BRAIN COMPUTER INTERFACE - Application of an Adaptive Bi-stage Classifier based on RBF-HMM

Brain Computer Interface is an emerging technology that allows new output paths to communicate the users intentions without the use of normal output paths, such as muscles or nerves. In order to obtain their objective, BCI devices make use of classifiers which translate inputs from the users brain signals into commands for external devices. This paper describes an adaptive bi-stage classifier. The first stage is based on Radial Basis Function neural networks, which provides sequences of pre-assignations to the second stage, that it is based on three different Hidden Markov Models, each one trained with pre-assignation sequences from the cognitive activities between classifying. The segment of EEG signal is assigned to the HMMwith the highest probability of generating the pre-assignation sequence. The algorithm is tested with real samples of electroencephalografic signal, from five healthy volunteers using the cross-validation method. The results allow to conclude that it is possible to implement this algorithm in an on-line BCI device. The results also shown the huge dependency of the percentage of the correct classification from the user and the setup parameters of the classifier

Seguimiento de óptimos en movimiento a través de predicciones basadas en filtros de Kalman

Los problemas de optimización dinámica tratan con entornos variables. En este artículo se presentan varias técnicas para integrar información de movimiento en un algoritmo genético, cuando la función de fitness cambia con el tiempo y los cambios en el óptimo siguen una ley no basada en el azar. Se propone un mecanismo para estimar dicha ley con elfin de mejorar la capacidad de seguimiento del optimo, que finalmente se prueba con una aplicación de seguimiento de objetos en movimiento para un sistema de visión artificial

Miniature Quad-rotor Dynamics Modeling & Guidance for Vision-based Target Tracking Control Tasks

This paper presents the dynamics modeling and the control & guidance architecture for specific target tracking indoors tasks using a miniature quad-rotor. Our objective is to develop a testbed using Matlab for experimentation and simulation of dynamics, control and guidance methods within a strong interplay between the hardware on board and software provisioned

A waypoint-based mission planner for a farmland coverage with an aerial robot - a precision farming tool

Remote sensing (RS) with aerial robots is becoming more usual in every day time in Precision Agriculture (PA) practices, do to their advantages over conventional methods. Usually, available commercial platforms providing off-the-shelf waypoint navigation are adopted to perform visual surveys over crop fields, with the purpose to acquire specific image samples. The way in which a waypoint list is computed and dispatched to the aerial robot when mapping non empty agricultural workspaces has not been yet discussed. In this paper we propose an offline mission planner approach that computes an efficient coverage path subject to some constraints by decomposing the environment approximately into cells. Therefore, the aim of this work is contributing with a feasible waypoints-based tool to support PA practice

Brain Computer Interface. Comparison of Neural Networks Classifiers.

Brain Computer Interface is an emerging technology that allows new output paths to communicate the user’s intentions without use of normal output ways, such as muscles or nerves (Wolpaw, J. R.; et al., 2002).In order to obtain its objective BCI devices shall make use of classifier which translate the inputs provided by user’s brain signal to commands for external devices. The primary uses of this technology will benefit persons with some kind blocking disease as for example: ALS, brainstem stroke, severe cerebral palsy (Donchin et al., 2000).This report describes three different classifiers based on three different types of neural networks: Radial Basis Functions RBF, Probabilistic Neural Networks PNN, and Multi-Layer Perceptions MLP. The report compares the results produced by them in order to obtain conclusions to apply to an on-line BCI device; it also describes the experimental procedure followed in the experiments. As result of the tests carried out on five healthy volunteers an estimation of the success rate for each type of classifier, the type and architecture of the classifier, and filtering windows are established

Feedback effect analysis by comparison of discrimination capability of On-line and Off-line experimental procedures based on LDA

This paper analyses the user’s feedback influence in the mental task discrimination capability through the comparison of results obtained from Off-line and On-line Brain Computer Interface experimental procedures. Experiments performed under these two paradigms were carried out by five male volunteers. In order to develop a wearable BCI device only two electrodes in C3 and C4 zones have been used for electroencephalographic signal acquisition. These procedures apply seven different types of preprocessing windows and Linear Discrimination Analysis technique to reduce the dimension of the feature space before the quantification of the discrimination capability between the proposed mental activities. The discrimination capability is quantified through statistical analysis, based on bilateral contrast test, between the population of the LDA transformed feature vectors

Planificador de Objetivos Supeditados a una Mision Prioritaria

Este capítulo presenta un sistema de planificación de objetivos que se basa en una planificación previa de mayor prioridad para desarrollar una misión secundaria supeditada a la primera. Esta aproximación se aplica tanto en simulación como con una implementación real a un escenario de exploración planetaria, En él, tomando como misión principal el reconocimiento y toma de muestras, se desarrolla como misión secundaria despliegue de una red de sensors inalámbricos

Simultaneous Task Subdivision and Assignment in the FRACTAL Multi-robot System

This paper presents a negotiation protocol for simultaneous task subdivision and assignment in a heterogeneous multi-robot system. The protocol is based on an abstraction of the concept of task that allows it to be applied independently on the actual task, and adopts Rubinsteins’s alternate offers protocol extended with a co-evolutionary step in search for the best (counter)-offer. The protocol has been tested on computer simulated application scenarios

Sma control for bio-mimetic fish locomotion

In this paper, we describe our current work on bio-inspired locomotion systems using smart materials. The aim of this work is to investigate alternative actuation mechanisms based on smart materials, exploring the possibility of building motor-less and gear-less robots. A swimming underwater robot is being developed whose movements are generated using such materials, concretely Shape Memory Alloys. This paper focuses on the actuators control in order to generate the desired motion pattern

Simulación de un Sistema de Navegación para un Grupo de Robots de Exteriores Utilizando Microsoft Robotics Developer Studio

El sistema de navegación es una de las principales diferencias entre los robots de interiores y los de exteriores. Habitualmente los sistemas que trabajan en exteriores pueden contar con la información proveniente de sensores GNSS que proporcionan una solución de navegación que puede alcanzar precisiones centimétricas en tiempo real, pero que pueden tener una disponibilidad muy reducida en ciertos entornos como los urbanos. Esta baja disponibilidad obliga a disponer de sistemas adicionales que permitan navegar al robot de una forma segura cuando esta información no está disponible, siendo el más habitual la odometría, que puede aportar soluciones robustas con una precisión razonable en entornos principalmente planos. Trabajar con robots de exteriores supone en muchas ocasiones sufrir muchas restricciones a la hora de realizar validaciones o experimentos por lo que los sistemas de simulación se convierten en una excelente herramienta para sus desarrolladores. En este capítulo, se presenta cómo se ha desarrollado un sistema de navegación para robots de exteriores utilizando la herramienta Microsoft Robotics Developer Studio y cómo esta solución puede ser escalada a un conjunto de robots gracias al uso de las librerías de creación y administración de procesos concurrentes y distribuidos, CCR y DSS, propias de esta herramienta