplados a VANTs capazes de prover o nível necessário de comunicação confiável sobre a Internet móvel, e processar o algoritmo proposto para a coordenação dos enxames de VANTs. Experimentos foram feitos através da emulação de VANTs e redes de dados de telefonia que demostraram a eficácia do algoritmo proposto e analisam o impacto da latência de rede e da velocidade dos VANTs sobre a precisão da coordenação de movimento de enxames. / [en] This work presents an approach to coordinate swarms of Unmanned Aerial Vehicles (UAV) based on Internet communication provided by mobile phone networks. Several activities can be done by several UAVs flying in formation, such as surveillance and monitoring of mass events, search and rescue tasks, control of agricultural pests, monitoring and forest conservation, inspection of pipelines and electricity distribution networks or even military attack and recognition missions. Coordination of UAVs swarm can be branch in two sub-problems: communication between members of the swarm and the algorithm that controls members behaviors regarding their movements. The proposed solution assumes the use of a smartphone coupled with each UAV of the swarm, in order to provide the required level of reliable communication on the mobile Internet and run the proposed algorithm for the coordination of swarms of UAVs. Experiments were performed with emulated UAVs and WAN mobile networks. The results have demonstrated the effectiveness of the proposed algorithm, and have shown the influence of the network latency and the UAV speeds on the accuracy of the movement coordination in the swarms.

No description available.

The master´s thesis deals with the application of unmanned aerial vehicle (UAV) in photogrammetry and mapping. The first part describes the UAV that was used for imaging, legislative restrictions resulting from its operations, planning and realization of the flight. The second part of this thesis is focused on processing results, especially on evaluation the accuracy of the results gained by UAV with and without a GNSS module. The data are evaluated in the 3rd accuracy rating class (ČSN 01 3410). The theoretical principles are explained as well. The main aim of the thesis is to demonstrate the effective use of the GNSS module Emlid Reach and the unmanned aerial vehicle in geodesy.

The master thesis deals with design and realization of stabilizing and autopilot system, which is used in radio controlled model planes. The thesis contains a proposal of hardware platform, which is able to control the plane model based on data measured from a sensor system. Moreover, this thesis describes a software implementation of individual modules, which is measured the onboard values. The basic principles of stabilization and autonomous flight control are also summarized. In conclusion, the system is subjected to flight tests.

This thesis proposes a system for extraction of vehicle trajectories from aerial video data for traffic analysis. The system is designed to analyse video sequence of a single traffic scene captured by an action camera mounted on an arbitrary UAV flying at the altitudes of approximately 150 m. Each video frame is geo-registered using visual correspondence of extracted ORB features. For the detection of vehicles, MB-LBP classifier cascade is deployed, with additional step of pre-filtering of detection candidates based on movement and scene context. Multi-object tracking is achieved by Bayesian bootstrap filter with an aid of the detection algorithm. The performance of the system was evaluated on three extensively annotated datasets. The results show that on the average, 92% of all extracted trajectories are corresponding to the reality. The system is already being used in the research to aid the process of design and analysis of road infrastructures.

The ability for unmanned autonomous aerial vehicles (UAV) to localize themselves in an environment is fundamental for them to be able to function, even if they do not have access to a global positioning system. Recently, with the success of deep learning in vision based tasks, there have been some proposed methods for absolute geolocalization using vison based deep learning with satellite and UAV images. Most of these are only tested in urban environments, which begs the question: How well do they work in non-urban areas like forests and fields? One drawback of deep learning is that models are often regarded as black boxes, as it is hard to know why the models make the predictions they do, i.e. what information is important and is used for the prediction. To solve this, several neural network interpretation methods have been developed. These methods provide explanations so that we may understand these models better. This thesis investigates the localization accuracy of one geolocalization method in both urban and non-urban environments as well as applies neural network interpretation in order to see if it can explain the potential difference in localization accuracy of the method in these different environments. The results show that the method performs best in urban environments, getting a mean absolute horizontal error of 38.30m and a mean absolute vertical error of 16.77m, while it performed significantly worse in non-urban environments, getting a mean absolute horizontal error of 68.11m and a mean absolute vertical error 22.83m. Further, the results show that if the satellite images and images from the unmanned aerial vehicle are collected during different seasons of the year, the localization accuracy is even worse, resulting in a mean absolute horizontal error of 86.91m and a mean absolute vertical error of 23.05m. The neural network interpretation did not aid in providing an explanation for why the method performs worse in non-urban environments and is not suitable for this kind of problem. / Obemannade autonoma luftburna fordons (UAV) förmåga att lokaliera sig själva är fundamental för att de ska fungera, även om de inte har tillgång till globala positioneringssystem. Med den nyliga framgången hos djupinlärning applicerat på visuella problem har det kommit metoder för absolut geolokalisering med visuell djupinlärning med satellit- och UAV-bilder. De flesta av dessa metoder har bara blivit testade i stadsmiljöer, vilket leder till frågan: Hur väl fungerar dessa metoder i icke-urbana områden som fält och skogar? En av nackdelarna med djupinlärning är att dessa modeller ofta ses som svarta lådor eftersom det är svårt att veta varför modellerna gör de gissningar de gör, alltså vilken information som är viktig och används för gissningen. För att lösa detta har flera metoder för att tolka neurala nätverk utvecklats. Dessa metoder ger förklaringar så att vi kan förstå dessa modeller bättre. Denna uppsats undersöker lokaliseringsprecisionen hos en geolokaliseringsmetod i både urbana och icke-urbana miljöer och applicerar även en tolkningsmetod för neurala nätverk för att se ifall den kan förklara den potentialla skillnaden i precision hos metoden i dessa olika miljöer. Resultaten visar att metoden fungerar bäst i urbana miljöer där den får ett genomsnittligt absolut horisontellt lokaliseringsfel på 38.30m och ett genomsnittligt absolut vertikalt fel på 16.77m medan den presterade signifikant sämre i icke-urbana miljöer där den fick ett genomsnittligt absolut horisontellt lokaliseringsfel på 68.11m och ett genomsnittligt absolut vertikalt fel på 22.83m. Vidare visar resultaten att om satellitbilderna och UAV-bilderna är tagna från olika årstider blir lokaliseringsprecisionen ännu sämre, där metoden får genomsnittligt absolut horisontellt lokaliseringsfel på 86.91m och ett genomsnittligt absolut vertikalt fel på 23.05m. Tolkningsmetoden hjälpte inte i att förklara varför metoden fungerar sämre i icke-urbana miljöer och är inte passande att använda för denna sortens problem.

Distributed networks, meaning a network in which several agents work together unanimously to perform some task in order to reach goals has become a field with a wide range of applications. One such applications may exist in the form of drones with a purpose of observing and detecting forest fires. In such applications it can be of paramount importance to be able to agree over some opinions or values between the agents. This value could be something such as event detection or a general direction to fly in. However in such a network there might not exist a central hub and it would not be possible for all drones to communicate directly with each other. In order for such a network to be able to reach consensus or agreement, values have to be exchanged between the agents. This thesis focuses on a subset of this problem known as distributed averaging. In the thesis it is investigated how a networks ability to detect forest fires and communicate both efficiently and quickly can change when the number of agents are adjusted in the network. The results showed that, when operating in a fixed area, for a small network of drones the increasing effective energy cost per drone were higher, than that of a larger network. It was also discovered that the speed at which a network could reach an agreement was not necessarily affected by the size of the network. But as the field area being observed was increased, adverse effects were observed in terms of communication and event detection. / Distribuerade nätverk bestående av flera agenter som har som uppgift att tillsammans nå gemensamma resultat har blivit allt mer populärt. Ett sådant användningsområde är hur drönare kan användas för att observera och upptäcka skogsbränder över en given yta. I en sådan tillämpning är det av stor vikt att drönarnätverket kan kommunicera och kongruera över värden nätverket delar med varandra. Dessa värden kan representera händelser som nätverket har som uppgift att upptäcka eller en riktning för drönarna att flyga i. Det är inte alltid garanterat att det finns en central kommunikationscentral för sådana nätverk, utan blir beroende på att kommunicera med varandra för att utbyta och kongruera över värden. Den här rapporten fokuserar på en avgränsad del av det ovanstående problemet som kallas för distribuerat konsensusvärde (eng. distributed averaging). Rapporten undersöker hur ett sådant nätverks konvergeringsförmåga, totala energikostnad samt täckning påverkas när fler drönare tillförs till nätverket. När arbetsytan var satt till statisk storlek visade resultaten att den tillförda energikostnaden per drönare var högre för små nätverk än för större nätverk. Det visades också att hastigheten som nätverket når ett kongruerande värde inte nödvändigtvis påverkas av storleken av nätverket. När arbetsytan ökade i takt med storleken på nätverket observerades däremot motsatt effekt för energikostnad och hastigheten för att nå ett konsensusvärde.