UAS planning and trajectory generation for safe and long-duration oceanic and coastal missions.

La presente tesis doctoral, muestra el diseño de un sistema para la extensión de la duración de vuelo de sistemas autónomos no tripulados de tamaño pequeño. Este sistema fue diseñado en el contexto de misiones de vigilancia marítima y costera como parte del proyecto europeo MarineUAS. En este contexto, se han identificado tres problemas: 1) la necesidad de la estimación precisa de un campo de viento y la capacidad de identificación de fenómenos como el viento cortante o las ráfagas continuas y discretas para que puedan ser utilizadas potencialmente para la extracción de energía para mejorar la duración de vuelo. 2) La necesidad de generar trayectorias suaves para la extracción de energía considerando la dinámica de las plataformas de vuelo y 3) la habilidad de seguir dichas trayectorias. Para el primer problema, el uso de un método de computación directa permite determinar el campo de viento (velocidad y tasa de cambio de la velocidad de viento) sin la utilización de un estimador óptimo. Sin embargo, también se consideraron varios métodos y a partir de un análisis extenso se presentan diferentes comparativas de estos métodos, en el que se muestran las ventajas y desventajas de los mismos. Adicionalmente, la identificación de distintos fenómenos de viento, cómo las ráfagas, o el viento cortante, se logra a través de un innovador método que ejecuta una serie de pruebas estadísticas basadas en la distribución de Weibull y en distintos modelos dinámicos que consideran no solo la distribución del viento sino la interacción con el océano y la superficie en las respectivas capas límite. Para el segundo problema, una aproximación biomimética permitió el uso de un algoritmo complejo para la réplica de trajectorias de vuelo dinámico de aves. En dicho algoritmo se consideran observaciones presentadas por distintos científicos que permiten generar trayectorias paramétricas que consideran además restricciones cinemáticas de la plataforma en el diseño de las mismas. El tercer problema toma en consideración la curva generada y utiliza la teoría del campo de vectores para diseñar un controlador que permite seguir dicha trayectoria de manera eficiente y en tiempo real, respetando las leyes de control de bajo nivel en el autopiloto y permitiendo flexibilidad. Como complemento a este último sistema, se propone la reconfiguración dinámica de las misiones para mejorar el consumo energético durante el tiempo de vuelo considerando el viento predominante. Uno de los principales objectivos fue integrar, utilizando la metodología de ingeniería de sistemas, las distintias funciones anteriormente mencionadas en el que la ejecución de la misión fuese la prioridad. El principal logro fue haber realizado una extensa campaña experimental que permitió la validación del sistema en diferentes niveles, en el que se combinaron pruebas computacionales de alto y bajo nivel así como pruebas de campo en distintos escenarios y con distintas plataformas, lo cual permitió explorar la versatilidad del sistema. Los resultados muestran que se pueden lograr misiones más eficientes con mejoras de hasta un 20%en consumo de batería para misiones costeras. Finalmente, de los distintos análisis computacionales efectuados se concluye que el tiempo de ejecución de toda la función de extensión del vuelo es lo suficientemente pequeño para permitir la ejecución en tiempo real, lo cual, combinando con el diseño versátil en cuestión de arquitectura computacional, permiten la portabilidad del sistema así como la futura integración de funciones adicionales.In this thesis a system that aims to extend the flight duration of small Unmanned Aerial Systems (UAS) is presented. The system was designed in the context of oceanic and coastal surveillance missions as part of the MarineUAS European project. Three main problems were identified: 1) the need to accurately estimate the wind field and the capability to identify features of interest, such as, wind shear, and gusts that may be suitable to allow energy extraction to improve flight duration. 2) the need to generate smooth trajectories that extract energy, considering the UAS platform dynamics and 3) the ability to follow such paths. For the first problem, the use of a direct computation method allows determining the wind field (wind velocity and wind rate of change) without the use of an optimal estimator. Nevertheless, different wind velocity estimation methods are compared, and the pros and cons of each are exposed; in addition, the identification of features is accomplished with a novel approach that performs a real-time statistical analysis of the distribution of the wind field estimates, allowing the characterization of the shear components and also any other potential features, like continuous and discrete gusts considering complex models that take into account not only the phenomena but the interactions with the ground and ocean through their respective boundary layers. For the second problem, a biomimetic approach is presented, replicating the trajectories of soaring birds by considering observations of these birds and the replication of their swooping maneuvers using smooth parametrized curves. This allows flexibility in the curve design and also the incorporation of dynamic constraints of the platform on it. The solution of the third problem takes into account the smooth curve that was generated and among it, a type 1 Bishop moving frame is generated. Then, a novel adaptive control method based on the vector-field theory approach is proposed to calculate the error equations and the respective control law, which permits the tracking of the designed trajectory for dynamic soaring. Furthermore, an additional step was added, in which the surveillance mission is re-configured on a waypoint-to-waypoint basis for a more efficient flight considering the identified wind field. The result was that the execution of soaring trajectories would not be executed during all the mission, but only in specific legs that fulfill specific characteristics.The primary goal was to design algorithms that implement these functions and to integrate these functionalities in a systems-engineering approach, in which the mission execution is the main priority. An extensive experimental campaign was performed at different levels, in which software-in-the-loop and hardwarein- the-loop tests, together with field tests, were executed to demonstrate the efficiency of the various functions separately and integrated. The field tests and the simulations consider different scenarios and UAS platforms, showing the performance of the system in different conditions. The results showed that the system could execute a more efficient mission, with savings of up to 20% in battery consumption, with the so-called of the Flight-Duration-Enhancement-System (FDES). Finally, the computational analysis showed that the system could be executed in real-time with minimum latency despite the use of sophisticated algorithms; this, together with the chosen software and hardware architectures allows portability to other hardware components and the possibility of incorporating additional functions

A Framework for Offline Risk-aware Planning of Low-altitude Aerial Flights during Urban Disaster Response

Disaster response missions are dynamic and dangerous events for first responders. Active situational awareness is critical for effective decision-making, and unmanned aerial assets have successfully extended the range and output of sensors. Aerial assets have demonstrated their capability in disaster response missions via decentralized operations. However, literature and industry lack a systematic investigation of the algorithms, datasets, and tools for aerial system trajectory planning in urban disasters that optimizes mission performance and guarantee mission success. This work seeks to develop a framework and software environment to investigate the requirements for offline planning algorithms and flight risk models when applied to aerial assets exploring urban disaster zones. This is addressed through the creation of rapid urban maps, efficient flight planning algorithms, and formal risk metrics that are demonstrated in scenario-driven experiments using Monte Carlo simulation. First, rapid urban mapping strategies are independently compared for efficient processing and storage through obstacle and terrain layers. Open-source data is used when available and is supplemented with an urban feature prediction model trained on satellite imagery using deep learning. Second, sampling-based planners are evaluated for efficient and effective trajectory planning of nonlinear aerial dynamic systems. The algorithm can find collision-free, kinodynamic feasible trajectories using random open-loop control targets. Alternative open-loop control commands are formed to improve the planning algorithm’s speed and convergence. Third, a risk-aware implementation of the planning algorithm is developed that considers the uncertainty of energy, collisions, and onboard viewpoint data and maps them to a single measure of the likelihood of mission failure. The three modules are combined in a framework where the rapid urban maps and risk-aware planner are evaluated against benchmarks for mission success, performance, and speed while creating a unique set of benchmarks from open-source data and software. One, the rapid urban map module generates a 3D structure and terrain map within 20 meters of data and in less than 5 minutes. The Gaussian Process terrain model performs better than B-spline and NURBS models in small-scale, mountainous environments at 10-meter squared resolution. Supplementary data for structures and other urban landcover features is predicted using the Pix2Pix Generative Adversarial Network with a 3-channel encoding for nine labels. Structures, greenspaces, water, and roads are predicted with high accuracy according to the F1, OIU, and pixel accuracy metrics. Two, the sampling-based planning algorithm is selected for forming collision-free, 3D offline flight paths with a black-box dynamics model of a quadcopter. Sampling-based planners prove successful for efficient and optimal flight paths through randomly generated and rapid urban maps, even under wind and noise uncertainty. The Stable-Sparse-RRT, SST, algorithm is shown to improve trajectories for minimum Euclidean distance more consistently and efficiently than the RRT algorithm, with a 50% improvement in finite-time path convergence for large-scale urban maps. The forward propagation dynamics of the black-box model are replaced with 5-15 times more computationally efficient motion primitives that are generated using an inverse lower-order dynamics model and the Differential Dynamic Programming, DDP, algorithm. Third, the risk-aware planning algorithm is developed that generates optimal paths based on three risk metrics of energy, collision, and viewpoint risk and quantifies the likelihood of worst-case events using the Conditional-Value-at-Risk, CVaR, metric. The sampling-based planning algorithm is improved with informative paths, and three versions of the algorithm are compared for the best performance in different scenarios. Energy risk in the planning algorithm results in 5-35% energy reduction and 20-30% more consistency in finite-time convergence for flight paths in large-scale urban maps. All three risk metrics in the planning algorithm generally result in more energy use than the planner with only energy risk, but reduce the mean flight path risk by 10-50% depending on the environment, energy available, and viewpoint landmarks. A final experiment in an Atlanta flooding scenario demonstrates the framework’s full capability with the rapid urban map displaying essential features and the trajectory planner reporting flight time, energy consumption, and total risk. Furthermore, the simulation environment provides insight into offline planning limitations through Monte Carlo simulations with environment wind and system dynamics noise. The framework and software environment are made available to use as benchmarks in the field to serve as a foundation for increasing the effectiveness of first responders’ safety in the challenging task of urban disaster response.Ph.D

Aerial Vehicles

This book contains 35 chapters written by experts in developing techniques for making aerial vehicles more intelligent, more reliable, more flexible in use, and safer in operation.It will also serve as an inspiration for further improvement of the design and application of aeral vehicles. The advanced techniques and research described here may also be applicable to other high-tech areas such as robotics, avionics, vetronics, and space

Architecture and Information Requirements to Assess and Predict Flight Safety Risks During Highly Autonomous Urban Flight Operations

As aviation adopts new and increasingly complex operational paradigms, vehicle types, and technologies to broaden airspace capability and efficiency, maintaining a safe system will require recognition and timely mitigation of new safety issues as they emerge and before significant consequences occur. A shift toward a more predictive risk mitigation capability becomes critical to meet this challenge. In-time safety assurance comprises monitoring, assessment, and mitigation functions that proactively reduce risk in complex operational environments where the interplay of hazards may not be known (and therefore not accounted for) during design. These functions can also help to understand and predict emergent effects caused by the increased use of automation or autonomous functions that may exhibit unexpected non-deterministic behaviors. The envisioned monitoring and assessment functions can look for precursors, anomalies, and trends (PATs) by applying model-based and data-driven methods. Outputs would then drive downstream mitigation(s) if needed to reduce risk. These mitigations may be accomplished using traditional design revision processes or via operational (and sometimes automated) mechanisms. The latter refers to the in-time aspect of the system concept. This report comprises architecture and information requirements and considerations toward enabling such a capability within the domain of low altitude highly autonomous urban flight operations. This domain may span, for example, public-use surveillance missions flown by small unmanned aircraft (e.g., infrastructure inspection, facility management, emergency response, law enforcement, and/or security) to transportation missions flown by larger aircraft that may carry passengers or deliver products. Caveat: Any stated requirements in this report should be considered initial requirements that are intended to drive research and development (R&D). These initial requirements are likely to evolve based on R&D findings, refinement of operational concepts, industry advances, and new industry or regulatory policies or standards related to safety assurance

Conflict-free trajectory optimization with target tracking and conformance monitoring

This is a postprint (author final draft) deposit on institutional repository UPCommons from UPC, thanks to AIAA. Original version can be found on: https://arc.aiaa.org/doi/10.2514/1.C034251This paper proposes an optimization framework that computes conflict-free optimal trajectories in dense terminal airspace, while continuously monitoring trajectory conformance in an effort to improve predictability. The objective is to allow, as much as possible, continuous vertical trajectory profiles without impacting negatively on airspace capacity. Given automatic dependent surveillance–broadcast intent information, the future state of potential intruder aircraft are predicted, and this nominal trajectory is used as a constraint in the ownship trajectory optimization process. In it, a continuous multiphase optimal control problem is solved, taking into account spatial and temporal constraints. Additionally, a linearized Kalman filter keeps track of the target by estimating the deviations of its actual trajectory from its nominal trajectory, issuing a warning when an appropriate threshold is exceeded. This may be due to unexpected events, biases in the performance and weather models, wrong parameter assumptions, etc. An illustrative example is given, based on a computer simulation of two hypothetical trajectories in the Barcelona terminal maneuvering area. The results show how this framework resolves the problem of uncertainties in the trajectory predictions and results in a more efficient conflict resolution.Peer ReviewedPostprint (author's final draft

Autonomous Navigation for Mobile Robots in Crowded Environments

L'abstract è presente nell'allegato / the abstract is in the attachmen

Diseño de nuevos algoritmos de guiado y navegación con evasión de colisiones para vehículos aéreos no tripulados.

Tesis por compendio[ES] Debido a la creciente popularidad sobre la variedad de los Vehículos No Tripulados tanto en el campo militar como en el comercial, y de sus capacidades para navegar por diversos entornos, ya sean terrestres, aéreos o marinos, se evidencia que la clásica planificación de trayectorias y movimientos bidimensionales 2D podría no ser suficiente en un futuro inmediato. De esta manera, se debe resaltar que el presente trabajo aborda el problema de los Vehículos Aéreos No Tripulados (UAVs) de ala fija. En este sentido, la necesidad de encontrar una trayectoria navegable en el espacio euclídeo 3D se hace cada vez más necesario. En el caso de los UAV, considerar su cinemática para generar trayectorias suaves en tres dimensiones puede tener un interés significativo para la navegación autónoma aérea. Finalmente, los beneficios adicionales que se pueden producir son importantes. La principal dificultad de este problema es que los vehículos aéreos de características no-holonómicas se ven obligados a avanzar sin la posibilidad de detenerse a través de trayectorias 3D con curvaturas limitadas. En este sentido, se ha investigado la manera de proporcionar una completa caracterización de trayectorias óptimas para UAVs con un radio de giro limitado que se mueve en el plano tridimensional a una velocidad constante. Para completar tales tareas, un planificador de trayectorias no sólo debe proporcionar rutas tridimensionales para alcanzar una posición de destino sin colisionar con obstáculos, sino también debe asegurar que tal trayectoria sea adecuada para los UAVs que poseen propiedades cinemáticas específicas. Por lo tanto, el desarrollo del trabajo ha completado la algoritmia que genera una trayectoria discreta tridimensional al definir un conjunto de puntos 3D, resultantes de una división del espacio euclídeo tridimensional de manera dinámica, determinando las mejores opciones de avance, evitando analizar cada espacio del entorno completo. De esta manera, partiendo de los puntos 3D resultantes de la planificación de trayectoria tridimensional, se ha generado una trayectoria en forma de curva suave construida en función de las limitaciones de giro del UAV (resaltando que es difícil asegurar que el camino resultante cumpla con las restricciones cinemáticas en las tres dimensiones simultáneamente). Finalmente, es importante destacar que a menudo las restricciones mencionadas se calculan secuencialmente y de forma bidimensional, sobre un par de dimensiones desacopladas, lo que limita la capacidad de optimización. Para todo ello, se ha desarrollado un algoritmo de suavizado para un planificador de trayectorias que considera las restricciones cinemáticas tridimensionales completas sin desacoplar las dimensiones.[CA] Debut a la creixent popularitat sobre la varietat dels Vehicles No Tripulats tant en el camp militar com en el comercial, i de les seves capacitats per navegar per diversos entorns, ja siguin terrestres, aeris o marins, s'evidencia que la clàssica planificació de trajectòries i moviments bidimensionals 2D podria no ser suficient en un futur immediat. D'aquesta manera, s'ha de ressaltar que el present treball aborda el problema dels Vehicles Aeris No Tripulats (UAV) d'ala fixa. En aquest sentit, la necessitat de trobar una trajectòria navegable en l'espai euclidià 3D es fa cada vegada més necessari. En el cas dels UAV, considerar la seva cinemàtica per generar trajectòries suaus en tres dimensions pot tenir un interès significatiu per a la navegació autònoma aèria. Finalment, els beneficis addicionals que es poden produir són importants. La principal dificultat d'aquest problema és que els vehicles aeris de característiques no-holonómicas es veuen obligats a avançar sense la possibilitat de detenir-se a través de trajectòries 3D amb curvatures limitades. En aquest sentit, s'ha investigat la manera de proporcionar una completa caracterització de trajectòries òptimes per UAVs amb un radi de gir limitat que es mou en el pla tridimensional a una velocitat constant. Per completar aquestes tasques, un planificador de trajectòries no només ha de proporcionar rutes tridimensionals per assolir una posició de destinació sense col·lisionar amb obstacles, sinó també ha d'assegurar que tal trajectòria sigui adequada per als UAVs que posseeixen propietats cinemàtiques específiques. Per tant, el desenvolupament de la feina ha completat la algorísmia que genera una trajectòria discreta tridimensional a l'definir un conjunt de punts 3D, resultants d'una divisió de l'espai euclidià tridimensional de manera dinàmica, determinant les millors opcions d'avanç, evitant analitzar cada espai de l' entorn complet. D'aquesta manera, partint dels punts 3D resultants de la planificació de trajectòria tridimensional, s'ha generat una trajectòria en forma de corba suau construïda en funció de les limitacions de gir de l'UAV (ressaltant que és difícil assegurar que el camí resultant compleixi amb les restriccions cinemàtiques en les tres dimensions simultàniament). Finalment, és important destacar que sovint les restriccions esmentades es calculen seqöencialment i de forma bidimensional, sobre un parell de dimensions desacoblades, el que limita la capacitat d'optimització. Per tot això, s'ha desenvolupat un algoritme de suavitzat per a un planificador de trajectòries que considera les restriccions cinemàtiques tridimensionals completes sense desacoblar les dimensions.[EN] Due to the growing popularity of the variety of Unmanned Vehicles in both the military and commercial fields, and their capabilities to navigate diverse environments, whether land, air or sea, it is evident that the classic two-dimensional 2D trajectory and motion planning may not be enough in the near future. Thus, it should be noted that this paper addresses the problem of fixed-wing Unmanned Aerial Vehicles (UAVs). In this sense, the need to find a navigable path in 3D Euclidean space becomes more and more necessary. In the case of UAVs, considering their kinematics to generate smooth trajectories in three dimensions may be of significant interest for autonomous air navigation. Finally, the additional benefits that can be produced are important. The main difficulty of this problem is that air vehicles with non-holonomic characteristics are forced to advance without the possibility of stopping through 3D trajectories with limited curvatures. In this regard, research has been conducted to provide a complete characterization of optimal trajectories for UAVs with a limited turning radius that move in the 3D plane at a constant speed. To complete such tasks, a path planner must not only provide three-dimensional paths to reach a target position without colliding with obstacles, but must also ensure that such a path is suitable for UAVs that possess specific kinematic properties. Therefore, the development of the work has completed the algorithm that generates a discrete three-dimensional path by defining a set of 3D points, resulting from a division of the three-dimensional Euclidean space in a dynamic way, determining the best forward options, avoiding to analyze each space of the whole environment. In this way, starting from the 3D points resulting from the three-dimensional path planning, a smooth curve path has been generated, built according to the UAV turning constraints (highlighting that it is difficult to ensure that the resulting path meets the kinematic constraints in the three dimensions simultaneously). Finally, it is important to note that often the constraints mentioned are calculated sequentially and in a two-dimensional shape, on a pair of decoupled dimensions, which limits the ability to optimize. For all this, a smoothing algorithm has been developed for a path planner that considers the complete three-dimensional kinematic constraints without decoupling the dimensions.Este trabajo ha sido parcialmente financiado por el Gobierno de España a través del Ministerio de Economía y Competitividad bajo el proyecto de Investigación DP I2015−71443−R, y por la administración local de la Generalitat Valenciana a través de los proyectos GV /2017/029 y AICO/2019/055. El autor ha sido beneficiario de una beca otorgada por el Instituto de Fomento al Talento Humano (IFTH) (2015−AR2Q9209) a través del Gobierno de Ecuador.Samaniego Riera, FE. (2021). Diseño de nuevos algoritmos de guiado y navegación con evasión de colisiones para vehículos aéreos no tripulados [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/161274TESISCompendi

Multidisciplinary optimisation of an Unmanned Aerial Vehicle with a fuel cell powered energy system

ALF/ENGAER 139425-J Bernardo Miguel Teixeira Alves. Examination Committee: Chairperson: COR/ENGAER Luís António Monteiro Pessanha; Supervisors: Prof. André Calado Marta, MAJ/ENGAER Luís Filipe da Silva Félix; Member of the Committee: Prof. Pedro Vieira GamboaPara explorar a utilização de células de combustível a hidrogénio como alternativa viável aos combustíveis nocivos em veículos aéreos não-tripulados, um conceito de UAV de classe I foi desenvolvido no Centro de Investigação da Força Aérea (CIAFA). Este trabalho foca-se nos estudos trade-off realizados durante a sua conceção e na subsequente otimização. Primeiro, uma abordagem de otimização multi-objetivo foi utilizada com o auxílio do algoritmo genético NSGA-II para balancear dois objetivos em conflito: peso reduzido; e elevada autonomia. Conclui-se que é possível voar mais de três horas com um peso máximo à descolagem de 21,6 kg, uma célula de hidrogénio de 800 W e 148 g de hidrogénio. Uma configuração mais pesada com maior potência nominal e mais combustível foi descartada devido a um constragimento na envergadura. Posteriormente, com um conceito que satisfaz os requisitos impostos, uma abordagem multi-disciplinar (MDO) foi utilizada para maximizar a autonomia. O software utilizado foi o OpenAeroStruct, método dos elementos finitos (FEM) e o método da malha de vórtices (VLM) para modelar superfícies sustentadoras. Inicialmente, uma condição de cruzeiro e de carga foram utilizadas com torção geométrica da asa como variável de projeto. Posteriormente, maior complexidade foi introduzida atrav´es da utilização de afilamento, corda e envergadura. Finalmente, uma terceira condição de voo foi introduzida com o intuito de garantir o requisito de perda. Com a utilização de MDO foi possível aumentar a autonomia em 21% satisfazendo todos os requisitos. Este trabalho marca um passo importante no desenvolvimento de um futuro protótipo no Centro de Investigação.To explore the use of hydrogen fuel cells as a feasible alternative to pollutant fuels on Unmanned Aerial Vehicles (UAVs), a class I concept was designed at the Portuguese Air Force Research Centre. This work focuses on the trade-off studies performed during its design and on the optimisation that followed. First, a multi-objective optimisation approach was used with the aid of the Algorithm NSGAII to balance between two conflicting objectives: low weight and high endurance. It was found that it is possible to fly for more than 3 hours with a Maximum Take-off Weight of 21.6 kg, an 800 W fuel cell and 148 g of hydrogen. A heavier configuration with more power and fuel was discarded due to a wingspan constraint. Later, after the concept satisfied the project requirements, Multi-Disciplinary Design Optimisation (MDO) was performed to achieve the maximum endurance possible. The software used was OpenAeroStruct, low fidelity Finite Element Analysis (FEA) and Vortex Lattice Method (VLM) to model lifting surfaces. Initially, a cruise and a load flight point were used with wing geometric twist only as design variable. After, more complexity was added by introducing taper, wing chord and span. Finally, a third flight point was introduced to ensure the stall requirements were satisfied. The use of MDO allowed a 21% increase in endurance with a smaller wing area. Other improvements could not be achieved without violation of the constraints. This work marks an important milestone in the development of a future prototype at the Research Centre.N/