Online consolidation fiber placement is emerging as an automated manufacturing process for the fabrication of large composite material complex structures. While traditional composite manufacturing techniques limited the products' size, geometrical shapes and laminate patterns, robotic automation of the fiber placement process allows the manufacture of complex bodies with any desired surface pattern or towpreg's direction. Therefore, a complete understanding of the robot kinematic capabilities should be made to accurately position the structure's substrate in the workcell and to compute the feasible product dimensions and sizes. A Matlab algorithm is developed to verify the feasibility of straight-line trajectory paths and to locate all valid towpreg segments in the workspace, with no focus on optimization. The algorithm is applied preliminary to a three-link planar arm; and a 6-dof Merlin robot is subsequently considered to verify the towpreg layouts in the three-dimensional space. The workspace is represented by the longest feasible segments and plotted on parallel two-dimensional planes. The analysis is extended to locate valid square areas with predetermined dimensions. The fabrication of isotropic circular coupons is then tested with two different compaction heads. The results allow the formulation of a geometric correlation between the end-effector dimensional measures and the orientation of the end-effector with respect to the towpreg segments. / Master of Science

Every year, the ports of entry of the continental United States receive millions of containers from container ships for processing. These containers contain everything that the country imports, and sometimes regulated items can be hidden inside them in attempt to smuggle them illegally into the country. Some of these items may be radioactive material meant for criminal purposes and represent a threat to national security. The containers are currently being scanned for radioactivity as they leave the port, but before leaving the port, containers can sit inside the port for weeks. It can be beneficial to scan these containers before they are picked up to catch the illegal material sooner and reduce the risk of danger to those nearby. Uncrewed Aerial Systems can be useful for scanning container stacks in container fields since they can be attached with sensors and reach heights that are difficult for humans. They can also scan autonomously, requiring less over watch from people. This thesis attempts to solve the problem of autonomous search by using an initial 3D scan of the search area to input into a 3D path planning algorithm to generate a flight path that will sufficiently scan the search area while minimizing flight time. Coverage is a main area of concern, as well is computational complexity and time. In order to maintain security of the aircraft, the path must be generated on-board the aircraft, and as such use on-board, lightweight, computers. The approach taken in this thesis is by breaking the problem down into 2D layers, and then developing paths on each layer based on where the obstacles are. In order to maximize coverage, contours are generated around the obstacles. The vertices of the contours are then treated like points to visit in a Travelling Salesman Problem. To incentivize paths that run alongside the obstacles for better radiation detection, paths that do not run close to the obstacles are given a higher cost than those that do, resulting in a cost-minimizing path planning algorithm yielding paths that stay close to obstacles. The Travelling Salesman Problem algorithm then yields the most time effective path to cover the area while maintaining a distance healthy for radiation scanning from the obstacles. / Master of Science / Every year, the ports of entry of the continental United States receive millions of containers from container ships for processing. These containers contain everything that the country imports, and sometimes regulated items can be hidden inside them in attempt to smuggle them illegally into the country. Some of these items may be radioactive material meant for criminal purposes and represent a threat to national security. It can be beneficial to scan these containers before they are picked up to catch the illegal material sooner and reduce the risk of danger to those nearby. Uncrewed Aerial Systems can be useful for scanning container stacks in container fields since they can be attached with sensors and reach heights that are difficult for humans. They can also scan autonomously, requiring less over watch from people. This thesis attempts to solve the problem of autonomous search by using an initial 3D scan of the search area to input into a 3D path planning algorithm to sufficiently scan the search area while minimizing flight time.

In the past several years, the Defense Advanced Research Projects Agency (DARPA) has sponsored two Grand Challenges, races among autonomous ground vehicles in rural environments. These vehicles must follow a course delineated by Global Positioning System waypoints using no human guidance. Airborne LIDAR data and GIS can play a significant role in identifying barriers and least cost paths for such vehicles. Least cost paths minimize the sum of impedance across a surface. Impedance can be measured by steepness of slope, impenetrable barriers such as vegetation and buildings, fence lines and streams, or other factors deemed important to the vehicle's success at navigating the terrain. This research aims to provide accurate least cost paths for those vehicles using airborne LIDAR data. The concepts of barrier identification and least cost path generation are reviewed and forty-five least cost paths created with their performance compared to corresponding Euclidean paths. The least cost paths were found superior to the corresponding Euclidean paths in terms of impedance as they avoid barriers, follow roads and pass across relatively gentler slopes. / Master of Science

Underwater robotic vehicles are used in a variety of environments that would be dangerous for humans. For these vehicles to be successful, they need to be tolerant of a variety of internal and external faults. To be resilient to internal faults, the system must be capable of determining the source of faulty behavior. However many different faults within a robotic vehicle can create identical faulty behavior, which makes the vehicles impossible to diagnose using conventional methods. I propose a novel active diagnosis method for differentiating between faults that would otherwise have identical behavior. I apply this method to a communication system and a power distribution system in a robotic vehicle and show that active diagnosis is successful in diagnosing partially observable faults. An example of an external fault is inter-robot communication in underwater robotics. The primary communication method for underwater vehicles is acoustic communication which relies heavily on line-of-sight tracking and range. This can cause severe packet loss between agents when a vehicle is operating around obstacles. I propose novel path-planning methods for an Autonomous Underwater Vehicle (AUV) that ferries messages between agents. I applied this method to a custom underwater simulator and illustrate how it can be used to preserve at least twice as many packets sent between agents than would be obtained using conventional methods.

La representación del entorno juega un papel crucial en la navegación autónoma. A esta representación, se le suele denominar en la literatura como mapa, y su construcción suele realizarse mediante vehículos de mapeado dedicados. Sin embargo, aunque este tipo de mapas son muy precisos a nivel local, presentan el inconveniente de ser globalmente inconsistentes debido a la acumulación de pequeños errores que se hacen relevantes cuando los mapas crecen en tamaño. En la presente tesis doctoral, se propone como alternativa, la navegación autónoma basada en mapas públicos geo-referenciados. Este tipo de mapas, a diferencia de los construidos mediante vehículos de mapeado, son por naturaleza globalmente consistentes debido a que proceden de imágenes aéreas que se encuentran geo-referenciadas. Esto, además de ser una ventaja en sí misma, conlleva otro tipo de beneficios, como la no dependencia de un proceso de mapeado, o la posibilidad de navegar sin restricciones en el tamaño del entorno. No obstante, la integración de los mapas públicos geo-referenciados introduce algunas particularidades en la implementación de los algoritmos de navegación autónoma. Durante la investigación que se expone en esta memoria, se han desarrollado diferentes métodos para abordar dichas particularidades. En el módulo de localización, la representación de mapas geo-referenciados introduce la dependencia de un tipo de marcas que deben ser observables, tanto desde imágenes por satélite, como desde los sensores locales del vehículo. Esta restricción genera representaciones escasas que, a menudo, resultan en zonas ambiguas para la asociación de datos (efecto aliasing). Para abordar estos temas, se han desarrollado diferentes métodos robustos, como Delta-Angle Lane Markings Representation, una estrategia de representación para el proceso de asociación de datos, y Distance-Compatible SAmple Consensus, un método de asociación de datos. Para mitigar el efecto del aliasing en el módulo de localización, también se han empleado capacidades de autoajuste, que modifican de manera dinámica la configuración del método de asociación de datos en función de la pseudo-entropía medida en las observaciones. Por otra parte, para el módulo de planificación de rutas, se ha desarrollado un método llamado Naive-Valley-Path que corrige las imprecisiones locales intrínsecas en los mapas públicos. Todos estos métodos han sido comparados con sus homólogos en el estado del arte, demostrando en todos los casos mejoras que han resultado en contribuciones de gran impacto para la comunidad científica. / La presente tesis doctoral ha sido financiada por la Conselleria d’Innovació, Universitats, Ciència i Societat Digital de la Generalitat Valenciana y el Fondo Social Europeo de la Unión Europea a través de las subvenciones ACIF/2019/088 y BEFPI/2021/069.

Due to the growth of wireless communication many communication frequencies have grown increasingly dense. This density requires higher Q-factor to receive only the signal of interest. With the rise of smaller integrated circuits previous solutions used for filtering have become viable again. This paper explores whether the N-path filter is viable in the modern day for radio frequency receiver purposes. A non-differential N-path filter was created by utilizing Cadence Virtuoso with a working center frequency range of 750MHz to 1GHz while using TSMC technology. The desired quality factor of over 1,000 was reached while maintaining a total area of 800 by 800 micrometers. Through the analysis of the N-path filter new techniques for mixed signal analysis were used for simulation. This included parametric analysis in Cadence ADE-L and additional analysis in MATLAB, and the addition of a bootstrapping circuit to decrease simulation time. Future applications regarding analyzing mixed signals could use these methods to provide frequency response data and automated processing.

This thesis was motivated to simulate the evacuation traffic of Mississippi Stated University (MSU) main campus using the Path-Following logic of TSIS/CORSIM and to evaluate a set of traffic management plans. Three scenarios of traffic management plans were developed and tested. A NCT of 123 minutes was projected if evacuate without any plan. In comparison, under a pre-planned traffic management plan the NCT would decrease to 39 minutes. Further, if implement contra flow the NCT would reduce to 21 minutes. If even further adjust the signal timing plans at the university exits a NCT of 20 minutes would be achieved. The sensitivity analysis found that the NCT was sensitive to the CORSIM parameters of free flow speed, time to react to sudden deceleration of lead vehicle and the configuration of driver type, while the effects of discharge headway and start up lost time were not found to be significant.

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