Biologically inspired vision systems in robotics

During the last years, the International Journal of Advanced Robotic Systems, under the Topic of Vision Systems, especially welcomes papers that cover any aspect of biologically inspired vision in robots. As Guest Editors of the Special Issue on “Biologically Inspired Vision Systems in Robotics,” we feel that living beings have still much to tell us about the design and development of robotics

Hand-based interface for augmented reality

Augmented reality (AR) is a highly interdisciplinary field which has received increasing attention since late 90s. Basically, it consists of a combination of the real scene viewed by a user and a computer generated image, running in real time. So, AR allows the user to see the real world supplemented, in general, with some information considered as useful, enhancing the users perception and knowledge of the environment. Benefits of reconfigurable hardware for AR have been explored by Luk et al. [4]. However, the wide majority of AR systems have been based so far on PCs or workstation

Discrete-time cellular neural networks in FPGA

This paper describes a novel architecture for the hardware implementation of non-linear multi-layer cellular neural networks. This makes it feasible to design CNNs with millions of neurons accommodated in low price FPGA devices, being able to process standard video in real time.This research has been funded by MTyAS of Spain, IMSERSO RETVIS 150/06

Sistema de tiempo-real de código abierto para control robótico usando cultivos de neuroblastoma

Este artículo introduce un sistema de tiempo real de código abierto que controla remotamente un robot empleando cultivos de Neuroblastoma Humano y algunos principios básicos de Braitenberg. Los setups de arrays de microelectrodos han sido diseñados para cultivar directamente células neuronales sobre sustratos de silicio o cristal, proporcionando la capacidad de estimular y registrar simultáneamente la actividad del cultivo. El principal objetivo de esta investigación es modular las respuestas fisiológicas naturales de las células neuronales aplicando estimulación tetánica en el cultivo. Si el sistema es capaz de modificar las respuestas selectivas de algunas células con un patrón de estímulos externo proporcionado por un robot sobre diferentes escalas de tiempo, la estructura cultivada de neuroblastoma puede ser entrenada para procesar patrones espacio-temporales pre-programados, controlando de esta forma el comportamiento robótico.Asociación de Jóvenes Investigadores de Cartagena, (AJICT). Universidad Politécnica de Cartagena. Escuela Técnica Superior de Ingeniería Industrial UPCT, (ETSII). Escuela Técnica Superior de Ingeniería Agronómica, (ETSIA), Escuela Técnica Superior de Ingeniería de Telecomunicación (ETSIT). Escuela de Ingeniería de Caminos, Canales, y Puertos y de Ingeniería de Minas, (EICM). Fundación Séneca, Agencia Regional de Ciencia y Tecnología. Parque Tecnológico de Fuente Álamo. Grupo Aquilin

HANNA: a tool for hardware prototyping and benchmarking of ANNs. Poster

For some applications, designers must implement an ANN model over different platforms to meet performance, cost or power constrains, a process still more painful when several hardware implementations have to be evaluated. Continuous advances in VLSI technologies, computer architecture and software development make it difficult to find the adequate implementation platform. HANNA (Hardware ANN Architect), is a tool designed to automate the generation of hardware prototypes of MLP-like neural networks over FPGA devices. Coupled with traditional Matlab/Simulink environments the model can be synthesized, downloaded to the FPGA and co-simulated with the software version to trade off area, speed and precision requirements.This research is being funded by Ministerio de Ciencia y Tecnología TIC 2003-09557-C02-02

A multi-FPGA distributed embedded system for the emulation of Multi-Layer CNNs in real time video applications

This paper describes the design and the implementation of an embedded system based on multiple FPGAs that can be used to process real time video streams in standalone mode for applications that require the use of large Multi-Layer CNNs (ML-CNNs). The system processes video in progressive mode and provides a standard VGA output format. The main features of the system are determined by using a distributed computing architecture, based on Independent Hardware Modules (IHM), which facilitate system expansion and adaptation to new applications. Each IHM is composed by an FPGA board that can hold one or more CNN layers. The total computing capacity of the system is determined by the number of IHM used and the amount of resources available in the FPGAs. Our architecture supports traditional cloned templates, but also the (simultaneous) use of time-variant and space-variant templates.This work has been partially supported by the Fundación Séneca de la Región de Murcia through the research projects 08801/PI/08 and 08788/PI/08, and by the Spanish Government through project TIN2008-06893-C03

Inner-Hair Cells Parameterized-Hardware Implementation for Personalized Auditory Nerve Stimulation

In this paper the hardware implementation of an inner hair cell model is presented. Main features of the design are the use of Meddis’ transduction structure and the methodology for Design with Reusability. Which allows future migration to new hardware and design refinements for speech processing and custom-made hearing aid

Bio-inspired broad-class phonetic labelling

Recent studies have shown that the correct labeling of phonetic classes may help current Automatic Speech Recognition (ASR) when combined with classical parsing automata based on Hidden Markov Models (HMM).Through the present paper a method for Phonetic Class Labeling (PCL) based on bio-inspired speech processing is described. The methodology is based in the automatic detection of formants and formant trajectories after a careful separation of the vocal and glottal components of speech and in the operation of CF (Characteristic Frequency) neurons in the cochlear nucleus and cortical complex of the human auditory apparatus. Examples of phonetic class labeling are given and the applicability of the method to Speech Processing is discussed

Hardware implementation of a controller based on neurobiological adaptive models of the human motor-control system

In this work, a neural structure has been implemented into a device based on the new trends in hardware integration, for motor-control In multisensorial anthropomorphic robotic systems. This implementation gives a solution to the problem of physic integration of biologically Inspired control hierarchies in a robotic head-arm installation for robotic reaching tasks. The complete architecture has been implemented on an electronic board connected to a PC computer through a PCI interface. The hardware structure consists of two blocks: one for the working phase of the system, and the other for the learning and supervision phase of the system. These two blocks have been implemented with different technologies based on DSP processors and FPGAs. The algorithms implemented on DSPs have the function of updating the neural network on the FPGA, supervising the working of the algorithm implemented on FPGA and introducing corrections when the neural network produces results with little errors. The neural network has been implemented on FPGA and implements spatial-motor transformations of the robotic platform. It is programmed and updated by the supervisor implemented on a DSP processo

Utilización de FPGAs para el procesamiento digital de video

Este trabajo muestra alguna de las técnicas de procesamiento digital de video desarrolladas por el grupo de Hardware Reconfigurable del Dpto. de Electrónica, Tecnología de Computadoras y Proyectos de la UPCT. En el se resume la implementación de diversos algoritmos de procesamiento, los cuales plantean diferentes alternativas para la obtención de bordes de imágenes de video en tiempo real. Los algoritmos que se proponen son: extracción de bordes mediante el método del gradiente, algoritmo de CANNY y un método basado en redes neuronales celulares discretas (DT-CNN). Todas las implementaciones realizadas poseen como elemento común la utilización de dispositivos lógicos reconfigurables (FPGAs), cuya aportación principal al desarrollo es conseguir la aceleración hardware necesaria para procesar las imágenes de video a alta velocidad y en el mínimo espacio posible.Estos trabajos se realizan en el marco de los proyectos de investigación TIC 2003-09557-C02-02 y TIC 2003-09400-C04-02 del MCYT