Medidas y extracción de parámetros de dispositivos y redes SMATV

En este Proyecto Fin de Carrera trata de dar a conocer de forma detallada el comportamiento real en frecuencia de una red de distribución SMATV y establecer un procedimiento que pueda permitir una predicción más o menos precisa de su funcionamiento. Se realizará una reflexión sobre los procedimientos de cálculo que se emplean en entornos profesionales para el diseño de estas redes y sus carencias. En concreto nos centraremos en el uso de conectores y kits de conexión que se utilizan frecuentemente en redes SMATV. A la hora de realizar un proyecto de una red de este tipo solo se tienen en cuenta las perdidas por inserción de los conectores, y en muchas ocasiones ni siquiera eso, se realiza una estimación al alza y con eso basta. Este proyecto pretende demostrar la relevancia de los conectores dentro de una red, y tratar de arrojar luz sobre los aspectos más importantes a tener en cuenta a la hora de elegir e instalar un conector. Abstract In this Thesis is to present in detail the actual behavior frequency SMATV distribution network and establish a procedure to allow more or less accurate prediction of its operation. There will be a reflection on the calculation procedures used in professional environments for the design of these networks and their shortcomings. In particular we will focus on the use of connectors and connection kits that are frequently used in SMATV networks. When a project of this type network only takes into account the insertion loss of the connectors, and often not even that, an estimate is made up and that's enough. This project aims to demonstrate the relevance of the connectors within a network, and try to shed light on the most important aspects to consider when choosing and installing a connector.

Detection and Tracking of Dynamic Objects. A MultiRobot approach to Critical Infrastructures Surveillance.

Despite that Critical Infrastructures (CIs) security and surveillance are a growing concern for many countries and companies, Multi Robot Systems (MRSs) have not been yet broadly used in this type of facilities. This dissertation presents a novel study of the challenges arisen by the implementation of this type of systems and proposes solutions to specific problems. First, a comprehensive analysis of different types of CIs has been carried out, emphasizing the influence of the different characteristics of the facilities in the design of a security and surveillance MRS. One of the most important needs for the surveillance of a CI is the detection of intruders. From a technical point of view this problem can be abstracted as equivalent to the Detection and Tracking of Mobile Objects (DATMO). This dissertation proposes algorithms to solve this specific problem in a CI environment. Using 3D range images of the environment as input data, two detection algorithms for ground robots have been developed. These detection algorithms provide a list of moving objects in the robot detection area. Direct image differentiation and computer vision techniques are used when the robot is static. Alternatively, multi-layer ground reconstructions are compared to detect the dynamic objects when the robot is moving. Since CIs usually spread over large areas, it is very useful to incorporate aerial vehicles in the surveillance MRS. Therefore, a moving object detection algorithm for aerial vehicles has been also developed. This algorithm compares the real optical flow obtained from a down-face oriented camera with an artificial optical flow computed using a RANSAC based homography matrix. Two tracking algorithms have been developed to follow the moving objects trajectories. These algorithms can efficiently handle occlusions and crossings, as well as exchange information among robots. The multirobot tracking can be applied to any type of communication structure: centralized, decentralized or a combination of both. Even more, the developed tracking algorithms are independent of the detection algorithms and could be potentially used with other detection procedures or even with static sensors, such as cameras. In addition, using the 3D point clouds available to the robots, a relative localization algorithm has been developed to improve the position estimation of a given robot with observations from other robots. All the developed algorithms have been extensively tested in different simulated CIs using the Webots robotics simulator. Furthermore, the algorithms have also been validated with real robots operating in real scenarios. In conclusion, this dissertation presents a multirobot approach to Critical Infrastructure Surveillance, mainly focusing on Detecting and Tracking Dynamic Objects.

Sintetizador analógico en Arduino

Este proyecto consiste en el diseño y construcción de un sintetizador basado en el chip 6581 Sound Interface Device (SID). Este chip era el encargado de la generación de sonido en el Commodore 64, ordenador personal comercializado en 1982, y fue el primer sintetizador complejo construido para ordenador. El chip en cuestión es un sintetizador de tres voces, cada una de ellas capaz de generar cuatro diferentes formas de onda. Cada voz tiene control independiente de varios parámetros, permitiendo una relativamente amplia variedad de sonidos y efectos, muy útil para su uso en videojuegos. Además está dotado de un filtro programable para conseguir distintos timbres mediante síntesis sustractiva. El sintetizador se ha construido sobre Arduino, una plataforma de electrónica abierta concebida para la creación de prototipos, consistente en una placa de circuito impreso con un microcontrolador, programable desde un PC para que realice múltiples funciones (desde encender LEDs hasta controlar servomecanismos en robótica, procesado y transmisión de datos, etc.). El sintetizador es controlable vía MIDI, por ejemplo, desde un teclado de piano. A través de MIDI recibe información tal como qué notas debe tocar, o los valores de los parámetros del SID que modifican las propiedades del sonido. Además, toda esa información también la puede recibir de un PC mediante una conexión USB. Se han construido dos versiones del sintetizador: una versión “hardware”, que utiliza el SID para la generación de sonido, y otra “software”, que reemplaza el SID por un emulador, es decir, un programa que se comporta (en la medida de lo posible) de la misma manera que el SID. El emulador se ha implementado en un microcontrolador Atmega 168 de Atmel, el mismo que utiliza Arduino. ABSTRACT. This project consists on design and construction of a synthesizer which is based on chip 6581 Sound Interface Device (SID). This chip was used for sound generation on the Commodore 64, a home computer presented in 1982, and it was the first complex synthesizer built for computers. The chip is a three-voice synthesizer, each voice capable of generating four different waveforms. Each voice has independent control of several parameters, allowing a relatively wide variety of sounds and effects, very useful for its use on videogames. It also includes a programmable filter, allowing more timbre control via subtractive synthesis. The synthesizer has been built on Arduino, an open-source electronics prototyping platform that consists on a printed circuit board with a microcontroller, which is programmable with a computer to do several functions (lighting LEDs, controlling servomechanisms on robotics, data processing or transmission, etc.). The synthesizer is controlled via MIDI, in example, from a piano-type keyboard. It receives from MIDI information such as the notes that should be played or SID’s parameter values that modify the sound. It also can receive that information from a PC via USB connection. Two versions of the synthesizer have been built: a hardware one that uses the SID chip for sound generation, and a software one that replaces SID by an emulator, it is, a program that behaves (as far as possible) in the same way the SID would. The emulator is implemented on an Atmel’s Atmega 168 microcontroller, the same one that is used on Arduino.

Arquitectura de Control para la Conducción Autónoma de Vehículos en Entornos Urbanos y Autovías

Hoy en día, el desarrollo tecnológico en el campo de los sistemas inteligentes de transporte (ITS por sus siglas en inglés) ha permitido dotar a los vehículos con diversos sistemas de ayuda a la conducción (ADAS, del inglés advanced driver assistance system), mejorando la experiencia y seguridad de los pasajeros, en especial del conductor. La mayor parte de estos sistemas están pensados para advertir al conductor sobre ciertas situaciones de riesgo, como la salida involuntaria del carril o la proximidad de obstáculos en el camino. No obstante, también podemos encontrar sistemas que van un paso más allá y son capaces de cooperar con el conductor en el control del vehículo o incluso relegarlos de algunas tareas tediosas. Es en este último grupo donde se encuentran los sistemas de control electrónico de estabilidad (ESP - Electronic Stability Program), el antibloqueo de frenos (ABS - Anti-lock Braking System), el control de crucero (CC - Cruise Control) y los más recientes sistemas de aparcamiento asistido. Continuando con esta línea de desarrollo, el paso siguiente consiste en la supresión del conductor humano, desarrollando sistemas que sean capaces de conducir un vehículo de forma autónoma y con un rendimiento superior al del conductor. En este trabajo se presenta, en primer lugar, una arquitectura de control para la automatización de vehículos. Esta se compone de distintos componentes de hardware y software, agrupados de acuerdo a su función principal. El diseño de la arquitectura parte del trabajo previo desarrollado por el Programa AUTOPIA, aunque introduce notables aportaciones en cuanto a la eficiencia, robustez y escalabilidad del sistema. Ahondando un poco más en detalle, debemos resaltar el desarrollo de un algoritmo de localización basado en enjambres de partículas. Este está planteado como un método de filtrado y fusión de la información obtenida a partir de los distintos sensores embarcados en el vehículo, entre los que encontramos un receptor GPS (Global Positioning System), unidades de medición inercial (IMU – Inertial Measurement Unit) e información tomada directamente de los sensores embarcados por el fabricante, como la velocidad de las ruedas y posición del volante. Gracias a este método se ha conseguido resolver el problema de la localización, indispensable para el desarrollo de sistemas de conducción autónoma. Continuando con el trabajo de investigación, se ha estudiado la viabilidad de la aplicación de técnicas de aprendizaje y adaptación al diseño de controladores para el vehículo. Como punto de partida se emplea el método de Q-learning para la generación de un controlador borroso lateral sin ningún tipo de conocimiento previo. Posteriormente se presenta un método de ajuste on-line para la adaptación del control longitudinal ante perturbaciones impredecibles del entorno, como lo son los cambios en la inclinación del camino, fricción de las ruedas o peso de los ocupantes. Para finalizar, se presentan los resultados obtenidos durante un experimento de conducción autónoma en carreteras reales, el cual se llevó a cabo en el mes de Junio de 2012 desde la población de San Lorenzo de El Escorial hasta las instalaciones del Centro de Automática y Robótica (CAR) en Arganda del Rey. El principal objetivo tras esta demostración fue validar el funcionamiento, robustez y capacidad de la arquitectura propuesta para afrontar el problema de la conducción autónoma, bajo condiciones mucho más reales a las que se pueden alcanzar en las instalaciones de prueba. ABSTRACT Nowadays, the technological advances in the Intelligent Transportation Systems (ITS) field have led the development of several driving assistance systems (ADAS). These solutions are designed to improve the experience and security of all the passengers, especially the driver. For most of these systems, the main goal is to warn drivers about unexpected circumstances leading to risk situations such as involuntary lane departure or proximity to other vehicles. However, other ADAS go a step further, being able to cooperate with the driver in the control of the vehicle, or even overriding it on some tasks. Examples of this kind of systems are the anti-lock braking system (ABS), cruise control (CC) and the recently commercialised assisted parking systems. Within this research line, the next step is the development of systems able to replace the human drivers, improving the control and therefore, the safety and reliability of the vehicles. First of all, this dissertation presents a control architecture design for autonomous driving. It is made up of several hardware and software components, grouped according to their main function. The design of this architecture is based on the previous works carried out by the AUTOPIA Program, although notable improvements have been made regarding the efficiency, robustness and scalability of the system. It is also remarkable the work made on the development of a location algorithm for vehicles. The proposal is based on the emulation of the behaviour of biological swarms and its performance is similar to the well-known particle filters. The developed method combines information obtained from different sensors, including GPS, inertial measurement unit (IMU), and data from the original vehicle’s sensors on-board. Through this filtering algorithm the localization problem is properly managed, which is critical for the development of autonomous driving systems. The work deals also with the fuzzy control tuning system, a very time consuming task when done manually. An analysis of learning and adaptation techniques for the development of different controllers has been made. First, the Q-learning –a reinforcement learning method– has been applied to the generation of a lateral fuzzy controller from scratch. Subsequently, the development of an adaptation method for longitudinal control is presented. With this proposal, a final cruise control controller is able to deal with unpredictable environment disturbances, such as road slope, wheel’s friction or even occupants’ weight. As a testbed for the system, an autonomous driving experiment on real roads is presented. This experiment was carried out on June 2012, driving from San Lorenzo de El Escorial up to the Center for Automation and Robotics (CAR) facilities in Arganda del Rey. The main goal of the demonstration was validating the performance, robustness and viability of the proposed architecture to deal with the problem of autonomous driving under more demanding conditions than those achieved on closed test tracks.

Design and kinematic analysis of 3PSS-1S wrist for needle insertion guidance

In this work it is presented a complete kinematic analysis of the 3PSS-1S parallel mechanism for its implementation as a spherical wrist for a needle insertion guidance robot. The spherical 3PSS-1S mechanism is a low weight and reduced dimension parallel mechanism that allows spherical movements providing the requirements needed for the serial–parallel robotic arm for needle insertion guidance. The solution of its direct kinematic is computed with a numerical method based on the Newton–Raphson formulation and a constraint function of the mechanism. The input–output velocity equation is obtained with the use of screw theory. Three types of singular postures are identified during simulations and verified in the real prototype. The 3PSS-1S can perform pure rotations of ±45°±45°, ±40°±40°, ±60°±60° along the View the MathML sourcex, View the MathML sourcey, View the MathML sourcez axes respectively.

A vision-based strategy for autonomous aerial refueling tasks

Autonomous aerial refueling is a key enabling technology for both manned and unmanned aircraft where extended flight duration or range are required. The results presented within this paper offer one potential vision-based sensing solution, together with a unique test environment. A hierarchical visual tracking algorithm based on direct methods is proposed and developed for the purposes of tracking a drogue during the capture stage of autonomous aerial refueling, and of estimating its 3D position. Intended to be applied in real time to a video stream from a single monocular camera mounted on the receiver aircraft, the algorithm is shown to be highly robust, and capable of tracking large, rapid drogue motions within the frame of reference. The proposed strategy has been tested using a complex robotic testbed and with actual flight hardware consisting of a full size probe and drogue. Results show that the vision tracking algorithm can detect and track the drogue at real-time frame rates of more than thirty frames per second, obtaining a robust position estimation even with strong motions and multiple occlusions of the drogue.

Piezoelectric sensors system for impact detecting

This work describes an acoustic system that allows the automatic detection and location of mechanical impacts on metallic based structures, which is suitable in robotics and industrial applications. The system is based on the time delays of propagation of the acoustic waves along the metallic based structure and it determines the instant and the position when and were the impact has been produced by piezoelectric sensors and an electronic-computerized system. We have obtained that for distance impact of 40 cm and 50 cm the time delay is 2 s and 72 s respectively.