Monte Carlo Set-Membership Filtering for Nonlinear Dynamic Systems

This chapter considers the nonlinear filtering problem involving noises that are unknown and bounded. We propose a new filtering method via set-membership theory and boundary sampling technique to determine a state estimation ellipsoid. In order to guarantee the online usage, the nonlinear dynamics are linearized about the current estimate, and the remainder term is then bounded by an optimization ellipsoid, which can be described as the solution of a semi-infinite optimization problem. It is an analytically intractable problem for general nonlinear dynamic systems. Nevertheless, for a typical nonlinear dynamic system in target tracking, some certain regular properties for the remainder are analytically derived; then, we use a randomized method to approximate the semi-infinite optimization problem efficiently. Moreover, for some quadratic nonlinear dynamic systems, the semi-infinite optimization problem is equivalent to solving a semi-definite program problem. Finally, the set-membership prediction and measurement update are derived based on the recent optimization method and the online bounding ellipsoid of the remainder other than a priori bound. Numerical example shows that the proposed method performs better than the extended set-membership filter, especially in the situation of the larger noise

State Estimation with Sets of Densities considering Stochastic and Systematic Errors

In practical applications, state estimation requires the consideration of stochastic and systematic errors. If both error types are present, an exact probabilistic description of the state estimate is not possible, so that common Bayesian estimators have to be questioned. This paper introduces a theoretical concept, which allows for incorporating unknown but bounded errors into a Bayesian inference scheme by utilizing sets of densities. In order to derive a tractable estimator, the Kalman filter is applied to ellipsoidal sets of means, which are used to bound additive systematic errors. Also, an extension to nonlinear system and observation models with ellipsoidal error bounds is presented. The derived estimator is motivated by means of two example applications

Affective computing in a T-Learning application

This paper presents T-EDUCO, the first t-learning affective aware tutoring tool. T-EDUCO goes further than simply broadcasting an interactive educational application by allowing the figure of a tutor to be present and to govern the students’ learning process. The tutor can access academic and emotional information about the students through a continuous “emotional path” that includes timestamps and information about the progress made in each exercise. In this way, personal messages or extra educational contents for improving learning can be sent to the students. All this is made possible by a combination of broadcast and broadband technologiesFacultad de Informátic

Nonlinear Model Predictive Control Considering Stochastic and Systematic Uncertainties with Sets of Densities

In Model Predictive Control, the quality of control is highly dependent upon the model of the system under control. Therefore, a precise deterministic model is desirable. However, in real-world applications, modeling accuracy is typically limited and systems are generally affected by disturbances. Hence, it is important to systematically consider these uncertainties and to model them correctly. In this paper, we present a novel Nonlinear Model Predictive Control method for systems affected by two different types of perturbations that are modeled as being either stochastic or unknown but bounded quantities. We derive a formal generalization of the Nonlinear Model Predictive Control principle for considering both types of uncertainties simultaneously, which is achieved by using sets of probability densities. In doing so, a more robust and reliable control is obtained. The capabilities and benefits of our approach are demonstrated in real-world experiments with miniature walking robots

Evaluación de un sistema multimodal de reconocimiento de emociones

En el presente Trabajo Fin de Máster se ha llevado a cabo la implementación y evaluación de un algoritmo de fusión multimodal para detección de emociones propuesto anteriormente. Ello ha implicado la realización de las siguientes tareas: La mejora del módulo de detección facial previo, permitiendo la detección de expresiones faciales de forma automática y posibilitando el procesado de largas secuencias de vídeo. El desarrollo de un módulo de detección de emociones en texto, basado en el diccionario de Whissell, capaz de proporcionar una salida emocional en el espacio continuo. El desarrollo de una aplicación, en forma de mensajería instantánea, que permite a dos usuario interactuar emocionalmente por medio de expresiones faciales (vídeo), texto y emoticonos y que recoge todos los datos necesarios para el posterior cálculo de las salidas emocionales de cada uno de los módulos estudiados. La implementación del algoritmo de fusión y la prueba de su funcionamiento gracias a los módulos faciales, de texto y a los emoticonos. El diseño de un método de evaluación para sistemas de detección de emociones continuas y el desarrollo de todas las herramientas necesarias para su aplicación. Dicho método ha sido empleado para estudiar el efecto de la fusión multimodal en las tasas de acierto. El análisis de los resultados obtenidos, identificando las virtudes y los defectos tanto del algoritmo de fusión como del módulo de detección facial

Simultaneous Tracking and Shape Estimation of Extended Objects

This work is concerned with the simultaneous tracking and shape estimation of a mobile extended object based on noisy sensor measurements. Novel methods are developed for coping with the following two main challenges: i) The computational complexity due to the nonlinearity and high-dimensionality of the problem and ii) the lack of statistical knowledge about possible measurement sources on the extended object

Simultaneous Tracking and Shape Estimation of Extended Objects

This work is concerned with the simultaneous tracking and shape estimation of a mobile extended object based on noisy sensor measurements. Novel methods are developed for coping with the following two main challenges: i) The computational complexity due to the nonlinearity and high-dimensionality of the problem, and ii) the lack of statistical knowledge about possible measurement sources on the extended object

State Estimation for Distributed Systems with Stochastic and Set-membership Uncertainties

State estimation techniques for centralized, distributed, and decentralized systems are studied. An easy-to-implement state estimation concept is introduced that generalizes and combines basic principles of Kalman filter theory and ellipsoidal calculus. By means of this method, stochastic and set-membership uncertainties can be taken into consideration simultaneously. Different solutions for implementing these estimation algorithms in distributed networked systems are presented

Anales de jAUTI 2012 : I Jornadas Iberoamericanas de Difusión y Capacitación sobre Aplicaciones y Usabilidad de la Televisión Digital Interactiva

La RedAUTI tiene como objetivo principal apoyar la formación de los recursos humanos, estimular la investigación de forma transdisciplinaria y fortalecer los grupos de investigación de las universidades iberoamericanas en temas relacionados con TVDI, avanzando en el diseño, implementación y despliegue de aplicaciones, servicios y producción de contenidos para TVDI, en sus múltiples plataformas, de código abierto, de interés colectivo, para dar solución a problemas del contexto iberoamericano. Entre sus objetivos particulares se propone la realización de un evento anual de difusión abierto a la comunidad donde se ofrezcan charlas, por parte de los investigadores integrantes de la RedAUTI, relacionadas con el desarrollo de aplicaciones interactivas y contenidos para TVDI, estimulando la cultura local y el interés por innovación tecnológica entre los jóvenes Esta publicación es el resultado del primer evento organizado durante el primer año de actuación de la RedAUTI: "I Jornadas Iberoamericanas de Difusión y Capacitación sobre Aplicaciones y Usabilidad de la Televisión Digital Interactiva. jAUTI2012", realizadas en el mes de octubre de 2012 en la Facultad de Informática de la Universidad Nacional de La Plata, La Plata, Argentina.Facultad de Informátic