3 research outputs found

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

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    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

    Recursive Rewarding Modified Adaptive Cell Decomposition (RR-MACD): A Dynamic Path Planning Algorithm for UAVs

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    [EN] A relevant task in unmanned aerial vehicles (UAV) flight is path planning in 3D environments. This task must be completed using the least possible computing time. The aim of this article is to combine methodologies to optimise the task in time and offer a complete 3D trajectory. The flight environment will be considered as a 3D adaptive discrete mesh, where grids are created with minimal refinement in the search for collision-free spaces. The proposed path planning algorithm for UAV saves computational time and memory resources compared with classical techniques. With the construction of the discrete meshing, a cost response methodology is applied as a discrete deterministic finite automaton (DDFA). A set of optimal partial responses, calculated recursively, indicates the collision-free spaces in the final path for the UAV flight.The authors would like to acknowledge the Spanish Ministry of Economy and Competitiveness for providing funding through the project DPI2015-71443-R and the local administration Generalitat Valenciana through the project GV/2017/029. Franklin Samaniego thanks IFTH (Instituto de Fomento al Talento Humano) Ecuador (2015-AR2Q9209), for its sponsorship of this work.Samaniego-Riera, FE.; Sanchís Saez, J.; Garcia-Nieto, S.; Simarro Fernández, R. (2019). Recursive Rewarding Modified Adaptive Cell Decomposition (RR-MACD): A Dynamic Path Planning Algorithm for UAVs. Electronics. 8(3):1-21. https://doi.org/10.3390/electronics8030306S12183Valavanis, K. P., & Vachtsevanos, G. J. (Eds.). (2015). 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