A method is developed for computing the minimum fuel trajectory for a satellite that moves between two different positions and orientations using a sequence of impulsive burns. The method makes use of the linear Clohessy-Wiltshire equations to describe translational motions, Euler's equations of rigid body motion for describing the attitude motions, and a sequential quadratic programming optimization code. Initial solutions are found assuming no coupling between the translational and rotational motions and with no imposed constraint on the time of the rendezvous. Further solutions are then found by varying the vehicle center of gravity location along one axis, thereby coupling the rotational motions into two axes of translation thrusters, and by imposing time limits on the rendezvous. A discussion of the impact that these parameters have on the optimal solutions for two different models of the satellite thruster systems is then presented. / Master of Science

Consider the problem of developing an algorithm that computes optimal preprogrammed evasive maneuvers for a Maneuvering Reentry Vehicle (MaRV) attacking a target defended with Anti-Ballistic Missiles (ABMs). The problem is large in terms of the number of optimization parameters, and perhaps in terms of the number of nonlinear constraints. Since both MaRV and ABM trajectories are expensive to compute, rapid convergence of the optimization algorithm is of prime concern. This paper examines a discontinuity in the cost function that degrades both the speed and the reliability of optimizer convergence. A solution is offered, proposing that the optimization algorithm be operated in a new parameter space, in which the discontinuity occurs at infinity. Effectively, the mapping prevents the optimization algorithm from crossing the discontinuity thereby improving optimizer convergence. Results comparing convergence with and without the parameter mapping demonstrate the effectiveness of the procedure. / Master of Science

Yes / A significant proportion of healthcare that is delivered is wasteful, harmful and not evidence based. There are many wound care related guidelines, but their implementation in practice is variable. The Society of Tissue Viability (SoTV) published updated seating guidelines in 2017, but there is a lack of theoretical and conceptual clarity about how these guidelines are being utilised to inform clinical practice. Therefore, the aim of this paper is to generate a theory that can be used to incorporate the SoTV seating guidelines into policy and clinical practice. Methods: We critically reflected on data from an evaluation study utilising systems-thinking approach, informed by implementation and safety science using wider literature as well as our expertise to generate a guideline implementation theory. Discussion: Factors that facilitate or hinder the incorporation of the SoTV guidelines into policy and practice were characterised. We conceptualised the implementation of these guidelines into policy and practice into a Translation or Implementation into Policy or Practice (TIPP) theory with distinct stages, that we called liminal spaces. Knowledge of the guidelines, and the agency or authority to effect change, are key factors in the translation of these guidelines into clinical practice. Conclusion: Our theory is that there are liminal spaces in the implementation trajectory of these guidelines into practice, which have their own characteristics. This theory provides a framework that can be used to underpin guidelines strategies to embed skin and wound care guidelines into policy and clinical practice in order to improve patient care.

In this thesis we study the methods for motion planning for nonholonomic systems. These systems are characterized by nonholonomic constraints on their generalized velocities. The motion planning problem with constraints on the velocities is transformed into a control problem having fewer control inputs than the degrees of freedom. The main focus of the thesis is on the study of motion planning and design of the feedback control laws for an autonomous underwater vehicle: a nonholonomic system. The nonlinear controllability issues for the system are also studied. For the design of feedback controllers, the system is transformed into chained and power forms. The methods of transforming a nonholonomic system into these forms are discussed. The work presented in this thesis is a step towards the initial study concerning the applicability of kinematic-based control on underwater vehicles. / Master of Science

A pitch-control predictor-corrector ascent guidance algorithm has been developed and evaluated for a rocket-based upper stage of a two-stage-to-orbit launch vehicle. Detailed descriptions of the predictor-corrector algorithm and a neural network loop modification are given. The mission requirement is insertion into a stable 50 x 100 nmi orbit at 375,000 ft altitude, coasting toward apogee at a positive inertial flight path angle. Three degree-of-freedom trajectory analysis is performed using the Program to Optimize Simulated Trajectories (POST2). Results of Monte Carlo simulations including uncertainties in atmosphere, thrust, aerodynamics and initial state are presented and compared to trajectories optimized for maximum injected weight. / Master of Science

We present a new trajectory generation algorithm for autonomous guidance and control of unmanned vehicles from a given starting point to a given target location. We build and update incomplete a priori maps of the operating environment in real time using onboard sensors and compute level sets on the map reflecting the minimal cost of traversal from the current vehicle location to the goal. We convert the trajectory generation problem into a finite-time-horizon optimal control problem using the computed level sets as terminal costs in a receding horizon framework and transform it into a simpler nonlinear programming problem by discretization of the candidate control and state histories. We ensure feasibility of the generated trajectories by constraining the solution of the optimization problem using a simplified vehicle model. We provide strong performance guarantees by checking for stability of the algorithm through the test of matching conditions at the end of each iteration. The algorithm thus explicitly incorporates the vehicle dynamics and constraints and generates trajectories realizable by the vehicle in the field. Successful preliminary field demonstrations and complete simulation results for a marine unmanned surface vehicle demonstrate the efficacy of the proposed approach for fast operations in poorly characterized riverine environments. / Master of Science

Ce travail est développé dans le contexte des projets SESAR et Next-Gen, où de nouvelles applications de la gestion du trafic aérien (ATM) comme le concept de gestion d'opérations en 4D, se sont focalisées sur les opérations basées sur la trajectoire (TBO - Trajectory Based Operations). Ces opérations sont en relation avec l'extension de la flexibilité de la séparation entre avions, et par conséquence, avec l'augmentation de la capacité du trafic aérien. En sachant qu'une évolution des routes fixes et autorisations émises par le contrôle du trafic aérien (ATC - Air Traffic Control) vers des trajectoires flexibles est imminente, en s'appuyant en même temps aux niveaux les plus élevés de l'automatique embarquée, ce travail de recherche s'intéresse aux sujets qui aideront à la transition des systèmes actuels vers les systèmes compatibles avec les nouveaux besoins des TBO. Les principaux axes de recherche de ce manuscrit s'articulent en trois points: La génération de trajectoires en 4D, le guidage en 4D, et l'estimation de la masse d'un avion pour l'optimisation des trajectoires. Concernant la génération des trajectoires, le besoin des utilisateurs d'espaces aériens de planifier leurs routes préférées à partir d'un point d'entrée dans l'espace aérien sans être limités par les configurations existantes est considéré. Une solution particulière pour la génération de trajectoires lisses en 4D à partir de points de contrôle prédéfinis est alors explorée. La méthode proposée s'appuie sur les courbes de Bézier, et elle permet de contrôler la distance euclidienne entre le point de contrôle donné et la trajectoire proposée. Ceci est fait en modifiant la trajectoire de telle façon qu'elle reste à l'intérieur des limites des facteurs de charge, en considérant un compromis entre la courbure de la trajectoire et la vitesse voulue de l'avion, ce qui représente une étape importante dans le chemin vers les TBO. Le guidage précis en 4D améliorera la sûreté en diminuant l'occurrence de quasi-collisions aériennes pour des trajectoires en 4D planifiées en avance. En conséquence, deux autopilotes et deux méthodes de guidage sont développées avec l'objectif de réduire la charge de travail des contrôleurs du trafic aérien associée à un vol. Les techniques de backstepping et feedback linearization sont utilisées pour le pilotage, alors que l'inversion non linéaire directe et indirecte sont adoptées pour le guidage. De plus, l'impact de la connaissance inexacte de la masse de l'avion dans le suivi de trajectoires, ses conséquences dans l'optimisation, la consommation de carburant, et la performance de l'avion, a conduit à l'implémentation d'une estimation embarquée de la masse de l'avion. L'approche créée est basée sur les moindres carrées, en fournissant des estimations de la masse initiale et la masse courante, toutes les deux avec une précision suffisante pour atteindre les objectifs liées aux TBO. Les méthodes proposées dans cette thèse sont examinées en utilisant un modèle à six degrés de liberté, dont les paramètres approchent un appareil du type B737-200 ou A320-200. La simulation est basée sur une modélisation complète et non linéaire de la dynamique des avions de transport incluant des perturbations liées au vent. Des réseaux de neurones sont utilisés pour obtenir les différents coefficients aérodynamiques correspondant aux forces et moments de l'avion. / This work is developed with the perspective of SESAR and Next-Gen projects, where new applications of Air Traffic Management (ATM) such as the Full 4D Management concept, are centered on Trajectory-Based Operations (TBO), deeply related with the extension of the flexibility in separation between aircraft, and hence, with the augmentation of air traffic capacity. Therefore, since a shift from fixed routes and Air Traffic Control (ATC) clearances to flexible trajectories is imminent, while relying on higher levels of onboard automation, the thesis hinges around topics that should enable or ease the transition from current systems to systems compliant with the new expectancies of Trajectory-Based Operations. The main axes of the manuscript can be summarized in three topics: 4D trajectory generation, 4D guidance, and mass estimation for trajectory optimization. Regarding the trajectory generation, the need of airspace users to plan their preferred route from an entry to an exit point of the airspace without being constrained by the existent configurations is considered. Thus, a particular solution for 4D smooth path generation from preexisting control points is explored. The method is based on Bezier curves, and is able to control the Euclidian distance between the given control points and the proposed trajectory. This is done by reshaping the path to remain within load factor limits, taking into account a tradeoff between path curvature and aircraft intended speed, representing a milestone in the road towards Trajectory-Based Operations. It is considered that accurate 4D guidance will improve safety by decreasing the occurrence of near mid-air collisions for planned conflict free 4D trajectories. In consequence, two autopilots and two guidance approaches are developed with the objective of diminishing the workload for air traffic controllers associated to a single flight. The backstepping and feedback linearization techniques are used for attitude control, while direct and indirect nonlinear inversion are adopted for guidance. Furthermore, the impact of inaccurate mass knowledge in trajectory guidance, with consequences in optimization, fuel consumption, and aircraft performance, has led to the implementation of an on-board aircraft mass estimation. The created approach is based on least squares, providing an initial mass estimation, and online computations of the current mass, both with enough accuracy to meet the objectives related to TBO. The methods proposed in this thesis are tested in a six degrees of freedom Matlab model with its parameters chosen similar to an aircraft type B737-200 or A320-200. The simulation is based on a full nonlinear modelling of transport aircraft dynamics under wind disturbances. Trained neural networks are used to obtain the aerodynamic coefficients corresponding the aircraft forces and moments.

A Navegação é um dos maiores problemas na robótica móvel, sua função consiste em guiar o robô em um espaço de trabalho por um caminho plausível durante um determinado intervalo de tempo que o leve de um ponto inicial a um ponto final definido. É possível separar esse processo em vários níveis como, a localização do robô no espaço de trabalho, o planejamento de um caminho admissível, a geração de uma trajetória e por fim o controle desse trajeto. Este trabalho apresenta a proposta de desenvolvimento dos níveis de geração e controle de trajetória para um veículo terrestre de grande porte para uso em ambientes de trabalho semiestruturados, principalmente em ambientes agrícolas. Para tal propósito se utiliza o conceito de trajetórias baseadas em clotóides e predefinidas para um sistema bidimensional (X, Y). O gerador de trajetória proposto neste trabalho determina uma função contínua que considera as restrições cinemáticas e determina o tempo de trabalho, a posição e orientação do robô na posição final. As informações determinadas pela função são utilizadas por um controlador de lógica fuzzy para determinar as velocidades linear e angular do robô. Para validar trajetória planejada e o controlador, foram realizados testes nas plataformas robóticas Helvis-III, um protótipo simples com sistema de esterçamento nas rodas dianteiras estilo Ackermann e o RAM (Robô agrícola Móvel) - um veículo de grande porte com estrutura de esterçamento nas 2 rodas com estilo Ackermann de condução. O sistema demonstra bom desempenho, devido ao fato de que o desvio do caminho mantém uma media de 3 metros em base ao valor real e uma média de 0.5 metros em relação ao calculado, estando dentro dos padrões dos sensores GNSS usados para os testes experimentais. / Navigation is one of the biggest problems in mobile robotics, its ban on guiding the robot in a workspace by a plausible path over a defined interval of time than the level of a starting point and a definite endpoint. It is possible to separate the process at some levels such as the location of the robot in the workspace, the planning of a permissible path, the generation of a path and a process of control of that path. This paper presents a proposal for the development of teaching levels and trajectory control for a large land vehicle for use in semi structured work environments, mainly in agricultural environments. To do this, use the concept of routines in clothoids and predefined for a two-dimensional system (X, Y). The generator of trajectory standard this risk is work in the risk control risk, and the risk and the status of work, the status of the risk and work of the position. As one of the reasons for the function are used by a fuzzy logic controller to determine the linear and angular velocities of the robot. To validate the planned trajectory and controller, they were actually tested on the Helvis-III robotic platforms, a simple prototype with the Ackermann advanced style wheel-arming system and the RAM (Mobile Shared Robot) - a large vehicle with structure of Ackermann style 2-wheel steering. The system should be good performance, by the same of the tracking of average pathways and of three meters in base to value and average of 0.5 meters in body the year, being based on the limits of GNSS used for test experimental tests.

A Navegação é um dos maiores problemas na robótica móvel, sua função consiste em guiar o robô em um espaço de trabalho por um caminho plausível durante um determinado intervalo de tempo que o leve de um ponto inicial a um ponto final definido. É possível separar esse processo em vários níveis como, a localização do robô no espaço de trabalho, o planejamento de um caminho admissível, a geração de uma trajetória e por fim o controle desse trajeto. Este trabalho apresenta a proposta de desenvolvimento dos níveis de geração e controle de trajetória para um veículo terrestre de grande porte para uso em ambientes de trabalho semiestruturados, principalmente em ambientes agrícolas. Para tal propósito se utiliza o conceito de trajetórias baseadas em clotóides e predefinidas para um sistema bidimensional (X, Y). O gerador de trajetória proposto neste trabalho determina uma função contínua que considera as restrições cinemáticas e determina o tempo de trabalho, a posição e orientação do robô na posição final. As informações determinadas pela função são utilizadas por um controlador de lógica fuzzy para determinar as velocidades linear e angular do robô. Para validar trajetória planejada e o controlador, foram realizados testes nas plataformas robóticas Helvis-III, um protótipo simples com sistema de esterçamento nas rodas dianteiras estilo Ackermann e o RAM (Robô agrícola Móvel) - um veículo de grande porte com estrutura de esterçamento nas 2 rodas com estilo Ackermann de condução. O sistema demonstra bom desempenho, devido ao fato de que o desvio do caminho mantém uma media de 3 metros em base ao valor real e uma média de 0.5 metros em relação ao calculado, estando dentro dos padrões dos sensores GNSS usados para os testes experimentais. / Navigation is one of the biggest problems in mobile robotics, its ban on guiding the robot in a workspace by a plausible path over a defined interval of time than the level of a starting point and a definite endpoint. It is possible to separate the process at some levels such as the location of the robot in the workspace, the planning of a permissible path, the generation of a path and a process of control of that path. This paper presents a proposal for the development of teaching levels and trajectory control for a large land vehicle for use in semi structured work environments, mainly in agricultural environments. To do this, use the concept of routines in clothoids and predefined for a two-dimensional system (X, Y). The generator of trajectory standard this risk is work in the risk control risk, and the risk and the status of work, the status of the risk and work of the position. As one of the reasons for the function are used by a fuzzy logic controller to determine the linear and angular velocities of the robot. To validate the planned trajectory and controller, they were actually tested on the Helvis-III robotic platforms, a simple prototype with the Ackermann advanced style wheel-arming system and the RAM (Mobile Shared Robot) - a large vehicle with structure of Ackermann style 2-wheel steering. The system should be good performance, by the same of the tracking of average pathways and of three meters in base to value and average of 0.5 meters in body the year, being based on the limits of GNSS used for test experimental tests.

This thesis presents an integrated framework for online obstacle avoidance of rotary-wing unmanned aerial vehicles (UAVs), which can provide UAVs an obstacle field navigation capability in a partially or completely unknown obstacle-rich environment. The framework is composed of a LIDAR interface, a local obstacle grid generation, a receding horizon (RH) trajectory optimizer, a global shortest path search algorithm, and a climb rate limit detection logic. The key feature of the framework is the use of an optimization-based trajectory generation in which the obstacle avoidance problem is formulated as a nonlinear trajectory optimization problem with state and input constraints over the finite range of the sensor. This local trajectory optimization is combined with a global path search algorithm which provides a useful initial guess to the nonlinear optimization solver. Optimization is the natural process of finding the best trajectory that is dynamically feasible, safe within the vehicle's flight envelope, and collision-free at the same time. The optimal trajectory is continuously updated in real time by the numerical optimization solver, Nonlinear Trajectory Generation (NTG), which is a direct solver based on the spline approximation of trajectory for dynamically flat systems. In fact, the overall approach of this thesis to finding the optimal trajectory is similar to the model predictive control (MPC) or the receding horizon control (RHC), except that this thesis followed a two-layer design; thus, the optimal solution works as a guidance command to be followed by the controller of the vehicle. The framework is implemented in a real-time simulation environment, the Georgia Tech UAV Simulation Tool (GUST), and integrated in the onboard software of the rotary-wing UAV test-bed at Georgia Tech. Initially, the 2D vertical avoidance capability of real obstacles was tested in flight. Then the flight test evaluations were extended to the benchmark tests for 3D avoidance capability over the virtual obstacles, and finally it was demonstrated on real obstacles located at the McKenna MOUT site in Fort Benning, Georgia. Simulations and flight test evaluations demonstrate the feasibility of the developed framework for UAV applications involving low-altitude flight in an urban area.