Transformation and dynamic visualization of images from computer through an FPGA in a matrix of LED

This article shows the implementation of a system that uses a graphic interface to load a digital image into a programmable logic device, which is stored in its internal RAM memory and is responsible for visualizing it in a matrix of RGB LEDs, so that This way, the LEDs show an equivalent to the image that was sent from the PC, conserving an aspect ratio and respecting as much as possible the color of the original image. To carry out this task, a Matlab script was designed to load the image, convert and format the data, which are transmitted to the FPGA using the RS232 protocol. The FPGA is in charge of receiving them, storing them and generating all the signals of control and synchronization of the system including the control of the PWM signals necessary to conserve the brightness of each one of the LEDs. This system allows the visualization of static images in standard formats and, in addition, thanks to the flexibility of the hardware used, it allows the visualization of moving images type GIF

Design of a controller for wheeled mobile robots based on automatic movement sequencing

There are many kinds of robots and among them the wheeled mobile robots (WMR) stand out, because they are relatively cheap and easy to build. These features make WMRs the test prototypes for control strategies or motion generation. In general, the controllers developed are based on sensory schemes that give an WMR the ability to travel through flat or obstructed environments. However, these strategies are highly reactive, i.e. they are based on the control-action scheme and are not adaptive; or, they are motion schemes built from simulations that assume the environmental conditions to determine the robot's path. In both cases, WMRs do not adapt perfectly to the change of environment, since the controller does not find appropriate movements for the  robot to move from one point to another. Therefore, this article proposesapartial solution to this problem, with a controller that generates sets of adaptive movements for an WMR to travel around its environment from the sensory perception information

Strategy to determine the foot plantar center of pressure of a person through deep learning neural networks

Some case studies treated by physiotherapists or orthopedists to measure the alignment of the lower extremities during a gait cycle are based on empirical methods of visual observation. This methodology does not guarantee total success, since it depends on the experience of the specialist, what can cause irreversible damage to patients, such as: hip displacement, wear and overload of the joints of a single lower limb. Although, this problem has been addressed in the investigation by means of devices implementation with sensors or methods of processing sequences of images and videos, this topic is still under investigation because the current methods depend on many external elements and data given by an expert in the area. Therefore, this paper proposes a partial solution to this problem by systematizing the experience of a specialist through a computational learning method

Recognition system for facial expression by processing images with deep learning neural network

The recognition systems of patterns in images are mechanisms that filter the information that provides an image to highlight the area of interest for the user. Usually, these mechanisms are based on mathematical transformations that allow the processor to perform interpretations based on the geometry or shape of the image. However, the strategies that implement mathematical transformations are limited, since the effectiveness of these techniques is reduced by changing the morphology or resolution of the image. This paper presents a partial solution to this limitation with a digital image processing technique based on a deep learning neural network (DNN). This technique incorporates a mechanism that allows the DNN to determine the facial expression of a person, based on the segmented information of the image of their face. By segmenting the image and processing its characteristics in parallel, the proposed technique increases the effectiveness of recognizing facial gestures in different images even when modifying their characteristics

Low cost, high performance fuel cell energy conditioning system controlled by neural network

Fuel cells are an important option for the generation of renewable, efficient and environmentally friendly electricity. Although there are commercial applications in the industrial, residential and automotive sectors, it is not yet a mature technology and requires much research, particularly to reduce its costs to a level competitive with other technologies. This research is currently focused not only on the structure of the cell but also on the additional elements and sub systems required for its implementation as an energy solution. In this article, we propose an electrical energy conditioning scheme for the Formic acid fuel cell (direct formic acid fuel cellor DFAFC). This fuel cell was selected for its high performance, and low cost in low and medium power applications. The proposed system consists of a direct current-direct current (DC-DC) regulator supported by a power converter controlled by a Cortex-M3 ARM processor. This CPU is used to propagate a static neural network trained with the non-linear dynamics of the power converter. The power circuit is modeled and simulated to produce  the training parameters. The neural network is trained externally and runs off-line on the processor. The results show not only the regulation capacity of the control scheme but also its response speed to sudden changes in the load

Ecualizador gráfico usando sistema de desarrollo con arquitectura ARM

En el presente artículo se desarrolla un ecualizador gráfico de cinco bandas utilizando un dispositivo con arquitectura ARM y Android 2.3  como sistema operativo. El ecualizador funciona indirectamente como un reproductor de audio. La aplicación diseñada hace uso de librerías nativas de Android, algunas de ellas funcionales a partir del API 9 (Versión 2.3). Para la interacción con el usuario, esta aplicación dispone de dos actividades, la principal donde se captura el audio y donde se establece la variación de la ganancia de cada una de las bandas del ecualizador, y la segunda que muestra los archivos con extensión de audio que se encuentren en la memoria externa del dispositivo

Diseño de plataformas robóticas diferenciales conectadas en topología Mesh para tecnología Zigbee en entornos cooperativos

Este artículo muestra el desarrollo de un sistema de navegación basado en robótica tipo enjambre con un computador y tres plataformas diferenciales. El computador actúa como coordinador y las plataformas como routers haciendo uso del protocolo de comunicación ZigBee. Por medio de los módulos X-bee serie 2, un sensor ultrasónico y un odómetro, se estructura un esquema de control cooperativo con una interfaz gráfica configurable para el control de individual de los robots. El sistema se validó sobre prototipos reales demostrando un alto desempeño y versatilidad de uso

Metodología para el uso de la técnica de localización de raíces en la planeación de rutas para robots móviles

This paper shows the analysis and the implementation methodology of the technique of dynamic systems roots location used in free-obstacle path planning for mobile robots. First of all, the analysis and morphologic behavior identification of the paths depending on roots location in complex plane are performed, where paths type and their attraction and repulsion features in the presence of other roots similarly to the obtained with artificial potential fields are identified. An implementation methodology for this technique of mobile robots path planning is proposed, starting from three different methods of roots location for obstacles in the scene. Those techniques change depending on the obstacle key points selected for roots, such as borders, crossing points with original path, center and vertices. Finally, a behavior analysis of general technique and the effectiveness of each tried method is performed, doing 20 tests for each one, obtaining a value of 65% for the selected method. Modifications and possible improvements to this methodology are also proposed.Este artículo presenta el análisis y la metodología de implementación de la técnica de localización de raíces de sistemas dinámicos para la planeación de rutas libres de obstáculos para robots móviles. En primera instancia, se realiza un análisis e identificación del comportamiento morfológico de las trayectorias en dependencia de la ubicación de las raíces en el plano complejo, identificándose el tipo de trayectorias curvas y la característica de atracción y repulsión de estas en presencia de otras raíces, de forma similar al obtenido con la técnica de cargas de potencial artificial. Se plantea una metodología para implementación de esta técnica para la planeación de rutas de robots móviles, partiendo de tres métodos diferentes de ubicación de las raíces para los obstáculos presentes en el escenario. Dichas técnicas varían dependiendo de los puntos clave del obstáculo que son seleccionados para las raíces, tales como los bordes, los cruces con las trayectoria original, el centro y los vértices. Finalmente, se realiza un análisis de funcionamiento de la técnica en general y de la efectividad cada uno de los métodos evaluados, bajo 20 pruebas para cada uno, obteniendo un valor del 65% para el método seleccionado. También se proponen modificaciones o posibles mejoras a la metodología propuesta

Uso de redes neuronales para el reconocimiento de rostros en ambientes controlados

This paper discusses the implementation and validation of neural networks for face recognition in controlled environments, an implementation strategy that consists of 3 stages: acquisition, extraction of facial parameters and validation using neural networks is presented. This paper seeks to validate the operation of two neural networks in particular for face recognition, these are the Perceptron and ART. We seek to analyze and validate through a series of tests the possible operation of this type of neural networks in biometric identification systems and access control.Este artículo presenta la implementación y validación de redes neuronales para el reconocimiento de rostros en entornos controlados, se presenta una estrategia de implementación que consta de 3 etapas: adquisición, extracción de parámetros faciales y validación mediante redes neuronales. Este trabajo busca validar el funcionamiento de dos redes neuronales en particular para el reconocimiento de rostros, estas son el Perceptron y la ART. se busca analizar y validar mediante una serie de pruebas el posible funcionamiento de este tipo de redes neuronales en sistemas biométricos de identificación y control de acceso