Inflatable-wing Unmanned Aerial Vehicles (UAVs) have the ability to be packed in a fraction of their deployed volume. This makes them ideal for many deployable UAV designs, but inflatable wings can be flexible and don’t have conventional control surfaces. This thesis will investigate the use of wing warping as a means of autonomous control for inflatable wings. Due to complexities associated with manufacturing inflatable structures a new method of rapid prototyping deformable wings is used in place of inflatables to decrease cost and design-cycle time. A UAV testbed was developed and integrated with the warping wings and flown in a series of flight tests. The warping wing flew both under manual control and autopilot stabilization.

The past few decades have witnessed a growing interest in the engineering communities to approach the handling of imperfect information from a quantitatively justifiable angle. In the aerospace engineering domain, the movement to develop creative avenues to nondeterministically solving engineering problems has emerged in the field of aerospace systems design. Inspired by statistical data modeling and numerical analysis techniques that used to be relatively foreign to the designers of aerospace systems, a variety of strategies leveraging upon the probabilistic treatment of uncertainty has been, and continue to be, reported. Although each method differs in the sequence in which probabilistic analysis and numerical optimization are performed, a common motif in all of them is the lack of any built-in provisions to compensate for infeasibilities that occur during optimization. Constraint violations are either strictly prohibited or striven to be held to an acceptable probability threshold, implying that most hitherto developed probabilistic design methods promote an avoid-failure approach to developing aerospace systems under uncertainty. It is the premise of this dissertation that such a dichotomous structure of addressing imperfections is hardly a realistic model of how product development unfolds in practice. From a time-phased view of engineering design, it is often observed that previously unknown parameters become known with the passing of each design milestone, and their effects on the system are realized. Should these impacts happen to be detrimental to critical system-level metrics, then a compensatory action is taken to remedy any unwanted deviations from the target or required bounds, rather than starting the process completely anew. Anecdotal accounts of numerous real-world design projects confirm that such remedial actions are commonly practiced means to ensure the successful fielding of aerospace systems. Therefore, formalizing the remedial aspect of engineering design into a new methodological capability would be the next logical step towards making uncertainty handling more pragmatic for this generation of engineers. In order to formulate a nondeterministic solution approach that capitalizes on the practice of compensatory design, this research introduces the notion of recourse. Within the context of engineering an aerospace system, recourse is defined as a set of corrective actions that can be implemented in stages later than the current design phase to keep critical system-level figures of merit within the desired target ranges, albeit at some penalty. The terminology is inspired by the concept of the same name in the field of statistical decision analysis, where it refers to an action taken by a decision maker to mitigate the unfavorable consequences caused by uncertainty realizations. Recourse programs also introduce the concept of stages to optimization formulations, and allow each stage to encompass as many sequences or events as determined necessary to solve the problem at hand. Together, these two major premises of classical stochastic programming provide a natural way to embody not only the remedial, but also the temporal and nondeterministic aspects of aerospace systems design. A two-part strategy, which partitions the design activities into stages, is proposed to model the bi-phasal nature of recourse. The first stage is defined as the time period in which an a priori design is identified before the exact values of the uncertain parameters are known. In contrast, the second stage is a period occurring some time after the first stage, when an a posteriori correction can be made to the first-stage design, should the realization of uncertainties impart infeasibilities. Penalizing costs are attached to the second-stage corrections to reflect the reality that getting it done right the first time is almost always less costly than fixing it after the fact. Consequently, the goal of the second stage becomes identifying an optimal solution with respect to the second-stage penalty, given the first-stage design, as well as a particular realization of the random parameters. This two-stage model is intended as an analogue of the traditional practice of monitoring and managing key Technical Performance Measures (TPMs) in aerospace systems development settings. Whenever an alarmingly significant discrepancy between the demonstrated and target TPM values is noted, it is generally the case that the most cost-effective recourse option is selected, given the available resources at the time, as well as scheduling and budget constraints. One obvious weakness of the two-stage strategy as presented above is its limited applicability as a forecasting tool. Not only cannot the second stage be invoked without a first-stage starting point, but also the second-stage solution differs from one specific outcome of uncertainties to another. On the contrary, what would be more valuable given the time-phased nature of engineering design is the capability to perform an anticipatory identification of an optimum that is also expected to incur the least costly recourse option in the future. It is argued that such a solution is in fact a more balanced alternative than robust, probabilistically maximized, or chance-constrained solutions, because it represents trading the design optimality in the present with the potential costs of future recourse. Therefore, it is further proposed that the original two-stage model be embedded inside a larger design loop, so that the realization of numerous recourse scenarios can be simulated for a given first-stage design. The repetitive procedure at the second stage is necessary for computing the expected cost of recourse, which is equivalent to its mathematical expectation as per the strong law of large numbers. The feedback loop then communicates this information to the aggregate-level optimizer, whose objective is to minimize the sum total of the first-stage metric and the expected cost of future corrective actions. The resulting stochastic solution is a design that is well-hedged against the uncertain consequences of later design phases, while at the same time being less conservative than a solution designed to more traditional deterministic standards. As a proof-of-concept demonstration, the recourse-based solution approach is presented as applied to a contemporary aerospace engineering problem of interest - the integration of fuel cell technology into uninhabited aerial systems. The creation of a simulation environment capable of designing three system alternatives based on Proton Exchange Membrane Fuel Cell (PEMFC) technology and another three systems leveraging upon Solid Oxide Fuel Cell (SOFC) technology is presented as the means to notionally emulate the development process of this revolutionary aeropropulsion method. Notable findings from the deterministic trade studies and algorithmic investigation include the incompatibility of the SOFC based architectures with the conceived maritime border patrol mission, as well as the thermodynamic scalability of the PEMFC based alternatives. It is the latter finding which justifies the usage of the more practical specific-parameter based approach in synthesizing the design results at the propulsion level into the overall aircraft sizing framework. The ensuing presentation on the stochastic portion of the implementation outlines how the selective applications of certain Design of Experiments, constrained optimization, Surrogate Modeling, and Monte Carlo sampling techniques enable the visualization of the objective function space. The particular formulations of the design stages, recourse, and uncertainties proposed in this research are shown to result in solutions that are well compromised between unfounded optimism and unwarranted conservatism. In all stochastic optimization cases, the Value of Stochastic Solution (VSS) proves to be an intuitively appealing measure of accounting for recourse-causing uncertainties in an aerospace systems design environment.

Thesis (MScEng)--Stellenbosch University, 2013. / ENGLISH ABSTRACT: This project concerns motion planning for a rotary wing UAV, where vehicle controllers are already in place, and map data is readily available to a collision detection module. In broad terms, the goal of the motion planning algorithm is to provide a safe (i.e. obstacle free) flight path between an initial- and goal waypoint. This project looks at two specific motion planning algorithms, the Rapidly Exploring Random Tree (or RRT*), and the Probabilistic Roadmap Method (or PRM). The primary focus of this project is learning how these algorithms behave in specific environments and an in depth analysis is done on their differences. A secondary focus is the execution of planned paths via a Simulink simulation and lastly, this project also looks at the effect of path replanning. The work done in this project enables a rotary wing UAV to autonomously navigate an uncertain, dynamic and cluttered environment. The work also provides insight into the choice of an algorithm for a given environment: knowing which algorithm performs better can save valuable processing time and will make the entire system more responsive. / AFRIKAANSE OPSOMMING: ’n Tipiese vliegstuuroutomaat is daartoe in staat om ’n onbemande lugvaartvoertuig (UAV) so te stuur dat ’n stel gedefinieerde punte gevolg word. Die punte moet egter vooraf beplan word, en indien enige verandering nodig is (bv. as gevolg van veranderinge in die omgewing) is dit nodig dat ’n menslike operateur betrokke moet raak. Vir voertuie om ten volle outonoom te kan navigeer, moet die voertuig in staat wees om te kan reageer op veranderende situasies. Vir hierdie doel word kinodinamiese beplanningsalgoritmes en konflikdeteksiemetodes gebruik. Hierdie projek behels kinodinamiese beplanningsalgoritmes vir ’n onbemande helikopter, waar die beheerders vir die voertuig reeds in plek is, en omgewingsdata beskikbaar is vir ’n konflikdeteksie-module. In breë terme is die doel van die kinodinamiese beplanningsalgoritme om ’n veilige (d.w.s ’n konflikvrye) vlugpad tussen ’n begin- en eindpunt te vind. Hierdie projek kyk na twee spesifieke kinodinamiese beplanningsalgoritmes, die “Rapidly exploring Random Tree*” (of RRT*), en die “Probabilistic Roadmap Method” (of PRM). Die primêre fokus van hierdie projek is om die gedrag van hierdie algoritmes in spesifieke omgewings te analiseer en ’n volledige analise te doen op hul verskille. ’n Sekondêre fokus is die uitvoering van ’n beplande vlugpad d.m.v ’n Simulink-simulasie, en laastens kyk hierdie projek ook na die effek van padherbeplanning. Die werk wat gedoen is in hierdie projek stel ’n onbemande helikopter in staat om outonoom te navigeer in ’n onsekere, dinamiese en besige omgewing. Die werk bied ook insig in die keuse van ’n algoritme vir ’n gegewe omgewing: om te weet watter algoritme beter uitvoertye het kan waardevolle verwerkingstyd bespaar, en verseker dat die hele stelsel vinniger kan reageer.

abstract: The objective of this work is to develop a Stop-Rotor Multimode UAV. This UAV is capable of vertical take-off and landing like a helicopter and can convert from a helicopter mode to an airplane mode in mid-flight. Thus, this UAV can hover as a helicopter and achieve high mission range of an airplane. The stop-rotor concept implies that in mid-flight the lift generating helicopter rotor stops and rotates the blades into airplane wings. The thrust in airplane mode is then provided by a pusher propeller. The aircraft configuration presents unique challenges in flight dynamics, modeling and control. In this thesis a mathematical model along with the design and simulations of a hover control will be presented. In addition, the discussion of the performance in fixed-wing flight, and the autopilot architecture of the UAV will be presented. Also presented, are some experimental "conversion" results where the Stop-Rotor aircraft was dropped from a hot air balloon and performed a successful conversion from helicopter to airplane mode. / Dissertation/Thesis / M.S.Tech Mechanical Engineering 2011

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.

Au cours de la dernière décennie, les drones ont été largement utilisés dans les domaines des applications civiles. La photogrammétrie aéroportée a trouvé place dans ces applications comme une solution efficace de modélisation 3D mais aussi comme un outil de mesure. Vinci-Construction-Terrassement est une entreprise privée spécialisée dans le secteur des Travaux Publics qui intègre les drones et la photogrammétrie comme une solution de cartographie et de métrologie de ses chantiers. Cet outil est très efficace, par exemple, pour le calcul des volumes de stocks ou pour le suivi temporel de zones spécifiques avec un risque de glissement de terrain. Le but de ce travail est d’arriver à un géo-référencement direct des images acquises par la caméra lors du vol en s’appuyant uniquement sur un récepteur GPS embarqué. Le système utilisé doit être de faible coût et par conséquent le traitement des données est adapté à cette contrainte / Over the last decade, drones have been largely used for civil applications. Airborne photogrammetry has found place in these applications as a modeling and a measuring tool. Vinci-Construction-Terrassement is a private company of public building and works sector that integrates drones and photogrammetry as a mapping solution and metrology investigation on its sites. This tool is very efficient for the calculation of stock volumes for instance, or for time tracking of specific areas with risk of landslides. The aim of the present work is to do direct georeferencing of images acquired by the camera leaning on an embedded GPS receiver. The UAS used needs to be low cost and therefore data processing is adapted to this constraint

Unmanned Aerial Systems (UAS) are becoming more widely used in the new era of evolving technology; increasing performance while decreasing size, weight, and cost. A UAS equipped with a Flight Control System (FCS) that can be used to fly semi- or fully-autonomous is a prime example of a Cyber Physical and Safety Critical system. Current Cyber-Physical defenses against malicious attacks are structured around security standards for best practices involving the development of protocols and the digital software implementation. Thus far, few attempts have been made to embed security into the architecture of the system considering security as a holistic problem. Therefore, a Hierarchical, Embedded, Cyber Attack Detection (HECAD) framework is developed to provide security in a holistic manor, providing resiliency against cyber-attacks as well as introducing strategies for mitigating and dealing with component failures. Traversing the hardware/software barrier, HECAD provides detection of malicious faults at the hardware and software level; verified through the development of an FPGA implementation and tested using a UAS FCS.

This master thesis report presents the developement of an INS/GPS navigation loop written in ANSI C++ using a standard matrix library. The filter have been tested on an Unmanned Aerial Vehicle (UAV) called Brumby. Here data have been logged from the Inertial Measurement Unit (IMU) and the Global Positioning System (GPS) receiver. This data have then been postprocessed and run through the navigation filter for estimation of position, attitude and velocity of the vehicle during the flights. The error feedback to the Inertial Navigation System (INS) is done with a complement filter implemented using a kalman filter written in information form.The resulting navigation filter estimates the attitude within two degrees with 95% confidence and the position within two meter using 95% confidence. / <p>Validerat; 20101217 (root)</p>

There is a large number of design options to consider when designing aircraft vehicle systems for fighter aircraft, and there is a lack of tool support that provides an overview of these available design options. Various design options will bring consequences in terms of weight, performance, cost, etc. which is desired to be known in an early conceptual phase. Conventional methods, such as morphological matrix and design structure matrix, lack the ability to generate an overview and map complex systems. By studying model-based tools in form of ontologies and feature models in Protégé and FeatureIDE respectively, these tools are considered to provide a higher level of detail regarding the available design options compared to the conventional methods, such as the morphological matrix and the design structure matrix. Ontologies and feature-models are therefore considered to increase the effectiveness in the conceptual design phase of aircraft vehicle systems. By combining ontologies and feature models, more thoughtful design decisions can be performed. An increased knowledge of the available design options can lead to an improved development of aircraft vehicle systems, and new solutions can be evaluated. By performing more detailed trade studies for an unmanned aerial vehicle, for different system solutions, various parameters such as engine power outtake, system weight, etc. can be analysed and provide an indication whether a concept should be evaluated further. It is however necessary to consider how different parameters affect the overall system, and fuel penalty may be implemented as an equivalent parameter. Performing power flow calculations do however not consider solution-specific limitations, which have to be implemented to be able to determine if an aircraft vehicle system concept should be considered advantageous or not.

Feature detection and matching is an important step in many object tracking and detection algorithms. This paper discusses methods to improve upon previous work on the SYnthetic BAsis feature descriptor (SYBA) algorithm, which describes and compares image features in an efficient and discreet manner. SYBA utilizes synthetic basis images overlaid on a feature region of interest (FRI) to generate binary numbers that uniquely describe the feature contained within the FRI. These binary numbers are then used to compare against feature values in subsequent images for matching. However, in a non-ideal environment the accuracy of the feature matching suffers due to variations in image scale, and rotation. This paper introduces a new version of SYBA which processes FRI’s such that the descriptions developed by SYBA are rotation and scale invariant. To demonstrate the improvements of this robust implementation of SYBA called rSYBA, included in this paper are applications that have to cope with high amounts of image variation. The first detects objects along an oil pipeline by transforming and comparing frame-by-frame two surveillance videos recorded at two different times. The second shows camera pose plotting for a ground based vehicle using monocular visual odometry. The third generates panoramic images through image stitching and image transforms. All applications contain large amounts of image variation between image frames and therefore require a significant amount of correct feature matches to generate acceptable results.