No description available.

Flue-cured tobacco (Nicotiana tabacum L.) is a high value-per-acre crop that is intensively managed to optimize the yield of high quality cured leaf. Aerial remote sensing, specifically unmanned aerial vehicles (UAVs), present flue-cured tobacco producers and researchers with a potential tool for scouting and crop management. A two-year study, conducted in Southside Virginia at the Southern Piedmont Agricultural Research and Extension Center and on commercial farms, assessed the potential of aerial remote sensing in flue-cured tobacco. The effort encompassed two key objectives. First, examine the use of the enhanced normalized difference vegetation index (ENDVI) for separating flue-cured tobacco varieties and nitrogen rates. Secondly, develop hyperspectral indices and/or machine learning classification models capable of detecting Phytophthora nicotianae (black shank) incidence in flue-cured tobacco. In 2017, UAV-acquired ENDVI surveys demonstrated the ability to consistently separate between flue-cured tobacco varieties and nitrogen rates from topping to harvest. In 2018, ENDVI revealed significant differences among N-rates as early as 34 days after transplanting. Two hyperspectral indices were developed to detect black shank incidence based on differences in the spectral profiles of asymptomatic flue-cured tobacco plants compared to those with black shank symptoms. Testing of the indices showed significant differences between the index values of healthy and symptomatic plants (alpha = 0.05). In addition, the indices were able to detect black shank symptoms pre-symptomatically (alpha = 0.09). Subspace linear discriminant analysis, a machine learning classification, was also used for prediction of black shank incidence with up to 85.7% classification accuracy. / Master of Science / Unmanned Aerial Vehicle’s (UAVs) or drones, as they are commonly referred to, may have potential as a tool in flue-cured tobacco research and production. UAVs combined with sensors and cameras provide the opportunity to gather a large amount of data on a particular crop, which may be useful in crop management. Given the intensive management of flue-cured tobacco, producers may benefit from extra insight on how to better assess threats to yield such as under-fertilization and disease pressure. A two-year study was conducted in Southside Virginia at the Southern Piedmont Agricultural Research and Extension Center and on commercial farms. There were two objectives to this effort. First, assess the ability of UAV-acquired multispectral near-infrared imagery to separate flue-cured tobacco varieties and nitrogen rates. Secondly, develop hyperspectral indices and machine learning models that can accurately predict the incidence of black shank in flue-cured tobacco. Flue-cured tobacco nitrogen rates were significantly different in 2017 from 59 days after transplanting to harvest using UAV-acquired near-infrared imagery. In 2018, heavy rainfall may have led to nitrogen leaching from the soil resulting in nitrogen rates being significantly different as early as 34 days after transplanting. The imagery also showed a significant relationship with variety maturation type in the late stages of crop development during ripening. Two hyperspectral indices were developed and one machine learning model was trained. Each had the ability to detect black shank incidence in fluecured tobacco pre-symptomatically, as well as separated black shank infested plants from healthy plants.

The development and implementation of a flight test program for an unmanned aircraft is a multidisciplinary challenge. This thesis presents the development and implementation of a rigorous test program for the flight test of a Geometrically Scaled Joined Wing SensorCraft Remotely Piloted Vehicle from concept through successful flight test. The design methodology utilized in the development of the test program is presented, along with the extensive formal review process required for the approval of the test plan by the Air Force Research Laboratory. The design, development and calibration of a custom instrumentation package is also presented along with the setup, procedure and results from all testing. Results are presented for a wind tunnel test for air data boom calibration, propulsion system static thrust testing, a bifilar pendulum test for experimental calculation of mass moments of inertia, a static structural loading test for structural design validation, a full taxi test and a successful first flight. / Master of Science

It is a well-recognized fact that unmanned aerial vehicles are an essential element in today’s network-centric integrated battlefield environment. Compared to solo UAV missions, multiple unmanned aerial vehicles deployed in co-operative mode, offer many advantages that has motivated UAV researchers all over the world to evolve concept of operations that aims in achieving a paradigm shift from traditional ”dull” missions to perform ”dirty” and ”dangerous” missions. In future success of a mission will depend on interaction among UAV groups with no interaction with any ground entity. To reach this capability level, it is necessary for researchers, to first understand the various levels of autonomy and the crucial role that information and communication plays in making these autonomy levels possible. The thesis is in four parts: (i) Development of an organized framework to realize the goal of achieving fully autonomous systems. (ii) Design of UAV grouping algorithm and coordination tactics for ground attack missions. (iii) Cooperative network management in GPS denied environments. (iv) UAV group tactical path and goal re-plan in GPS denied wide area urban environments. This research thesis represents many first steps taken in the study of autonomous UAV systems and in particular group autonomy. An organized framework for autonomous mission control level by defining various sublevels, classifying the existing solutions and highlighting the various research opportunities available at each level is discussed. Significant contribution to group autonomy research, by providing first of its kind solution for UAV grouping based on Dubins’ path, establishing GPS protected wireless network capable of operating in GPS denied environment and demonstration of group tactical path and goal re-plan in a layered persistent ISR mission is presented. Algorithms discussed in this thesis are generic in nature and can be applied to higher autonomous mission control levels, involving strategic decisions among UAVs, satellites and ground forces in a network centric environment.

Approved for public release, distribution is unlimited / A control system was developed for autonomous visual tracking of a stationary target using a small unmanned aerial vehicle. The kinematic equations of this problem were developed, and the insight obtained from examination was applied in developing controllers for the system. This control system controlled the orientation of the camera to keep it constantly pointing at the target, and also controlled the trajectory of the aircraft in flight around the target. The initial control law that was developed drives the aircraft trajectory to a constant radius around the target. The range to the target is not directly measurable, so it was estimated using steady state Kalman filters. Once a range estimate is obtained, it is used to control the range to the target, and the aircraft trajectory is driven toward a circle with a specified radius. Initial tests of the control system with Simulink simulations have shown good performance of the control system. Further testing with hardware will be conducted, and flight tests are scheduled to be conducted in the near future. Conclusions are drawn and recommendations for further study are presented. / Ensign, United States Navy

Orientador: Vania Silvia Rosolen / Resumo: No Brasil, a captação de água para irrigação é de aproximadamente 1000 m³/s, caracterizando o maior consumo de água do território nacional. Como possível ambiente de estoque natural de água que cobre quase 20% do território, as áreas úmidas vem sendo drasticamente reduzidas pela conversão do uso da terra. As áreas úmidas promovem a infiltração das águas superficiais e caracterizam áreas de recarga de aquíferos. Nesse sentido, medidas e modelos relacionados aos solos com propriedades hidromórficas e seu papel na recarga de aquíferos constituem um desafio para compreender a dinâmica entre solo e água, a fim de atender o desenvolvimento sustentável. Neste estudo, análises baseadas em sensoriamento remoto, com o uso de sensores ópticos de alta resolução espaço-temporal a bordo de Veículos Aéreos Não Tripulados (VANT), associadas ao uso de técnicas não invasivas que permitem o mapeamento da arquitetura subsuperficial dos sistemas pedológicos (ensaios geofísicos de Eletrorresistividade, por Tomografia Elétrica), foram aplicadas para compreender a relação água-solo superficial e subsuperficial em uma área úmida da chapada sedimentar do oeste mineiro. A integração destes dados com ensaios in situ de permeabilidade e de densidade e granulometria dos solos, permitiu uma abordagem ampla e tridimensional do comportamento dos parâmetros hidrogeológicos na área úmida. Os resultados permitiram determinar que a área úmida estudada é uma depressão que possui três compartimentos com distinções... (Resumo completo, clicar acesso eletrônico abaixo) / Mestre

Os Veículos Aéreos Não Tripulados (VANTs) são ideais para operações de risco e estressante para o ser humano são as chamadas dull, dirty and dangerous missions. Portanto, uma importante aplicação desse tipo de robô aéreo diz respeito a operações de busca envolvendo múltiplos VANTs cooperativos, em que há risco de colisões entre aeronaves e o tempo de um voo é limitado, entre outros fatores, pela capacidade de um piloto trabalhar sem descanso. Entretanto, apesar de atualmente verificar-se um crescente número de pesquisas envolvendo VANTs e do grande potencial existente na utilização de VANTs, operações de busca cooperativas ainda não estão ocorrendo. Esse assunto é uma área de estudo multidisciplinar e nascente, que possui diversas linhas de pesquisa. Diferentes algoritmos de navegação e padrões de busca foram estudados visando selecionar o(s) mais adequado(s). Além disso, apresenta-se, neste trabalho, uma visão geral sobre os mecanismos de coordenação multiagente e avalia a adequação de cada uma delas à coordenação distribuída de agentes (VANTs), visando cooperação. Assim, com o objetivo de melhorar o desempenho de uma operação de busca, esta pesquisa de mestrado propõe um modelo de VANTs cooperativos que combina mecanismos de coordenação multiagente, algoritmos de navegação e padrões de busca estabelecidos pelos principais órgãos responsáveis pelas operações de busca e salvamento. Visando avaliar a sensibilidade do percentual médio de detecção de objetos, bem como o tempo médio de busca, foi desenvolvido um simulador e milhares de simulações foram realizadas. Observou-se que, utilizando o modelo, VANTs cooperativos podem reduzir, em média, 57% do tempo de busca (comparando com uma busca de dois VANTs não cooperativos no mesmo cenário), mantendo a probabilidade média de detecção dos objetos próxima de 100% e sobrevoando apenas 30% do espaço de busca. / There are an increasing number of researches into UAV (Unmanned Aerial Vehicle) in the literature. These robots are quite suitable to dull, dirty and dangerous missions. Thus, an important application of these vehicles is the search operations involving multiple UAVs in which there is risk of collisions among aircrafts and the flight time is limited by the maximum time of pilot working hours. However, despite the huge potential use of the UAVs, cooperative search operations with this kind of flying robots are not yet occurring. This research topic is a new and multidisciplinary area of study in its beginning and there are several issues that can be studied, such as centralized versus decentralized control, path planning for cooperative flights, agent reasoning for UAV tactical planning, safety assessments, reliability in automatic target reconnaissance by cameras, agent coordination mechanisms applied to UAV cooperation and the application itself. Different path planning algorithms were studied aiming to attain the most suitable to these kinds of operations, and the conclusions are presented. In addition, official documents of Search and Rescue operations are also studied in order to know the best practices already established for this kind of operations, and, finally, an overview of the coordination multi-agent theory is presented and evaluated to achieve the UAV coordination. This work proposes a model that combines path planning algorithms, search patterns and multi-agent coordination techniques to obtain a cooperative UAV model. The great goal for cooperative UAV is to achieve such performance that the performance of the group overcomes the sum of the individual performances isolatedly. Then, aiming to analyze the average percentage of objects detection, and the average search time, a simulator was developed and thousands of simulations were run. It was observed that, using the proposed model, two cooperative UAVs can perform a search operation 57% faster than two non cooperative UAVs, keeping the average probability of objects detection approaching at 100% and flying only 30% of the search space.

Detecção de linhas de alta tensão em ambientes complexos é uma das tarefas mais desafiadoras em inspeções que utilizam Veículos Aéreos Não Tripulados (VANTs). Este trabalho foca em dar uma solução para este desafio, através do desenvolvimento de um algoritmo de controle de voo de precisão, que guie o VANT de maneira autônoma sobre as linhas de alta tensão. O algoritmo proposto é baseado em quatro etapas: Captura da Imagem, Filtragem da Imagem, Detecção das Linhas e Controle de Voo. Inicialmente a imagem é redimensionada para um tamanho em que as linhas fiquem em maior evidência, depois uma sequência de filtros é aplicada na imagem para reduzir ruído e evidenciar ainda mais as linhas. Depois deste pré-tratamento, um filtro de duas dimensões com formato similar ao de uma linha de alta tensão é usado para extrair os pixels pertencentes as bordas destas linhas. Após a aplicação do filtro de duas dimensões, a Transformada de Hough é aplicada na imagem resultante para detectar os segmentos de reta. Por fim, todos os dados obtidos no processamento da imagem são utilizados para guiar o VANT de maneira autônoma pelas linhas de transmissão. O algoritmo proposto apresenta um eficiente sistema de detecção de linhas de alta tensão, para auxiliar o controle de voo autônomo de um VANT, apresentando resultados convincentes. / Power lines detection in complex environments is one of the most important and challenging tasks in Unmanned Aerial Vehicles (UAV)-based inspections. This work focuses on tackling this challenge by developing a control algorithm to support fine grain UAV control to autonomously guide the aerial platform over the power lines. The proposed algorithm is based on four stages: Image Capturing, Image Filtering, Line Detection and Flight Control. Firstly, the image is cropped to a size that fits all the power lines, then a sequence of filters is applied in the image to reduce noise and highlight these lines. After all the image's pretreatment, a 2D filter with similar shape of a power transmission line is used to extract pixels that belongs to the line's edges. Then, the Hough Transform method detects the line segments in the edges result image. Lastly all the obtained data is used to autonomously guide a UAV over the power transmission lines. The proposed algorithm presents an efficient power transmission lines detecting system to support the autonomous UAV guidance, which presents convincing results.

A segurança nos voos de Veículos Aéreos Não Tripulados (VANTs) é uma importante questão e vem ganhando destaque devido a uma série de acidentes com tais aeronaves. O aumento do número de aeronaves no espaço aéreo e a autonomia cada vez maior para realizar missões estão entre outros elementos que merecem destaques. No entanto, pouca atenção tem sido dada a autonomia da aeronave em casos emergenciais [Contexto]. Nesse contexto, o desenvolvimento de algoritmos que efetuem o planejamento de rotas na ocorrência de situações críticas é fundamental para obter maior segurança aérea. Eventuais situações de insegurança podem estar relacionadas a uma falha nos equipamentos do veículo aéreo que impede a continuação da missão em curso pela aeronave [Lacuna]. A presente pesquisa avança o estado da arte considerando um conceito chamado In-Flight Awareness (IFA), que estabelece consciência situacional em VANTs, visando maior segurança de voo. Os estudos também avançam na proposição de modelos matemáticos que representem o estado da aeronave avariada, viabilizando o pouso emergencial e minimizando possíveis danos [Propósito]. Este trabalho utiliza técnicas de computação evolutiva como Algoritmos Genéticos (AG) e Algoritmos Genéticos Multi-Populacional (AGMP), além de uma Heurística Gulosa (HG) e um modelo de Programação Linear Inteira Mista (PLIM) no tratamento de falhas críticas juntamente com o conceito de IFA [Metodologia]. As soluções obtidas foram avaliadas através de experimentos offline usando os modelos matemáticos desenvolvidos, além de validadas em um simulador de voo e em um voo real. De forma geral, o AG e AGMP obtiveram resultados equivalentes, salvando o VANT em aproximadamente 89% dos mapas. A HG conseguiu trazer a aeronave até uma região bonificadora em 77% dos mapas dentro de um tempo computacional abaixo de 1 segundo. No modelo PLIM, o tempo gasto foi de cerca de quatro minutos já que garantia a otimalidade da solução encontrada. Devido ao seu elevado tempo computacional, uma estratégia evolvendo rotas pré-calculadas foi definida a partir do PLIM, mostrando-se bastante promissora. Nos experimentos envolvendo simulador de voo foram testadas diferentes condições de vento e se verificou que mesmo sobre tais condições os métodos desenvolvidos conseguiram efetuar o pouso com segurança [Resultado]. O trabalho apresentado colabora com a segurança de Veículos Aéreos Não Tripulados e com a proposta de modelos matemáticos que representem a aeronave em caso de situações críticas. Os métodos, de forma geral, mostraram-se promissores na resolução do problema de pouso emergencial já que trouxeram a aeronave com segurança até regiões interessantes ao pouso em um baixo tempo computacional. Isso foi atestado pelos resultados obtidos a partir das simulações offline, em simulador de voo e em voo real [Conclusão]. As principais contribuições do trabalho são: modelagem de regiões adequadas ao pouso, modelagem de falhas, arquitetura do sistema planejador de rotas e modelo linear para para pouso emergencial [Contribuição]. / The security involved in flights of Unmanned Aerial Vehicles (UAVs) is an important issue and is achieving prominence due to a number of accidents involving such aircraft. Other elements that deserve highlights are the increase in the number of aircraft in the airspace and autonomy to perform missions, however, little attention has been given to the autonomy of the aircraft in emergency cases [Context]. In this context, the development of algorithms that contribute significantly to the path planning in the event of critical situations is essential for more air traffic. Possible situations of insecurity may be related to a failure in the equipment of vehicle that prevents the continuation of the current mission by aircraft [Gap]. The research advances the state of the art considering a concept called In-Flight Awareness (IFA), which provides situational awareness in UAVs aiming at greater flight safety. Advances also in the developing of mathematical models that represent the state of the damaged aircraft, with the purpose to execute the emergency landing by minimizing damages [Purpose]. Thus, this work applies evolutionary computation techniques such as Genetic Algorithms (GA) and Multi-Population Genetic Algorithms (MPGA), as well as a Greedy Heuristic (GH) and a Mixed Integer Linear Programming (MILP) model to deal with critical situations along with the concept of IFA [Methodology]. The solutions obtained were evaluated through offline experiments using the developed mathematical models, which were validated in a flight simulator and a real-world flight. In General, the GA and MPGA reached similar results by saving the UAV in approximately 89% of the maps, while the GH was able to bring the aircraft to a bonus region for 77% of maps within a feasible computational time lower than 1 second. In the MILP model, the time spent was about four minutes since it guarantees optimality of the solution found. Due to such high computational time, a strategy involving nearby routes pre-calculated was defined from the MILP which was very promising. In experiments involving flight simulator, different wind conditions were tested and it was found that even under such conditions the methods developed have managed to execute the landing safely [Result]. The work presented collaborates with the safety of Unmanned Aerial Vehicles and with the proposal of mathematical models that represent the aircraft under critical situations. The methods, in general, were promising since they brought the aircraft to execute a safe landing within a low computational time as shown by offline simulations, flight simulator and real flight [Conclusion]. The main contributions are: fault modeling, system architecture planner routes and linear model for emergency landing. [Contribution].

This paper aims to present the thesis developed in the Doctoral Programin Computer Science and Computational Mathematics of the ICMC/USP. The thesis theme seeks to advance the state of the art by solving the problems of scalability and representation present in mission planning algorithms for Unmanned Aerial Vehicle (UAV). Techniques based on mathematical programming and evolutionary computation are proposed. Articles have been published, submitted or they are in final stages of preparation.These studies report the most significant advances in the representation and scalability of this problem. Mission planners worked on the thesis deal with stochastic problems in non-convex environments,where collision risks or failures in mission planning are treated and limited to a tolerated value. The advances in the representation allowed to solve violations in the risks present in the original literature modeling, besides making the models more realistic when incorporating aspects such as effects of the air resistance. Efficient mathematical modeling techniques allowed to advance from a Mixed Integer Nonlinear Programming (MINLP) model, originally proposed in the literature, to a Mixed Integer Linear Programming (MILP) problem. Modeling as a MILP led to problem solving more efficiently through the branch-and-algorithm. The proposed new representations resulted in improvements from scalability, solving more complex problems within a shorter computational time. In addition, advances in scalability are even more effective when techniques combining mathematical programming and metaheuristics have been applied to the problem. / O presente documento tem por objetivo apresentar a tese desenvolvida no Programade Doutorado em Ciência da Computação e Matemática Computacional do ICMC/USP. O tema da tese busca avançar o estado da arte ao resolver os problemas de escalabilidade e representação presentes em algoritmos de planejamento para missões com Veículos Aéreos Não Tripulados (VANTs). Técnicas baseadas em programação matemática e computação evolutiva são propostas. Artigos foram publicados, submetidos ou se encontram em fase final de elaboração. Esses trabalhos reportamos avanços mais significativos obtidos na representação e escalabilidade deste problema.Os planejadores de missão trabalhados na tese lidam com problemas estocásticos em ambientes não convexos, onde os riscos de colisão ou falhas no planejamento da missão são tratados e limitados a um valor tolerado. Os avanços na representação permitiram solucionar violações nos riscos presentes na modelagem original, além de tornar os modelos mais realistas ao incorporar aspectos como efeitos da resistência do ar. Para isso, técnicas eficientes de modelagem matemática permitiram avançar de um modelo de Programação Não-Linear Inteira Mista(PNLIM), originalmente proposto na literatura, para um problema de Programação Linear Inteira Mista (PLIM). A modelagem como um PLIM levou à resolução do problema de forma mais eficiente através do algoritmo branch-and-cut. As novas representações propostas resultaram em melhorias na escalabilidade, solucionando problemas mais complexos em um tempo computacional menor.Além disso,os avanços em escalabilidade mostraram-se mais efetivos quando técnicas combinando programação matemática e metaheurísticas foram aplicadas ao problema.