A mitigação de desastres naturais exige respostas rápidas e confiáveis. No Brasil, a estação de chuvas provoca muitos alagamentos em regiões urbanas e, para monitorar esse fenômeno, foi instalada em São Carlos-SP uma rede de sensores sem fio para acompanhar o nível de água dos rios da cidade. Entretanto, essa rede de sensores está suscetível a falhas que podem comprometer o funcionamento do sistema, e a adoção de mecanismos redundantes e de redes móveis 3G podem acarretar em custos proibitivos à monitoração desses rios, além de não garantirem a operação normal desse monitoramento. Assim, este trabalho apresenta uma solução baseada em veículo aéreo não tripulado (VANT) para reduzir os problemas oriundos das falhas em uma rede de sensores para detectar desastres naturais como enchentes e deslizamentos. Na solução proposta, o VANT pode ser transportado para o sítio do desastre para minimizar os problemas provenientes das falhas (por exemplo, para servir como um roteador ou até mesmo para servir como uma mula de dados e transmitir imagens em tempo real para equipes de resgate). Estudos foram conduzidos em um protótipo real, equipado com o UAV Brain (módulo computacional desenvolvido especificamente para este projeto), para uma análise exploratória do consumo energético do VANT e do rádio transmissor que equipa o VANT. Os resultados mostram que a melhor situação para o rádio comunicador se dá quando o VANT está no ar e com uma antena de maior ganho, e os fatores que mais influenciam no consumo energético do rádio são a altura do VANT e o tipo de antena utilizado. Além disso, tais resultados mostram também a viabilidade desta proposta em redes de sensores sem fio linear e esparsa. / The mitigation of natural disasters requires quick and reliable answers. In Brazil, the rainy season causes many flooding in urban areas and, to monitor this phenomenon, a wireless sensor network to monitor the water level of the citys rivers was installed in São Carlos-SP. However, this sensor network is susceptible to failures that may jeopardize the operation of the system, and the adoption of redundant mechanisms and 3G mobile networks may result in prohibitive costs to the monitoring of these rivers, and does not guarantee the normal operation of monitoring. This work presents an aerial vehicle-based solution unmanned (UAV) to reduce the problems originated from failures in a network of sensors to detect natural disasters such as floods and landslides. In the proposed solution, the UAV can be transported to the disaster site to minimize problems arising from failures (eg, to serve as a router or even to serve as a data mule and transmit images in real time for rescue teams). Studies were conducted in a real prototype, equipped with UAV Brain (computational module developed specifically for this project), for an exploratory analysis of the energy consumption UAV and radio transmitter fitted to the UAV. The results show that the best situation for the radio communicator is when the UAV is in the air and with a higher gain antenna, and the factors that most influence on the radio energy consumption are the height of the UAV and the type of antenna used. Furthermore, these results also show the feasibility of this proposal in linear and sparse wireless sensor networks.

This text presents the development of a four-degree-of-freedom (4DOF) quadcopter prototype that allows the vehicle to rotate around the three axes (yaw, pitch and roll) and linear movement along z-axis (altitude). The goal is to obtain a prototype bench that uses a good amount of components used in commercial quadcopters (sensors and actuators) and use it to apply attitude and altitude controllers, using techniques such as PID, LQR and Sliding-Mode. Starting from the system modeling, its specifications are shown followed by listing the components used, finishing with the development of the controllers and their simulations and applications. / Este texto apresenta o desenvolvimento de um protótipo de quadricóptero com quatro graus de liberdade (4DOF), o qual possibilita a rotação do veículo em torno dos três eixos (yaw, pitch e roll) e o deslocamento ao longo do eixo z (altitude). O objetivo é obter um protótipo de bancada que use a maior quantidade de componentes de um quadricóptero comercial (sensores e atuadores) e usá-lo para a aplicação de controladores de atitude e altitude, utilizando técnicas PID, LQR e Sliding-Mode. Partindo da modelagem do sistema, mostra-se as especificações do mesmo, os componentes utilizados e finaliza-se com o desenvolvimento dos controladores, simulação e aplicação deles.

Existe um número considerável de áreas utilizadas como pontos de descarte de resíduos de construção civil na cidade de Palmas – TO que extrapolam o alcance das ferramentas de controle e fiscalização do município, principalmente em pontos dentro do perímetro urbano. A presente pesquisa tem como objetivo principal verificar a aplicabilidade da utilização de imagens obtidas pelo veículo aéreo não tripulado (VANT), no auxílio da identificação dos resíduos e de pontos de descarte de resíduos de construção civil (RCC) em áreas irregulares da cidade. De posse do instrumento, foram tomadas como unidade amostral áreas de descarte preliminarmente mapeadas por meio de imagens de satélite com resoluções espaciais menos refinadas. Com metodologia que permitisse atestar a potencialidade dos produtos gerados em termos de fotointerpretação, precisões geométricas e geográficas, foram feitos sobrevoos com diferentes sobreposições de imageamento e com a utilização de pontos de controle coletados por meio de GPS de precisão. Os resultados encontrados mostram que as imagens aéreas obtidas e os ortomosaicos gerados podem auxiliar de forma confiável, rápida, segura e com melhores informações na identificação de pontos de lançamento de RCC, atestando que as plataformas VANTs e os sensores passíveis de serem acoplados à elas podem servir adequadamente como tecnologia para sensoriamento remoto, como ênfase no estudo proposto. / There are a considerable number of areas used as waste disposal points for construction in the city of Palmas - TO, which extrapolate the reach of the control and inspection tools of the municipality, especially in points within the urban perimeter. The present research has as main objective to verify the applicability of the use of images obtained by the unmanned aerial vehicle (UAV), in the aid of the identification of the residues and points of disposal of construction waste (RCC) in irregular areas of the city. Once the instrument was in possession, preliminary sampling areas were mapped using satellite images with less refined spatial resolution. With a methodology that allowed to attest to the potential of the products generated in terms of photointerpretation, geometric and geographic precisions, overflight with different overlays of imaging and with the use of control points collected through precision GPS were made. The results obtained show that the aerial images obtained and the generated ortomosaic can help in a reliable, fast, safe and with better information in the identification of points of launch of RCC, attesting that the platforms VANTs and the sensors that can be coupled to them can Adequately serve as a technology for remote sensing, as an emphasis on the proposed study.

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This text presents the development of a four-degree-of-freedom (4DOF) quadcopter prototype that allows the vehicle to rotate around the three axes (yaw, pitch and roll) and linear movement along z-axis (altitude). The goal is to obtain a prototype bench that uses a good amount of components used in commercial quadcopters (sensors and actuators) and use it to apply attitude and altitude controllers, using techniques such as PID, LQR and Sliding-Mode. Starting from the system modeling, its specifications are shown followed by listing the components used, finishing with the development of the controllers and their simulations and applications. / Este texto apresenta o desenvolvimento de um protótipo de quadricóptero com quatro graus de liberdade (4DOF), o qual possibilita a rotação do veículo em torno dos três eixos (yaw, pitch e roll) e o deslocamento ao longo do eixo z (altitude). O objetivo é obter um protótipo de bancada que use a maior quantidade de componentes de um quadricóptero comercial (sensores e atuadores) e usá-lo para a aplicação de controladores de atitude e altitude, utilizando técnicas PID, LQR e Sliding-Mode. Partindo da modelagem do sistema, mostra-se as especificações do mesmo, os componentes utilizados e finaliza-se com o desenvolvimento dos controladores, simulação e aplicação deles.

Doctor of Philosophy / Genetics Interdepartmental Program / Jesse A. Poland / A central question in modern biology is to understand the genotype-to-phenotype (G2P) link, that is, how the genetics of an organism results in specific characteristics. However, prediction of phenotypes from genotypes is a difficult problem due to the complex nature of genomes, the environment, and their interactions. While the recent advancements in genome sequencing technologies have provided almost unlimited access to high-density genetic markers, large-scale rapid and accurate phenotyping of complex plant traits remains a major bottleneck. Here, we demonstrate field-based complex trait assessment approaches using a commercially available light-weight Unmanned Aerial Systems (UAS). By deploying novel data acquisition and processing pipelines, we quantified lodging, ground cover, and crop growth rate of 1745 advanced spring wheat lines at multiple time-points over the course of three field seasons at three field sites in South Asia. High correlations of digital measures to visual estimates and superior broad-sense heritability demonstrate these approaches are amenable for reproducible assessment of complex plant traits in large breeding nurseries. Using these validated high-throughput measurements, we applied genome-wide association and prediction models to assess the underlying genetic architecture and genetic control. Our results suggest a diffuse genetic architecture for lodging and ground cover in wheat, but heritable genetic variation for prediction and selection in breeding programs. The logistic regression-derived parameters of dynamic plant height exhibited strong physiological linkages with several developmental and agronomic traits, suggesting the potential targets of selection and the associated tradeoffs. Taken together, our highly reproducible approaches provide a proof-of-concept application of UAS-based phenomics that is scalable to tens-of-thousands of plots in breeding and genetic studies as will be needed to understand the G2P and increase the rate of gain for complex traits in crop breeding.

Unmanned aerial systems (UASs) often require multiple human operators fulfilling diverse roles for safe and correct operation. Reliably designing the human interaction, autonomy, and decision making aspects of these systems requires the use of modeling. We propose a conceptual model that models human machine interaction systems as a group of actors connected by a network of communication channels. We present a simulation framework implemented in Java, with an optional XML model parser that can be analyzed using the Java Pathfinder (JPF) model checker. We propose two human workload metrics based on a taxonomy extracted from the relevant literature. Using the simulator to produce a workload profile over time for each human actor, we conducted a case study by modeling a UAS integrated into the National Airspace System. Additionally we adapted an existing cognitive workload metric to act as a baseline. The results of this case study were consistent with known workload events and the results of our baseline metric.

Precision agriculture requires detailed and timely information about field condition. In less than the short flight time a UAV (Unmanned Aerial Vehicle) can provide, an entire field can be scanned at the highest allowed altitude. The resulting NDVI (Normalized Difference Vegetation Index) imagery can then be used to classify each point in the field using a FIS (Fuzzy Inference System). This identifies areas that are expected to be similar, but only closer inspection can quantify and diagnose crop properties. In the remaining flight time, the goal is to scout a set of representative points maximizing the quality of actionable information about the field condition. This quality is defined by two new metrics: the average sampling probability (ASP) and the total scouting luminance (TSL). In simulations, the scouting flight plan created using a GA (Genetic Algorithm) significantly outperformed plans created by grid sampling or human experts, obtaining over 99% ASP while improving TSL by an average of 285%.

<p>A control system for autonomous landing of an unmanned aerial vehicle (UAV)with high precision has been developed. The UAV is a medium sized model he-licopter. Measurements from a GPS, a camera and a compass are fused with anextended Kalman filter for state estimation of the helicopter. Four PID-controllers,one for each control signal of the helicopter, are used for the helicopter control.During the final test flights fifteen landings were performed with an average land-ing accuracy of 35 cm.    A bias in the GPS measurements makes it impossible to land the helicopter withhigh precision using only the GPS. Therefore, a vision system using a camera anda pattern provided landing platform has been developed. The vision system givesaccurate measurement of the 6-DOF pose of the helicopter relative the platform.These measurements are used to guide the helicopter to the landing target. Inorder to use the vision system in real time, fast image processing algorithms havebeen developed. The vision system can easily match up the with the camera framerate of 30 Hz.</p> / <p>Ett kontrolsystem för att autonomt landa en modellhelikopter har utvecklats.Mätdata från en GPS, en kamera samt en kompass fusioneras med ett Extend-ed Kalman Filter för tillståndsestimering av helikoptern. Fyra PID-regulatorer,en för varje kontrolsignal på helikoptern, har används för regleringen. Under densista provflygningen gjordes tre landingar av vilken den minst lyckade slutade35 cm från målet.    På grund av en drift i GPS-mätningarna är det omöjligt att landa helikopternmed hög precision med bara en GPS. Därför har ett bildbehandlingssystem som an-vänder en kamera samt ett mönster på platformen utvecklats. Bidbehandlingssys-temet mäter positionen och orienteringen av helikoptern relativt platformen. Dessamätningar används kompensera för GPS-mätningarnas drift. Snabba bildbehan-dlingsalgoritmer har utvecklats för att kunna använda bildbehandlingssystemet irealtid. Systemet är mycket snabbare än 30 bilder per sekund vilket är kameranshastighet.</p>

A control system for autonomous landing of an unmanned aerial vehicle (UAV)with high precision has been developed. The UAV is a medium sized model he-licopter. Measurements from a GPS, a camera and a compass are fused with anextended Kalman filter for state estimation of the helicopter. Four PID-controllers,one for each control signal of the helicopter, are used for the helicopter control.During the final test flights fifteen landings were performed with an average land-ing accuracy of 35 cm.    A bias in the GPS measurements makes it impossible to land the helicopter withhigh precision using only the GPS. Therefore, a vision system using a camera anda pattern provided landing platform has been developed. The vision system givesaccurate measurement of the 6-DOF pose of the helicopter relative the platform.These measurements are used to guide the helicopter to the landing target. Inorder to use the vision system in real time, fast image processing algorithms havebeen developed. The vision system can easily match up the with the camera framerate of 30 Hz. / Ett kontrolsystem för att autonomt landa en modellhelikopter har utvecklats.Mätdata från en GPS, en kamera samt en kompass fusioneras med ett Extend-ed Kalman Filter för tillståndsestimering av helikoptern. Fyra PID-regulatorer,en för varje kontrolsignal på helikoptern, har används för regleringen. Under densista provflygningen gjordes tre landingar av vilken den minst lyckade slutade35 cm från målet.    På grund av en drift i GPS-mätningarna är det omöjligt att landa helikopternmed hög precision med bara en GPS. Därför har ett bildbehandlingssystem som an-vänder en kamera samt ett mönster på platformen utvecklats. Bidbehandlingssys-temet mäter positionen och orienteringen av helikoptern relativt platformen. Dessamätningar används kompensera för GPS-mätningarnas drift. Snabba bildbehan-dlingsalgoritmer har utvecklats för att kunna använda bildbehandlingssystemet irealtid. Systemet är mycket snabbare än 30 bilder per sekund vilket är kameranshastighet.