Thesis (M.S.)--Ohio University, June, 2005. / Includes bibliographical references (p. 90-92)

Thesis (Ph. D.)--University of Texas at Austin, 2005. / Vita. Includes bibliographical references.

Thesis (M.S.)--Ohio University, June, 2005. / Title from PDF t.p. Includes bibliographical references (p. 90-92)

Thesis (Ph. D.)--Aerospace Engineering, Georgia Institute of Technology, 2008. / Ruzzene, Massimo, Committee Chair ; Bottasso, Carlo L., Committee Member ; Costello, Mark, Committee Member ; Hodges, Dewey H., Committee Member ; Weston, Neil, Committee Member.

The thesis traces the history of missile aerodynamic prediction methods and defines the aerodynamic requirements for the subsonic free-flight projectiles configurations under consideration. Different types of trajectory model are described with the aerodynamic input requirement being analysed. Methods of generating the required aerodynamic data for the trajectory models are discussed emphasising the aerodynamic models capabilities, weaknesses and ease of use. The method of masses aerodynamic prediction method is defined, highlighting the adaptations to the method that were carried out to generate the aerodynamic stability data required for subsequent projectile trajectory analysis. An assessment of the sensitivity and accuracy of the simulated data is carried out using experimental flight trial data on different projectile configurations. Finally, using the simulation models developed in previous chapters, a parametric analysis is carried out on different projectile configurations to optimise the trajectory performance.

The explosion of personal positioning devices like GPS-enabled smartphones has enabled the collection and storage of a huge amount of positioning data in the form of trajectories. Thereby, trajectory data have brought many research challenges in the process of recovery, storage and knowledge discovery in mobility as well as new applications to support our society in mobility terms. Other research area that has been receiving great attention nowadays is the area of complex network or science of networks. Complex network is the first approach to model complex system that are present in the real world, such as economic markets, the Internet, World Wide Web and disease spreading to name a few. It has been applied in different field, like Computer Science, Biology and Physics. Therefore, complex networks have demonstrated a great potential to investigate the behavior of complex systems through their entities and the relationships that exist among them. The present dissertation, therefore, aims at exploiting approaches to analyze mobility data using a perspective of complex networks. The first exploited approach stands for the trajectories as the main entities of the networks connecting each other through a similarity function. The second, in turn, focuses on points of interest that are visited by people, which perform some activities in these points. In addition, this dissertation also exploits the proposed methodologies in order to develop a software tool to support users in mobility analysis using complex network techniques.

The thesis proposes a 3D navigation and planning system for an autonomous remotely controlled quadcopter (drone). The solution uses the drone sensor data along with the data processed from the video camera image stream, without having any knowledge of its surroundings beforehand and without using any nav- igation signal (GPS). The video camera data are transformed into a sparse point- cloud representation, from it is created an occupancy map of the surrounding area with adaptive cell size. The planner can construct trajectory plans in the map, respecting the detected obstacles. The planned trajectory is executed by a simple drone controller. The proposed system includes a simulator which enables virtual execution of the whole process. The thesis composes originally independent and incompatible sub- systems into a single compactly working system. The functionality of the system is demonstrated on a few simple scenarios, one of which is the return of the drone to its starting location.

In recent times, as the National Aeronautics and Space Administration (NASA) focuses on establishing a sustained presence in cislunar space, there has been an increase in planned missions to the cislunar vicinity for lunar exploration. Due to this increase in planned missions, the use of cislunar structures available in the Circular Restricted Three-Body Problem (CRTBP) has become of greater interest. Traditionally, transfers that leverage CRTBP structures in the cislunar vicinity have been generated as point designs. As a consequence of the non-linearity of this model, transitioning these point designs to other epochs or mission scenarios is non-trivial. Hence, a trade space of transfer solutions, that leverage the underlying dynamics, is of interest for rapid mission design. In this study, numerical methods and dynamical systems theory are leveraged to extract available dynamical structures in the model, which are subsequently exploited for transfer design. A trade space of relatively low time of flight, two-maneuver transfers, from a 500 km altitude Low Earth Orbit (LEO) to the Earth-Moon L1 Lyapunov orbit family is generated and analyzed.

The main goal is the programming scene MATLAB/Simulink creation of graphic user interface (GUI), which allows the simulation of mobile robots movement. The work covers two types of these robots – first one is the robot with differentially controlled truck and second one auto robot (car-like robot). As a part of this draft GUI, there are also possibilities of showing all trajectory or only actual position, selection of step after which the robot can delineate and possibility of layout between the positions by using the button back and forwards.

Optimal trajectory planning methods that implement convex optimization techniques are applied to the area of satellite rendezvous and proximity operations. This involves the development of linearized relative orbital motion dynamics and constraints for two satellites, where one maintains a near-circular reference orbit. The result is formulated as a convex optimization problem, where the objective is to minimize the amount of fuel required to transfer from a given initial condition to the desired final conditions. A traditional rendezvous and proximity operations scenario is analyzed, which includes examples of initial approach, inspection, final approach, and docking trajectories. This scenario may include trajectory constraints such as maximum allowable control acceleration levels, approach corridors, and spherical keep-out zones. A second scenario that ensures passive safety, in the event of control failures on the maneuvering satellite. The convex optimization problem is ultimately formulated as a second-order cone program. Algorithm CPU and memory requirements are analyzed. Several examples of resulting optimal trajectories are presented for both scenarios, and these trajectories are implemented in a nonlinear simulation.