[ES] El ritmo de desarrollo tecnológico actual y la investigación científica están permitiendo alcanzar mayores niveles de automatización en todos los sectores industriales. Uno de los ejemplos más representativos es el uso de aeronaves no tripuladas (UAS) en diferentes aplicaciones. Debido al gran potencial de este tipo de aeronaves, las Autoridades de Aviación Civil están desarrollando un nuevo marco regulatorio que permita integrarlas en el espacio aéreo civil de forma segura. El objetivo consiste en garantizar que la operación con UAS se realice con un nivel de seguridad equivalente al de la aviación tripulada convencional. Para tratar de alcanzar este objetivo, esta tesis propone aumentar el nivel de automatización de un UAS dotando al sistema embarcado con la capacidad de Gestión Automática de Contingencias (ACM). La función del sistema ACM es la de asesorar al piloto en el momento en que se produce una contingencia en vuelo; y en última instancia, tomar el control total de la aeronave si la situación así' lo requiere (por ejemplo, en caso de pérdida del enlace de Comunicación y Control (C2)) o si el piloto delega la resolución del conflicto al sistema automático. Para acreditar que las nuevas funciones no suponen un riesgo añadido para la operación, resultará determinante seguir metodologías de diseño seguro basadas en los estándares de la industria aeroespacial. La tesis propone una solución tecnológica basada en tres pilares: a) una arquitectura software para el sistema automático a bordo de la aeronave que trate de adaptar la trayectoria de vuelo a la condición operacional del vehículo, equilibrando seguridad y robustez; b) una especificación de Plan de Misión novedosa que permita aumentar la predictibilidad de la aeronave tras sufrir una contingencia; y c) un modelo de riesgo que permita determinar la ruta que minimiza el riesgo derivado de la operación. Las diferentes propuestas realizadas en esta tesis se han implementado en un demostrador y se han validado en un entorno de simulación. Los resultados obtenidos apoyan la idea de que dotar al sistema embarcado de mayor grado de automatización puede ser un mecanismo viable hacia la integración segura de UAS en el espacio aéreo civil. En concreto, los resultados muestran que el sistema ACM propuesto es capaz de reducir el riesgo de la operación tras sufrir una contingencia y que, cuando esto ocurre, la respuesta de la aeronave sigue siendo predecible, incluso si el piloto no puede intervenir. / [CA] El ritme de desenvolupament tecnològic actual i la investigació científica estan permetent implementar majors nivells d'automatització a tots els àmbits de la indústria. Un dels exemples més representatius és l'ús d'aeronaus no tripulades (UAS) en diferents aplicacions. Vist el gran potencial d'aquest tipus d'aeronaus, les Autoritats d'Aviació Civil estan tractant de desenvolupar un nou marc regulador que permeta integrar-les en l'espai aeri civil de forma segura. Es tracta de garantir que l'operació d'un UAS es realitza amb un nivell de seguretat equivalent al de l'aviació tripulada convencional. Per tal d'assolir aquest objectiu, aquesta tesi proposa augmentar el nivell d'automatització d'un UAS dotant el sistema embarcat amb la capacitat de Gestió Automàtica de Contingències (ACM). La funció del sistema ACM és assessorar el pilot quan ocorre una contingència en vol; i en última instància, prendre el control total sobre l'aeronau si és necessari (per exemple, en cas de pèrdua de l'enllaç de Comunicació i Control (C2)) o si el pilot delega la resolució del conflicte al sistema automàtic. Per tal d'acreditar que les noves funcions del sistema automàtic no comporten un risc afegit per a l'operació, resultarà determinant emprar metodologies de disseny segur d'acord amb els estàndards de la indústria aeroespacial. La tesi proposa una solució tecnològica basada en tres pilars: a) una arquitectura software per al sistema automàtic a bord de l'aeronau que tracte d'adaptar la trajectòria de vol a la condició operacional del vehicle, equilibrant seguretat i robustesa; b) una especificació de Pla de Missió innovadora que permeta augmentar la predictibilitat de l'aeronau quan ocorre una contingència; i c) un model de risc que permeta determinar la ruta que minimitza el risc derivat de l'operació. Les distintes propostes realitzades en aquesta tesi s'han implementat sobre un demostrador i s'han validat en un entorn de simulació. Els resultats de la investigació recolzen la idea que dotar el sistema embarcat d'un major grau d'automatització pot ser un mecanisme adient per integrar els UAS en l'espai aeri civil de manera segura. En concret, els resultats indiquen que el sistema ACM és capaç de reduir el risc de l'operació quan ocorre una contingència i que en eixe cas, la resposta de l'aeronau segueix sent predicible, fins i tot si el pilot no hi pot intervenir. / [EN] Technological development and scientific research are steadily enabling higher levels of automation in the global industry. In the aerospace sector, the operation of Unmanned Aircraft System (UAS) is a clear example. Given the huge potential of the UAS market, Civil Aviation Authorities are elaborating a new regulatory framework for the safe integration of UAS into the civil airspace. The general goal is ensuring that the operation of UAS has an Equivalent Level of Safety (ELOS) to that of manned aviation. To meet the previous goal, this thesis advocates for increasing the level of automation of UAS operations by providing the automatic system on-board the aircraft with Automated Contingency Management (ACM) functions. ACM functions are designed to assist the pilot-in-command in case a contingency, and ultimately to fully replace the pilot if this is required by the situation (e.g. due to a Command and Control (C2) link loss) or if the pilot decides so. However, in order for automation to be safe, automated functions must be developed following safe design methodologies based on aerospace standards. The thesis develops a technological solution that is based on three pillars: a) a software architecture for the automatic system on-board the aircraft that tries to autonomously adapt to contingencies while still achieving mission objectives; b) a novel Mission Plan specification than increases predictability in the event of a contingency; and c) a probabilistic risk model that ensures that the flight trajectory is optimal from the point of view of the risk exposure. The different proposals are prototyped and validated using a simulation environment. The results obtained support the idea that an increase in the automation level of the aircraft can be an effective means towards the safe integration of UAS into the civil airspace. The proposed ACM functions are proved to reduce the operational risk in the event of a contingency, while ensure that the aircraft remains predictable, even without pilot intervention. / En primer lloc, vull fer constar que aquesta tesi ha estat co-financiada pel Fons Social Europeu 2014-2020 i pel programa VALI+d de la Generalitat Valenciana (expedient número ACIF/2016/197). / Usach Molina, H. (2019). Automated Contingency Management in Unmanned Aircraft Systems [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/130202 / TESIS

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Nitrogen run-off from agriculture have been linked to human health problems on a global level. Large-scale conventional producers struggle to redefine themselves as sustainable because reducing nitrogen (N) inputs without justification or validation may lead to severe profit losses. Small unmanned aerial systems (sUAS) sensing may allow for decreased N runoff. Failure to address this problem will exacerbate already excessive N runoff into the Mississippi River and beyond. The purpose of this study was to reduce fertilizer N input using sUAS technology to assess crop canopy needs. In 2020 and 2021, variable rate nitrogen (VRN) side-dress N application maps were calculated on early corn and cotton crops sensed with MicaSense® technology. The SCCCI and FENDVI VIs most often were highly related by SEq to early corn and cotton canopy N status. VariRite™ technology was successfully implemented in producer’s fields using VI calibrated imagery captured from sUAS.

Unmanned aircraft systems (UAS) represent the future of modern aviation. Over the past 10 years their use abroad by the military has become commonplace for surveillance and combat. Unfortunately, their use at home has been far more restrictive. Due to safety and regulatory concerns, UAS are prohibited from flying in the National Airspace System without special authorization from the FAA. One main reason for this is the lack of an on-board pilot to "see and avoid" other air traffic and thereby maintain the safety of the skies. Development of a comparable capability, known as "Sense and Avoid" (SAA), has therefore become a major area of focus. This research focuses on the SAA problem as it applies specifically to small UAS. Given the size, weight, and power constraints on these aircraft, current approaches fail to provide a viable option. To aid in the development of a SAA system for small UAS, various simulation and hardware tools are discussed. The modifications to the MAGICC Lab's simulation environment to provide support for multiple agents is outlined. The use of C-MEX s-Functions to improve simulation performance and code portability is also presented. For hardware tests, two RC airframes were constructed and retrofitted with autopilots to allow autonomous flight. The development of a program to interface with the ground control software and run the collision avoidance algorithms is discussed as well. Intruder sensing is accomplished using a low-power, low-resolution radar for detection and an Extended Kalman Filter (EKF) for tracking. The radar provides good measurements for range and closing speed, but bearing measurements are poor due to the low-resolution. A novel method for improving the bearing approximation using the raw radar returns is developed and tested. A four-state EKF used to track the intruder's position and trajectory is derived and used to provide estimates to the collision avoidance planner. Simulation results and results from flight tests using a simulated radar are both presented. To effectively plan collision avoidance paths a tree-branching path planner is developed. Techniques for predicting the intruder position and creating safe, collision-free paths using the estimates provided by the EKF are presented. A method for calculating the cost of flying each path is developed to allow the selection of the best candidate path. As multiple duplicate paths can be created using the branching planner, a strategy to remove these paths and greatly increase computation speed is discussed. Both simulation and hardware results are presented for validation.

Proving the correctness of autonomous systems is challenged by the use of non-deterministic artificial intelligence algorithms and ever-increasing lines of code. While correctness is conventionally determined through analysis and testing, it is impossible to train and test the system for all possible scenarios or formally analyze millions of lines of code. This thesis describes an alternative method that monitors system behavior during runtime and executes a recovery action if any formally specified property is violated. Multiple parallel safety monitors synthesized from linear temporal logic (LTL) formulas capturing the correctness and liveness properties are implemented in isolated configurable hardware to avoid negative impacts on the system performance. Model checking applied to the final implementation establishes the correctness of the last line of defense against malicious attacks and software bugs. The first part of this thesis illustrates the monitor synthesis flow with rules defining a three-dimensional cage for a commercial-off-the-shelf drone and demonstrates the effectiveness of the monitoring system in enforcing strict behaviors. The second part of this work defines safety monitors to provide assurances for a virtual autonomous flight beyond visual line of sight. Distinct sets of monitors are called into action during different flight phases to monitor flight plan conformance, stability, and airborne collision avoidance. A wireless interface supported by the proposed architecture enables the configuration of monitors, thereby eliminating the need to reprogram the FPGA for every flight. Overall, the goal is to increase trust in autonomous systems as demonstrated with two common drone operations. / Master of Science / Software code in autonomous systems, like cars, drones, and robots, keeps growing not just in length, but also in complexity. The use of machine learning and artificial intelligence algorithms to make decisions could result in unexpected behaviors when encountering completely new situations. Traditional methods of verifying software encounter difficulties while establishing the absolute correctness of autonomous systems. An alternative to proving correctness is to enforce correct behaviors during execution. The system's inputs and outputs are monitored to ensure adherence to formally stated rules. These monitors, automatically generated from rules specified as mathematical formulas, are isolated from the rest of the system and do not affect the system performance. The first part of this work demonstrates the feasibility of the approach by adding monitors to impose a virtual cage on a commercially available drone. The second phase of this work extends the idea to a simulated autonomous flight with a predefined set of points that the drone must pass through. These points along with the necessary parameters for the monitors can be uploaded over Bluetooth. The position, speed, and distance to nearby obstacles are independently monitored and a recovery action is executed if any rule is violated. Since the monitors do not assume anything about the source of the violations, they are effective against malicious attacks, software bugs, and sensor failures. Overall, the goal is to increase confidence in autonomous systems operations.

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UAS has been become a very popular tool in surveying and evaluation of the systems measurement uncertainties are necessary. The most common method for georeferencing UAS data is to use ground control points (GCP) in order to use them in block adjustment. In recent years’ new techniques for direct georeferencing with UAS have been presented, which in theory means that the position of the UAS can be determined accurately enough and therefore GCP’s can be excluded. This study evaluates  uncertainties of the UAS Freya from SmartPlanes that don’t need GCP’s for georeferencing. The technique applied in the evaluation is based on Post Processed Kinematic (PPK) for coordinate determination of the UAS, which means that the collected GNSS data can be post processed using a reference station.   The test area was a 280 x 320 m block in the north end of Gävle airport, Sweden. Each flight is conducted in two orthogonal blocks and evaluated in three different ways against the 16 GCP. The altitude was about 90 m for all flights. The uncertainty of the PPK-technique is tested and evaluated with three different methods to ensure both accuracy and potential use. In total five flights were assessed and evaluated with Agisoft PhotoScan against 16 GCP spread over the area. The position of each GCP’s was determined with four independent network RTK measurements.  The results show that the georeferencing with the PPK-technique and block adjustment has potential to meet the uncertainties in level with indirect georeferencing using GCP. The results show very similar planimetric uncertainties, around 0,020 m in RMS, for all evaluations with the PPK-technique. The results of the uncertainty in height is more scattered where the two lowest results in a RMS under 0,015 m and the highest over 0,100 m for the difference against the 16 GCP.  It is possible to achieve low uncertainties with the method without the use of GCP. For areas where establishment of GCP is not possible, using UAS equipped with PPKtechnology provides a very suitable alternative to use. The results show relatively large differences between the evaluations and in order to determine the exact cause of them, further studies are required. / Den starka teknikutvecklingen för UAS resulterar i flera nya produkter på marknaden och för att utvärdera deras mätosäkerheter krävs det kontroller av systemen. Den vanligaste metoden vid georeferering med UAS är att använda koordinatbestämda flygsignaler på marken. På senare år har metoder för direkt georeferering presenterats, vilket i teorin innebär att positionen för UAS kan bestämmas så pass noggrant att flygsignaler kan uteslutas. I denna studie utvärderas mätosäkerheter för Freya, ett UAS från SmartPlanes som med hjälp av bra positionering och blockutjämning ska kunna användas för georeferering utan flygsignalering. Systemet från Smartplanes bygger på Post Processed Kinematic (PPK) för koordinatbestämning, vilket innebär att insamlat GNSS data kan efterberäknas med korrektioner från en referensstation. Mätosäkerheten för PPK-tekniken testas och utvärderas med 3 olika metoder för att se både på mätosäkerhet samt möjlig användning. Totalt fem flygningar har utförts på ett testområde som var cirka 280x320 m och beläget i den norra delen av Gävle flygplats. Flyghöjden var kring 90 m för alla flygningar som vidare har bearbetats och utvärderats i programvaran PhotoScan från Agisoft. Kontrollen av mätosäkerheten har gjorts mot 16 spridda kontrollpunkter på marken som har positionsbestämts med fyra oberoende nätverks-RTK mätningar vardera. Varje flygning är utförd i två ortogonala block och utvärderades med fyra olika konfigurationer mot de 16 kontrollpunkterna.  Resultaten visar att georeferering med hjälp av blockutjämning och PPK-tekniken har potential för att uppnå mätosäkerheter i nivå med indirekt georeferering med hjälp av stödpunkter på marken. I plan visar resultaten på väldigt jämna mätosäkerheter, kring 0,020 m i RMS, för alla utvärderingar med PPK-tekniken. Resultaten i höjd är mer spridda där de lägsta visar mätosäkerheter under 0,015 m RMS och de högsta över 0,100 m i RMS för avvikelsen mot kontrollpunkterna. Det är fullt möjligt att uppnå låga mätosäkerheter med metoden utan användning av stödpunkter. För användningsområden där stödpunkter inte kan etableras är detta UAS med PPK-tekniken ett mycket lämpligt alternativ att använda. Resultaten visar på relativt stora skillnader mellan de olika testade metoderna och för att avgöra den exakta orsaken till dem skulle vidare studier behövas.

The focus of this dissertation is on developing novel methods and extending existing ones to improve the security and reliability of fixed-wing unmanned aircraft systems (UAS). Specifically, we focus on three strands of work: i) designing UAS controllers with performance guarantees using the robust control framework, ii) developing tools for detection and mitigation of physical-layer security threats in UAS, and iii) extending tools from compositional verification to design and verify complex systems such as UAS. Under the first category, we use the robust H-infinity control approach to design a linear parameter-varying (LPV) path-following controller for a fixed-wing UAS that enables the aircraft to follow any arbitrary planar curvature-bounded path under significant environmental disturbances. Three other typical path-following controllers, namely, a linear time-invariant H-infinity controller, a nonlinear rate-tracking controller, and a PID controller, are also designed. We study the relative merits and limitations of each approach and demonstrate through extensive simulations and flight tests that the LPV controller has the most consistent position tracking performance for a wide array of geometric paths. Next, convex synthesis conditions are developed for control of distributed systems with uncertain initial conditions, whereby independent norm constraints are placed on the disturbance input and the uncertain initial state. Using this approach, we design a distributed controller for a network of three fixed-wing UAS and demonstrate the improvement in the transient response of the network when switching between different trajectories. Pertaining to the second strand of this dissertation, we develop tools for detection and mitigation of security threats to the sensors and actuators of UAS. First, a probabilistic framework that employs tools from statistical analysis to detect sensor attacks on UAS is proposed. By incorporating knowledge about the physical system and using a Bayesian network, the proposed approach minimizes the false alarm rates, which is a major challenge for UAS that operate in dynamic and uncertain environments. Next, the security vulnerabilities of existing UAS actuators are identified and three different methods of differing complexity and effectiveness are proposed to detect and mitigate the security threats. While two of these methods involve developing algorithms and do not require any hardware modification, the third method entails hardware modifications to the actuators to make them resilient to malicious attacks. The three methods are compared in terms of different attributes such as computational demand and detection latency. As for the third strand of this dissertation, tools from formal methods such as compositional verification are used to design an unmanned multi-aircraft system that is deployed in a geofencing application, where the design objective is to guarantee a critical global system property. Verifying such a property for the multi-aircraft system using monolithic (system-level) verification techniques is a challenging task due to the complexity of the components and the interactions among them. To overcome these challenges, we design the components of the multi-aircraft system to have a modular architecture, thereby enabling the use of component-based reasoning to simplify the task of verifying the global system property. For component properties that can be formally verified, we employ results from Euclidean geometry and formal methods to prove those properties. For properties that are difficult to be formally verified, we rely on Monte Carlo simulations. We demonstrate how compositional reasoning is effective in reducing the use of simulations/tests needed in the verification process, thereby increasing the reliability of the unmanned multi-aircraft system. / Doctor of Philosophy / Given the safety-critical nature of many unmanned aircraft systems (UAS), it is crucial for stake holders to ensure that UAS when deployed behave as intended despite atmospheric disturbances, system uncertainties, and malicious adversaries. To this end, this dissertation deals with developing novel methods and extending existing ones to improve the security and reliability of fixed-wing UAS. Specifically, we focus on three key areas: i) designing UAS controllers with performance guarantees, ii) developing tools for detection and mitigation of security threats to sensors and actuators of UAS, and iii) extending tools from compositional verification to design and verify complex systems such as UAS. Pertaining to the first area, we design controllers for UAS that would enable the aircraft to follow any arbitrary planar curvature-bounded path under significant atmospheric disturbances. Four different controllers of differing complexity and effectiveness are designed, and their relative merits and limitations are demonstrated through extensive simulations and flight tests. Next, we develop control design tools to improve the transient response of multi-mission UAS networks. Using these tools, we design a controller for a network of three fixed-wing UAS and demonstrate the improvement in the transient response of the network when switching between different trajectories. As for the contributions in the second area, we develop tools for detection and mitigation of security threats to the sensors and actuators of UAS. First, we propose a framework for detecting sensor attacks on UAS. By judiciously using knowledge about the physical system and techniques from statistical analysis, the framework minimizes the false alarm rates, which is a major challenge in designing attack detection systems for UAS. Then, we focus on another important attack surface of the UAS, namely, the actuators. Here, we identify the security vulnerabilities of existing UAS actuators and propose three different methods to detect and mitigate the security threats. The three methods are compared in terms of different attributes such as computational demand, detection latency, need for hardware modifications, etc. In regard to the contributions in the third area, tools from compositional verification are used to design an unmanned multi-aircraft system that is tasked to track and compromise an aerial encroacher, wherein the multi-aircraft system is required to satisfy a global system property pertaining to collision avoidance and close tracking. A common approach to verifying global properties of systems is monolithic verification where the whole system is analyzed. However, such an approach becomes intractable for complex systems like the multi-aircraft system considered in this work. We overcome this difficulty by employing the compositional verification approach, whereby the problem of verifying the global system property is reduced to a problem of reasoning about the system’s components. That being said, even formally verifying some component properties can be a formidable task; in such cases, one has to rely on Monte Carlo simulations. By suitably designing the components of the multi-aircraft system to have a modular architecture, we show how one can perform focused component-level simulations rather than conduct simulations on the whole system, thereby limiting the use of simulations during the verification process and, as a result, increasing the reliability of the system.

The modernization of the National Air Traffic Control System is on the horizon, and with it, the possible introduction of autonomous air vehicles into the national airspace. Per the FAA Aerospace Forecast (FAA, 2013), U.S. carrier passenger traffic is expected to average 2.2 percent growth per year over the next 20 years with government statistics indicating that the average domestic load factor for airlines in 2014 was approximately 84.4 percent (US Department of Transportation, 2015). Adding to that demand, the potential introduction of unmanned and autonomous air vehicles motivates reconsideration of control schemes. One of the proposed solutions (Eby, 1994) would involve a decentralized control protocol. Equipping each aircraft with the information necessary to navigate safely through integrated airspace becomes an information sharing problem: how much information about other aircraft is required for a pilot to safely fly the gamut of a heavily populated airspace and what paradigm shifts may be necessary to safely and efficiently utilize available airspace? This thesis describes the development of a tool for testing alternative traffic management systems, centralized or decentralized, in the presence of uncertainty. Applying a computational fluid dynamics-inspired approach to the problem creates a simulation tool to model both the movement of traffic within the airspace and also allows study of the effects of interactions between vehicles. By incorporating a Smoothed Particle Hydrodynamics (SPH) based model, discrete particle aircraft each carry a set of unique deterministic and stochastic properties. With this model, aircraft interaction can be studied to better understand how variations in the nondeterministic properties of the system affect its overall efficiency and safety. The tool is structured to be sufficiently flexible as to allow incorporation of different collision detection and avoidance rules for aircraft traffic management. / Master of Science