<p>Multirotor unmanned aerial vehicles (UAVs) added with the ability to physically interact with the environment has opened endless possibilities for aerial mobile manipulation tasks. With the unlimited reachable workspace and physical interaction capabilities, such robots can enhance human ability to perform dangerous and hard-to-reach tasks. However, realizing aerial mobile manipulation in real-world scenarios is challenging with respect to the diversity in aerial platforms, control fidelity and susceptibility to variations in the environment. Therefore, the first part of the dissertation provides tools to  classify and evaluate different multirotor designs. A measure of responsiveness of a multirotor platform in exerting generalized forces and rejecting disturbances is discussed through the control bandwidth analysis. Superiority in control bandwidth for fully-actuated multirotors is established in a comparison with equivalent under-actuated multirotors. To further classify and distinguish multirotor platforms, a new mobility measure is proposed and compared by surveying all aerial platforms employed for aerial mobile manipulation. In compliance to the control bandwidth analysis, the mobility measure for fully-actuated multirotors is relatively higher making them better suited for manipulation tasks. </p> <p><br></p> <p><br></p> <p>Aerial physical interaction, as a part of aerial mobile manipulation, with partially unknown environments is challenging due to the uncertainties imposed while dexterously exerting force signatures. A hybrid physical interaction (HyPhI) controller is proposed to enable constrained force contact with a steady transition from unconstrained motion, by squelching excess energy during initial impact. However, uncertainties posed by the partially unknown environment requires to understand the surrounding environment and their current physical states, that can enhance interaction performance. The limited resources and flight time of the multirotors requires to simultaneously understand the environment and perform aerial physical interactions. Inspection-on-the-fly is an uncanny ability of humans to intuitively infer states during manipulation while reducing the necessity to conduct inspection and manipulation separately. In this dissertation, the inspection-on-the-fly method based HyPhI controller is proposed to engage in a steady contact with partially unknown environments, while simultaneously estimating the physical states of the surfaces. The proposed method is evaluated in a mockup of real-world facility, to understand the surface properties while engaging in steady interactions. Further, such inspection of surfaces and estimation of various states enables a deeper understanding of the environment while enhancing the ability to physically interact. </p>

La vision représente un des plus importants signaux en robotique. Une caméra monoculaire peut fournir de riches informations visuelles à une fréquence raisonnable pouvant être utilisées pour la commande, l’estimation d’état ou la navigation dans des environnements inconnus par exemple. Il est cependant nécessaire de respecter des contraintes visuelles spécifiques telles que la visibilité de mesures images et les occultations durant le mouvement afin de garder certaines cibles visuelles dans le champ de vision. Les quadrirotors sont dotés de capacités de mouvement très réactives du fait de leur structure compacte et de la configuration des moteurs. De plus, la vision par une caméra embarquée (fixe) va subir des rotations dues au sous-actionnement du système. Dans cette thèsenous voulons bénéficier de l’agilité du quadrirotor pour réaliser plusieurs tâches de navigation basées vision. Nous supposons que l’estimation d’état repose uniquement sur la fusion capteurs d’une centrale inertielle (IMU) et d’une caméra monoculaire qui fournit des estimations de pose précises. Les contraintes visuelles sont donc critiques et difficiles dans un tel contexte. Dans cette thèse nous exploitons l’optimisation numérique pour générer des trajectoires faisables satisfaisant un certain nombre de contraintes d’état, d’entrées et visuelles non linéaires. A l’aide la platitude différentielle et de la paramétrisation par des B-splines nous proposons une stratégie de replanification performante inspirée de la commande prédictive pour générer des trajectoires lisses et agiles. Enfin, nous présentons un algorithme de planification en temps minimum qui supporte des pertes de visibilité intermittentes afin de naviguer dans des environnements encombrés plus vastes. Cette contribution porte l’incertitude de l’estimation d’état au niveau de la planification pour produire des trajectoires robustes et sûres. Les développements théoriques discutés dans cette thèse sont corroborés par des simulations et expériences en utilisant un quadrirotor. Les résultats reportés montrent l’efficacité des techniques proposées. / Vision constitutes one of the most important cues in robotics. A single monocular camera can provide rich visual information at a reasonable rate that can be used as a feedback for control, state estimation of mobile robots or safe navigation in unknown environments for instance. However, it is necessary to satisfy particular visual constraints on the image such as visibility and occlusion constraints during motion to keep some visual targets visible. Quadrotors are endowed with very reactive motion capabilities due to their compact structure and motor configuration. Moreover, vision from a (fixed) on-board camera will suffer from rotation motions due to the system underactuation. In this thesis, we want to benefit from the system aggressiveness to perform several vision-based navigation tasks. We assume state estimation relies solely on sensor fusion of an onboard inertial measurement unit (IMU) and a monocular camera that provides reliable pose estimates. Therefore, visual constraints are challenging and critical in this context. In this thesis we exploit numerical optimization to design feasible trajectories satisfying several state, input and visual nonlinear constraints. With the help of differential flatness and B-spline parametrization we will propose an efficient replanning strategy inspired form Model Predictive Control to generate smooth and agile trajectories. Finally, we propose a minimum-time planning algorithm that handles intermittent visibility losses in order to navigate in larger cluttered environments. This contribution brings state estimation uncertainty at the planning stage to produce robust and safe trajectories. All the theoretical developments discussed in this thesis are corroborated by simulations and experiments run by using a quadrotor UAV. The reported results show the effectiveness of proposed techniques.

The conventional Mini and Large scale Unmanned Aerial Vehicle systems span anywhere from approximately 12 inches to 12 feet; endowing them with larger propulsion systems, batteries/fuel-tanks, which in turn provide ample power reserves for long-endurance flights, powerful actuators, on-board avionics, wireless telemetry etc. The limitations thus imposed become apparent when shifting to Micro Aerial Vehicles (MAVs) and trying to equip them with equal or near-equal flight endurance, processing, sensing and communication capabilities, as their larger scale cousins. The conventional MAV as outlined by The Defense Advanced Research Projects Agency (DARPA) is a vehicle that can have a maximum dimension of 6 inches and weighs no more than 100 grams. Under these tight constraints, the footprint, weight and power reserves available to on-board avionics and actuators is drastically reduced; the flight time and payload capability of MAVs take a massive plummet in keeping with these stringent size constraints. However, the demand for micro flying robots is increasing rapidly. The applications that have emerged over the years for MAVs include search&rescue operations for trapped victims in natural disaster succumbed urban areas; search&reconnaissance in biological, radiation, natural disaster/hazard succumbed/prone areas; patrolling&securing home/office/building premises/urban areas. VTOL capable rotary and fixed wing flying vehicles do not scale down to micro sized levels, owing to the severe loss in aerodynamic efficiency associated with low Reynolds number physics on conventional airfoils; whereas, present state of the art in flapping wing designs lack in one or more of the minimum qualities required from an MAV: Appreciable flight time, appreciable payload capacity for on-board sensors/telemetry and 6DoF hovering/VTOL performance. This PhD. work is directed towards overcoming these limitations. Firstly, this PhD thesis presents the advent of a novel Quad-Wing MAV configuration (called the QV). The Four-Wing configuration is capable of performing all 6DoF flight maneuvers including VTOL. The thesis presents the design, conception, simulation study and finally hardware design/development of the MAV. Secondly, this PhD thesis proves and demonstrates significant improvement in on-board Energy-Harvesting resulting in increased flight times and payload capacities of the order of even 200%-400% and more. Thirdly, this PhD thesis defines a new actuation principle called, Fixed Frequency, Variable Amplitude (FiFVA). It is demonstrated that by the use of passive elastic members on wing joints, a further significant increase in energy efficiency and consequently reduction in input power requirements is observed. An actuation efficiency increase of over 100% in many cases is possible. The natural evolution of actuation development led to invention of two novel actuation systems to illustrate the FiFVA actuation principle and consequently show energy savings and flapping efficiency improvement. Lastly, but not in the least, the PhD thesis presents supplementary work in the design, development of two novel Micro Architecture and Control (MARC) avionics platforms (autopilots) for the application of demonstrating flight control and communication capability on-board the Four-Wing Flapping prototype. The design of a novel passive feathering mechanism aimed to improve lift/thrust performance of flapping motion is also presented.

Cette thèse développe une nouvelle approche de contrôle pour les avions à échelle réduite. Les lois de commande proposées exploitent un modèle non linéaire simple mais pertinent des forces aérodynamiques appliquées à l’aéronef. Ils reposent sur une structure hiérarchique de contrôle non linéaires, et sont synthétisées sur la base d’analyse de stabilité et de convergence théoriques. Ils sont conçus pour fonctionner sur un large domaine de vol. En particulier, ils évitent les singularités associées à la paramétrisation de l'attitude et la direction de la vitesse. Dans un premier temps, le problème de stabilisation de trajectoires de référence est résolu en étendant la méthode du "thrust vectoring", utilisée pour les véhicules à voilure tournante, au cas des aéronefs à voilure fixe. Dans le cas des avions, le principal défi est de prendre en compte les forces aérodynamiques dans la conception des systèmes de commande. Afin de résoudre ce problème, le contrôle proposé est conçu et analysé sur la base du modèle de forces aérodynamique proposé. Le domaine d'utilisation de cette loi de commande est élargi et englobe les trajectoires d'équilibre (trim trajectories) qui sont classiquement utilisées dans la littérature. Cette solution est ensuite adaptée au problème de suivi de chemin, afin de concevoir des lois de guidage cinématique et de contrôle dynamique applicables à presque tout chemin 3D régulier. Les lois de contrôle proposées contiennent des termes intégraux qui robustifient le contrôle vis-à-vis de dynamiques non modélisées. Plusieurs problèmes pratiques sont adressés et les lois de commande proposées sont validées par des simulations du type "hardware-in-the-loop". Enfin, des résultats d'essais en vol illustrent la performance des lois de contrôle proposées. / The present thesis develops a new control approach for scale-model airplanes. The proposed control solutions exploit a simple but pertinent nonlinear model of aerodynamic forces acting on the aircraft. Nonlinear controllers are based on a hierarchical structure, and are derived on the basis of theoretical stability and convergence analyses. They are designed to operate on a large spectrum of operating conditions. In particular, they avoid the singularities associated with the parameterization of the attitude and the heading of the vehicle, and do not rely on a decoupling between longitudinal and lateral dynamics. First, the trajectory tracking problem is addressed by extending the thrust vectoring method used for small rotor vehicles to the case of fixed wing vehicles. In the case of airplanes, the main challenge is to take into account the aerodynamic forces in the design of control systems. In order to solve this problem, the proposed control is designed and analyzed on the basis of the proposed aerodynamic forces model. The flight envelope is thus broadened beyond trim trajectories which are classically used in the literature. This solution is then adapted to the path following problem, and kinematic guidance and dynamic control laws are developed within a single coherent framework that applies to almost any regular 3D path. The proposed control laws incorporate integral terms that robustify the control with respect to unmodelled dynamics. Several practical issues are addressed and the proposed control laws are validated via hardware-in-the-loop simulations. Finally, successful flight test results illustrate the soundness and performance of the proposed control laws.

[ES] Las ciudades modernas están al límite de su capacidad en el plano horizontal. Muchas de ellas tienen un problema de tráfico muy complejo de paliar o resolver. La movilidad aérea urbana promete ser la revolución que puede resolver la saturación del tráfico en los futuros escenarios urbanos. Se espera que el crecimiento del mercado de la movilidad aérea urbana muestre una tendencia positiva constante, pero la tecnología asociada necesita aumentar su madurez. La gestión de múltiples vehículos aéreos, que dependen de tecnologías en auge como la inteligencia artificial y las estaciones de control en tierra automatizadas, requerirá una conexión tierra-aire-tierra sólida e ininterrumpida para completar sus trayectorias. La exigencia de una conexión ininterrumpida está naturalmente relacionada con una comprensión completa de los fenómenos que afectan al canal aire-tierra. La primera contribución es proponer un modelo de canal que pueda capturar las consecuencias de dichos fenómenos. Normalmente, un modelo de este tipo puede emitir el estado del canal en un punto determinado, prediciendo el estado del canal a lo largo de la trayectoria de la aeronave. Un modelo muy detallado exige herramientas y datos que proporcionen la información necesaria. La descripción y enumeración de cada pieza de información necesaria para una simulación de canal satisfactoria componen la segunda contribución. Una vez conocido el estado del canal, se pueden optimizar los puntos recorridos por la aeronave para cubrir aquellos con mejor rendimiento del canal. La tercera y última contribución es la propuesta de un conjunto de algoritmos de optimización para encontrar la ruta más adecuada. El algoritmo de optimización constituye el planificador de trayectorias, del que se espera que explore eficazmente el espacio de búsqueda y proponga una trayectoria que cumpla con los objetivos predefinidos: máxima calidad aire-tierra, disponibilidad y tiempo de vuelo. Cada método propuesto se pone a prueba en varios escenarios. Estos escenarios incluyen diversas situaciones que pueden estresar a los métodos y favorecer la elección de uno de ellos. Las situaciones incluidas son diferentes condiciones del terreno y zonas de exclusión aérea. / [CA] Les ciutats modernes estan al límit de la seua capacitat al pla horitzontal. Moltes tenen un problema de trànsit molt complex de pal·liar o resoldre. La mobilitat aèria urbana promet ser la revolució que pot resoldre la saturació del trànsit als futurs escenaris urbans. S'espera que el creixement del mercat de la mobilitat aèria urbana mostre una tendència positiva constant, però la tecnologia associada necessita augmentar-ne la maduresa. La gestió de múltiples vehicles aeris, que depenen de tecnologies en auge com la intel·ligència artificial i les estacions de control a terra automatitzades, requerirà una connexió terra-aire-terra sòlida i ininterrompuda per completar les seues trajectòries. L'exigència d'una connexió ininterrompuda està relacionada naturalment amb una comprensió completa dels fenòmens que afecten el canal aire-terra. La primera contribució és proposar un model de canal que puga capturar les conseqüències dels fenòmens esmentats. Normalment, un model d'aquest tipus pot emetre l'estat del canal en un punt determinat, predient l'estat del canal al llarg de la trajectòria de l'aeronau. Un model molt detallat exigeix eines i dades que proporcionen la informació necessària. La descripció i l'enumeració de cada peça d'informació necessària per a una simulació de canal satisfactòria componen la segona contribució. Una vegada conegut l'estat del canal, es poden optimitzar els punts recorreguts per l'aeronau per tal de cobrir aquells amb el millor rendiment del canal. La tercera i última contribució és la proposta d'un conjunt d'algorismes d'optimització per trobar la ruta més adequada. L'algorisme d'optimització constitueix el planificador de trajectòries, del qual s'espera que explore eficaçment l'espai de cerca i propose una trajectòria que complisca els objectius predefinits: màxima qualitat aire-terra, disponibilitat i temps de vol. Cada mètode proposat es posa a prova a diversos escenaris. Aquests escenaris inclouen diverses situacions que poden estressar els mètodes i afavorir-ne l'elecció. Les situacions incloses són diferents condicions del terreny i les zones d'exclusió aèria. / [EN] Modern cities are at the limit of their capacity in the horizontal plane. Many of them have a traffic problem that is highly complex to alleviate or solve. Urban air mobility promises to be the revolution that can solve traffic saturation in future urban scenarios. The growth of the urban air mobility market is expected to show a constant positive tendency, but the associated technology needs to raise its readiness levels. Managing aerial vehicle fleets, dependent on rising technologies such as artificial intelligence and automated ground control stations, will require a solid and uninterrupted connection to complete their trajectories. The requirement for an uninterrupted connection is naturally connected to a complete understanding of phenomena affecting the air-to-ground channel. The first contribution to the field is to propose a channel model that can capture the consequences of said phenomena. Typically, such a model can output the channel state at a given point, predicting the channel state throughout the aircraft's trajectory. A highly detailed model demands tools and data to deliver the necessary information. The description and enumeration of each piece of information required for a successful channel simulation compose the second contribution to the field. Once the channel state is known, the travelled points by the aircraft can be optimised to cover those with better channel performance. The third and last contribution to the field is proposing a set of optimisation algorithms to find the most suitable route. The optimisation algorithm forms the path planner, expected to efficiently explore the search space and propose a trajectory compliant with predefined objectives: maximum air-to-ground quality, availability, and flight time. Each proposed method is tested in various scenarios. These scenarios include various situations that can stress the methods and favour the choice of one. Included situations are different terrain conditions and no-fly zones. / Expósito García, A. (2023). Deterministic model of the radio channel applied to the optimization of the UAV trajectory for optimum air-to-ground communication in the environment of future urban scenarios [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/192614