Pianificazione di coperture fotogrammetriche mediante RPAS

Il seguente elaborato di tesi tratta il problema della pianificazione di voli fotogrammetrici a bassa quota mediante l’uso di SAPR, in particolare è presentata una disamina delle principali applicazioni che permettono di programmare una copertura fotogrammetrica trasversale e longitudinale di un certo poligono con un drone commerciale. Il tema principale sviluppato è la gestione di un volo fotogrammetrico UAV mediante l’uso di applicativi software che permettono all’utente di inserire i parametri di volo in base alla tipologia di rilievo che vuole effettuare. L’obbiettivo finale è quello di ottenere una corretta presa fotogrammetrica da utilizzare per la creazione di un modello digitale del terreno o di un oggetto attraverso elaborazione dati in post-processing. La perfetta configurazione del volo non può prescindere dalle conoscenze base di fotogrammetria e delle meccaniche di un veicolo UAV. I capitoli introduttivi tratteranno infatti i principi della fotogrammetria analogica e digitale soffermandosi su temi utili alla comprensione delle problematiche relative al progetto di rilievo fotogrammetrico aereo. Una particolare attenzione è stata posta sulle nozioni di fotogrammetria digitale che, insieme agli algoritmi di Imagine Matching derivanti dalla Computer Vision, permette di definire il ramo della Fotogrammetria Moderna. Nei capitoli centrali verranno esaminate e confrontate una serie di applicazioni commerciali per smartphone e tablet, disponibili per sistemi Apple e Android, per trarne un breve resoconto conclusivo che le compari in termini di accessibilità, potenzialità e destinazione d’uso. Per una maggiore comprensione si determinano univocamente gli acronimi con cui i droni vengono chiamati nei diversi contesti: UAV (Unmanned Aerial Vehicle), SAPR (Sistemi Aeromobili a Pilotaggio Remoto), RPAS (Remotely Piloted Aicraft System), ARP (Aeromobili a Pilotaggio Remoto).

Evaluation of vegetation recovery after fire: a case study in Calde, central region of Portugal

Remote Sensing has been used for decades, and more and more applications are added to its repertoire. With this study we aim to show the use of Remote Sensing in the field of vegetation recovery monitoring in burned areas and the added value of data with a high spatial resolution. This was done by analysing both Landsat 7 and 8 scenes, after the forest fire of summer 2012 in the parish of Calde, in the central region of Portugal, as well as an orthophoto produced with images acquired by an unmanned aerial vehicle.

Implementação em FPGA de um Modem QPSK

Esta dissertação insere-se num conjunto de trabalhos a decorrer no Instituto de Telecomunicações de Aveiro que tem como objetivo o desenvolvimento de um sistema de comunicação para um UAV. Neste sentido, apresenta a implementação e validação de um modem em banda base aberto e flexível implementado em FPGA, baseado em abordagem SDR, com possibilidade de integraçãoo no sistema de comunicação com o UAV. Ao longo desta dissertação implementou-se, utilizando o MATLAB, um modem de modulação adaptável, ao qual foram integrados algoritmos de sincronismo e de correção de fase. Desta forma, foi possível realizar uma análise ao modelo comportamental dos vários constituintes do modem abstraindose dos tempos de atraso do processamento ou da precisão da representação dos dados, e assim simplificar a sua implementação em hardware. Analisado o modelo comportamental do modem desenvolvido em MATLAB realizou-se a sua implementação em hardware para a modulação QPSK. A sua prototipagem foi realizada, com recurso à ferramenta computacional Vivado Design Suite 2014.2, utilizando o kit de desenvolvimento ZedBoard e o frontend AD-FMCOMMS1-EBZ. O correto funcionamento dos módulos implementados em hardware foi posteriormente avaliado através de uma interface entre o MATLAB e a Zed- Board, sendo que, os resultados obtidos no modelo em MATLAB serviram como termo de comparação. Através da utilização desta interface é possível validar parte do modem implementado em FPGA, mantendo o restante processamento a ser realizado em MATLAB, validando assim os módulos em FPGA de uma forma isolada.

DESIGN, FABRICATION, AND PERFORMANCE CHARACTERIZATION OF MULTIFUNCTIONAL STRUCTURES TO HARVEST SOLAR ENERGY FOR FLAPPING WING AERIAL VEHICLES

Flapping Wing Aerial Vehicles (FWAVs) have the capability to combine the benefits of both fixed wing vehicles and rotary vehicles. However, flight time is limited due to limited on-board energy storage capacity. For most Unmanned Aerial Vehicle (UAV) operators, frequent recharging of the batteries is not ideal due to lack of nearby electrical outlets. This imposes serious limitations on FWAV flights. The approach taken to extend the flight time of UAVs was to integrate photovoltaic solar cells onto different structures of the vehicle to harvest and use energy from the sun. Integration of the solar cells can greatly improve the energy capacity of an UAV; however, this integration does effect the performance of the UAV and especially FWAVs. The integration of solar cells affects the ability of the vehicle to produce the aerodynamic forces necessary to maintain flight. This PhD dissertation characterizes the effects of solar cell integration on the performance of a FWAV. Robo Raven, a recently developed FWAV, is used as the platform for this work. An additive manufacturing technique was developed to integrate photovoltaic solar cells into the wing and tail structures of the vehicle. An approach to characterizing the effects of solar cell integration to the wings, tail, and body of the UAV is also described. This approach includes measurement of aerodynamic forces generated by the vehicle and measurements of the wing shape during the flapping cycle using Digital Image Correlation. Various changes to wing, body, and tail design are investigated and changes in performance for each design are measured. The electrical performance from the solar cells is also characterized. A new multifunctional performance model was formulated that describes how integration of solar cells influences the flight performance. Aerodynamic models were developed to describe effects of solar cell integration force production and performance of the FWAV. Thus, performance changes can be predicted depending on changes in design. Sensing capabilities of the solar cells were also discovered and correlated to the deformation of the wing. This demonstrated that the solar cells were capable of: (1) Lightweight and flexible structure to generate aerodynamic forces, (2) Energy harvesting to extend operational time and autonomy, (3) Sensing of an aerodynamic force associated with wing deformation. Finally, different flexible photovoltaic materials with higher efficiencies are investigated, which enable the multifunctional wings to provide enough solar power to keep the FWAV aloft without batteries as long as there is enough sunlight to power the vehicle.

Development of a Real-Time Hierarchical 3D Path Planning Algorithm for Unmanned Aerial Vehicles

Unmanned aerial vehicles (UAVs) frequently operate in partially or entirely unknown environments. As the vehicle traverses the environment and detects new obstacles, rapid path replanning is essential to avoid collisions. This thesis presents a new algorithm called Hierarchical D* Lite (HD*), which combines the incremental algorithm D* Lite with a novel hierarchical path planning approach to replan paths sufficiently fast for real-time operation. Unlike current hierarchical planning algorithms, HD* does not require map corrections before planning a new path. Directional cost scale factors, path smoothing, and Catmull-Rom splines are used to ensure the resulting paths are feasible. HD* sacrifices optimality for real-time performance. Its computation time and path quality are dependent on the map size, obstacle density, sensor range, and any restrictions on planning time. For the most complex scenarios tested, HD* found paths within 10% of optimal in under 35 milliseconds.

RISK-BASED MULTIOBJECTIVE PATH PLANNING AND DESIGN OPTIMIZATION FOR UNMANNED AERIAL VEHICLES

Safe operation of unmanned aerial vehicles (UAVs) over populated areas requires reducing the risk posed by a UAV if it crashed during its operation. We considered several types of UAV risk-based path planning problems and developed techniques for estimating the risk to third parties on the ground. The path planning problem requires making trade-offs between risk and flight time. Four optimization approaches for solving the problem were tested; a network-based approach that used a greedy algorithm to improve the original solution generated the best solutions with the least computational effort. Additionally, an approach for solving a combined design and path planning problems was developed and tested. This approach was extended to solve robust risk-based path planning problem in which uncertainty about wind conditions would affect the risk posed by a UAV.

Motion Planning and Controls with Safety and Temporal Constraints

Motion planning, or trajectory planning, commonly refers to a process of converting high-level task specifications into low-level control commands that can be executed on the system of interest. For different applications, the system will be different. It can be an autonomous vehicle, an Unmanned Aerial Vehicle(UAV), a humanoid robot, or an industrial robotic arm. As human machine interaction is essential in many of these systems, safety is fundamental and crucial. Many of the applications also involve performing a task in an optimal manner within a given time constraint. Therefore, in this thesis, we focus on two aspects of the motion planning problem. One is the verification and synthesis of the safe controls for autonomous ground and air vehicles in collision avoidance scenarios. The other part focuses on the high-level planning for the autonomous vehicles with the timed temporal constraints. In the first aspect of our work, we first propose a verification method to prove the safety and robustness of a path planner and the path following controls based on reachable sets. We demonstrate the method on quadrotor and automobile applications. Secondly, we propose a reachable set based collision avoidance algorithm for UAVs. Instead of the traditional approaches of collision avoidance between trajectories, we propose a collision avoidance scheme based on reachable sets and tubes. We then formulate the problem as a convex optimization problem seeking control set design for the aircraft to avoid collision. We apply our approach to collision avoidance scenarios of quadrotors and fixed-wing aircraft. In the second aspect of our work, we address the high level planning problems with timed temporal logic constraints. Firstly, we present an optimization based method for path planning of a mobile robot subject to timed temporal constraints, in a dynamic environment. Temporal logic (TL) can address very complex task specifications such as safety, coverage, motion sequencing etc. We use metric temporal logic (MTL) to encode the task specifications with timing constraints. We then translate the MTL formulae into mixed integer linear constraints and solve the associated optimization problem using a mixed integer linear program solver. We have applied our approach on several case studies in complex dynamical environments subjected to timed temporal specifications. Secondly, we also present a timed automaton based method for planning under the given timed temporal logic specifications. We use metric interval temporal logic (MITL), a member of the MTL family, to represent the task specification, and provide a constructive way to generate a timed automaton and methods to look for accepting runs on the automaton to find an optimal motion (or path) sequence for the robot to complete the task.

Desarrollo de un sistema para supervisión de pastoreo

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Mission and Scenario Planning for Unmanned Aerial Vehicles (Path Planning and Collision Avoidance Systems)

As unmanned autonomous vehicles (UAVs) are being widely utilized in military and civil applications, concerns are growing about mission safety and how to integrate dierent phases of mission design. One important barrier to a coste ective and timely safety certication process for UAVs is the lack of a systematic approach for bridging the gap between understanding high-level commander/pilot intent and implementation of intent through low-level UAV behaviors. In this thesis we demonstrate an entire systems design process for a representative UAV mission, beginning from an operational concept and requirements and ending with a simulation framework for segments of the mission design, such as path planning and decision making in collision avoidance. In this thesis, we divided this complex system into sub-systems; path planning, collision detection and collision avoidance. We then developed software modules for each sub-system

As ruturas epistemológicas na cultura aeronáutica resultantes da emergência da guerra aérea remota

A evolução tecnológica e a necessidade operacional de Unmanned Aircraft Systems (UAS) ditarão, a curto trecho, a sua expansão funcional à quase totalidade das áreas de missão tipicamente reservadas às plataformas tripuladas. Talvez a maior barreira à adoção dos UAS de forma plena, pela United States Air Force (USAF) em particular, e por extensão a outras Forças Aéreas que partilhem de valores semelhantes, será a alteração da cultura organizacional, no sentido de promover a aceitação dos sistemas não tripulados como capacidades idênticas às providenciadas pelas aeronaves tripuladas. Este artigo pretende explorar algumas das forças dissociativas que resistem à integração dos UAS na estrutura de força de uma instituição, tomando como exemplo a USAF enquanto maior utilizadora destes sistemas e influenciadora das tendências futuras do Poder Aéreo. Para melhor percebermos os desafios culturais que despontam do emprego em larga escala de UAS de combate, teremos de percorrer o processo de independência da USAF e a validação estratégica do Poder Aéreo enquanto instrumento militar preferencial

Validação Computacional tendo em vista a Interoperabilidade entre os Veículos Aéreos Não Tripulados

Nos dias de hoje, com o contínuo desenvolvimento e inovação no campo dos UAVs (Unmanned Aerial Vehciles), o mundo já tem como adquiridos os benefícios que estes sistemas podem fornecer. Os benefícios obtidos com a aplicação destes sistemas abrange tanto as forças armadas como industrias e organizações civis. Todas as nações e indústrias querem ter uma cota parte no futuro desta tecnologia. Diferentes UAVs foram desenvolvidos, mas estes, diferem em termos de arquitetura e protocolos de comunicação. Protocolos como o STANAG 4586, MAVLink, JAUS e ROS são só alguns exemplos. A proliferação de informação através destes sistemas e as suas consolas de comando e controlo é uma das principais preocupações, principalmente pelas forças armadas. Uma das principais prioridades é combinar forças de diferentes nações, principalmente pelos membros NATO. A necessidade de uma consola para cada tipo de sistema devido à falta de padronização apresenta assim um problema. É conhecida a necessidade de uma padronização em termos de arquitetura por camadas e de comunicação tendo em vista a interoperabilidade entre estes sistemas. Não existe nenhuma que esteja a ser implementada como documento padrão. Pretende-se que o STANAG 4586 seja o documento padrão para os membros NATO e, por conseguinte, todos os esforços estão direcionados em desenvolver sistemas que o consigam implementar. Os diferentes UAVs já existentes possuem o seu próprio protocolo de comunicação e a alteração de toda a sua estrutura não é fácil. A ideia de fazer uma conversão de linguagens como alternativa surge como uma solução teórica ótima. Utilizando um piloto automático que comunica com a sua consola através da linguagem MAVLink esta dissertação tem como objetivo desenvolver um programa computacional que converta as mensagens MAVLink em STANAG 4586 e estudar se o tempo de conversão é operacionalmente válido tendo em conta os requisitos operacionais dos sistemas.

POSE ESTIMATION AND 3D RECONSTRUCTION USING SENSOR FUSION

A camera maps 3-dimensional (3D) world space to a 2-dimensional (2D) image space. In the process it loses the depth information, i.e., the distance from the camera focal point to the imaged objects. It is impossible to recover this information from a single image. However, by using two or more images from different viewing angles this information can be recovered, which in turn can be used to obtain the pose (position and orientation) of the camera. Using this pose, a 3D reconstruction of imaged objects in the world can be computed. Numerous algorithms have been proposed and implemented to solve the above problem; these algorithms are commonly called Structure from Motion (SfM). State-of-the-art SfM techniques have been shown to give promising results. However, unlike a Global Positioning System (GPS) or an Inertial Measurement Unit (IMU) which directly give the position and orientation respectively, the camera system estimates it after implementing SfM as mentioned above. This makes the pose obtained from a camera highly sensitive to the images captured and other effects, such as low lighting conditions, poor focus or improper viewing angles. In some applications, for example, an Unmanned Aerial Vehicle (UAV) inspecting a bridge or a robot mapping an environment using Simultaneous Localization and Mapping (SLAM), it is often difficult to capture images with ideal conditions. This report examines the use of SfM methods in such applications and the role of combining multiple sensors, viz., sensor fusion, to achieve more accurate and usable position and reconstruction information. This project investigates the role of sensor fusion in accurately estimating the pose of a camera for the application of 3D reconstruction of a scene. The first set of experiments is conducted in a motion capture room. These results are assumed as ground truth in order to evaluate the strengths and weaknesses of each sensor and to map their coordinate systems. Then a number of scenarios are targeted where SfM fails. The pose estimates obtained from SfM are replaced by those obtained from other sensors and the 3D reconstruction is completed. Quantitative and qualitative comparisons are made between the 3D reconstruction obtained by using only a camera versus that obtained by using the camera along with a LIDAR and/or an IMU. Additionally, the project also works towards the performance issue faced while handling large data sets of high-resolution images by implementing the system on the Superior high performance computing cluster at Michigan Technological University.

Adaptive Sampling with Mobile Sensor Networks

Mobile sensor networks have unique advantages compared with wireless sensor networks. The mobility enables mobile sensors to flexibly reconfigure themselves to meet sensing requirements. In this dissertation, an adaptive sampling method for mobile sensor networks is presented. Based on the consideration of sensing resource constraints, computing abilities, and onboard energy limitations, the adaptive sampling method follows a down sampling scheme, which could reduce the total number of measurements, and lower sampling cost. Compressive sensing is a recently developed down sampling method, using a small number of randomly distributed measurements for signal reconstruction. However, original signals cannot be reconstructed using condensed measurements, as addressed by Shannon Sampling Theory. Measurements have to be processed under a sparse domain, and convex optimization methods should be applied to reconstruct original signals. Restricted isometry property would guarantee signals can be recovered with little information loss. While compressive sensing could effectively lower sampling cost, signal reconstruction is still a great research challenge. Compressive sensing always collects random measurements, whose information amount cannot be determined in prior. If each measurement is optimized as the most informative measurement, the reconstruction performance can perform much better. Based on the above consideration, this dissertation is focusing on an adaptive sampling approach, which could find the most informative measurements in unknown environments and reconstruct original signals. With mobile sensors, measurements are collect sequentially, giving the chance to uniquely optimize each of them. When mobile sensors are about to collect a new measurement from the surrounding environments, existing information is shared among networked sensors so that each sensor would have a global view of the entire environment. Shared information is analyzed under Haar Wavelet domain, under which most nature signals appear sparse, to infer a model of the environments. The most informative measurements can be determined by optimizing model parameters. As a result, all the measurements collected by the mobile sensor network are the most informative measurements given existing information, and a perfect reconstruction would be expected. To present the adaptive sampling method, a series of research issues will be addressed, including measurement evaluation and collection, mobile network establishment, data fusion, sensor motion, signal reconstruction, etc. Two dimensional scalar field will be reconstructed using the method proposed. Both single mobile sensors and mobile sensor networks will be deployed in the environment, and reconstruction performance of both will be compared.In addition, a particular mobile sensor, a quadrotor UAV is developed, so that the adaptive sampling method can be used in three dimensional scenarios.

Unmanned Aerial Vehicle: tecnologie e prospettive future

Partendo dalla definizione di UAV e UAS, arrivando a quella di drone, nella tesi saranno definiti i termini precedenti, ossia un sistema aereo senza pilota a bordo, la nascita del termine drone e le tendenze attuali. Dopo una precisa classificazione nelle quattro categorie principali (droni per hobbisti, commerciali e militari di me- dia grandezza, militari specifici di grandi dimensioni e stealth da combattimento) saranno descritti gli ambiti di utilizzo: da un lato quello militare e della sicurezza, dall’altro quello civile e scientifico. I capitoli centrali della tesi saranno il cuore dell’opera: l’architettura dell’UAV sarà descritta analizzando la totalità delle sue componenti, sia hardware che software. Verranno, quindi, analizzati i problemi relativi alla sicurezza, focalizzandosi sull’hacking di un UAV, illustrandone le varie tecniche e contromisure (tra cui anche come nascondersi da un drone). Il lavoro della tesi prosegue nei capitoli successivi con un’attenta trattazione della normativa vigente e dell’etica dei droni (nonché del diritto ad uccidere con tali sistemi). Il capitolo relativo alla tecnologia stealth sarà importante per capire le modalità di occultamento, le tendenze attuali e i possibili sviluppi futuri degli UAV militari da combattimento. Il capitolo finale sugli sviluppi futuri esporrà le migliorie tecnologiche e gli obiettivi degli UAV negli anni a venire, insieme ad eventuali utilizzi sia militari che civili. La ricerca sarà orientata verso sistemi miniaturizzati, multiple UAV e swarming.

The role of agriculture and food consumption in tropical conservation

A growing human population, shifting human dietary habits, and climate change are negatively affecting global ecosystems on a massive scale. Expanding agricultural areas to feed a growing population drives extensive habitat loss, and climate change compounds stresses on both food security and ecosystems. Understanding the negative effects of human diet and climate change on agricultural and natural ecosystems provides a context within which potential technological and behavioral solutions can be proposed to help maximize conservation. The purpose of this research was to (1) examine the potential effects of climate change on the suitability of areas for commercial banana plantations in Latin America in the 2050s and how shifts in growing areas could affect protected areas; (2) test the ability of small unmanned aerial vehicles (UAVs) to map productivity of banana plantations as a potential tool for increasing yields and decreasing future plantation expansions; (3) project the effects on biodiversity of increasing rates of animal product consumption in developing megadiverse countries; and (4) estimate the capacity of global pasture biomass production and Fischer-Tropsch hydrocarbon synthesis (IGCC-FT) processing to meet electricity, gasoline and diesel needs. The results indicate that (1) the overall extent of areas suitable for conventional banana cultivation is predicted to decrease by 19% by 2050 because of a hotter and drier climate, but all current banana exporting countries are predicted to maintain some suitable areas with no effects on protected areas; (2) Spatial patterns of NDVI and ENDVI were significantly positively correlated with several metrics of fruit yield and quality, indicating that UAV systems can be used in banana plantations to map spatial patterns of fruit yield; (3) Livestock production is the single largest driver of habitat loss, and both livestock and feedstock production are increasing in developing biodiverse tropical countries. Reducing global animal product consumption should therefore be at the forefront of strategies aimed at reducing biodiversity loss; (4) Removing livestock from global pasture lands and instead utilizing the biomass production could produce enough energy to meet 100% of the electricity, gasoline, and diesel needs of over 40 countries with extensive grassland ecosystems, primarily in tropical developing countries.^