21 resultados para bio-inspired foams

em Universidad Politécnica de Madrid


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A generic bio-inspired adaptive architecture for image compression suitable to be implemented in embedded systems is presented. The architecture allows the system to be tuned during its calibration phase. An evolutionary algorithm is responsible of making the system evolve towards the required performance. A prototype has been implemented in a Xilinx Virtex-5 FPGA featuring an adaptive wavelet transform core directed at improving image compression for specific types of images. An Evolution Strategy has been chosen as the search algorithm and its typical genetic operators adapted to allow for a hardware friendly implementation. HW/SW partitioning issues are also considered after a high level description of the algorithm is profiled which validates the proposed resource allocation in the device fabric. To check the robustness of the system and its adaptation capabilities, different types of images have been selected as validation patterns. A direct application of such a system is its deployment in an unknown environment during design time, letting the calibration phase adjust the system parameters so that it performs efcient image compression. Also, this prototype implementation may serve as an accelerator for the automatic design of evolved transform coefficients which are later on synthesized and implemented in a non-adaptive system in the final implementation device, whether it is a HW or SW based computing device. The architecture has been built in a modular way so that it can be easily extended to adapt other types of image processing cores. Details on this pluggable component point of view are also given in the paper.

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Providing security to the emerging field of ambient intelligence will be difficult if we rely only on existing techniques, given their dynamic and heterogeneous nature. Moreover, security demands of these systems are expected to grow, as many applications will require accurate context modeling. In this work we propose an enhancement to the reputation systems traditionally deployed for securing these systems. Different anomaly detectors are combined using the immunological paradigm to optimize reputation system performance in response to evolving security requirements. As an example, the experiments show how a combination of detectors based on unsupervised techniques (self-organizing maps and genetic algorithms) can help to significantly reduce the global response time of the reputation system. The proposed solution offers many benefits: scalability, fast response to adversarial activities, ability to detect unknown attacks, high adaptability, and high ability in detecting and confining attacks. For these reasons, we believe that our solution is capable of coping with the dynamism of ambient intelligence systems and the growing requirements of security demands.

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In this work, we propose the Networks of Evolutionary Processors (NEP) [2] as a computational model to solve problems related with biological phenomena. In our first approximation, we simulate biological processes related with cellular signaling and their implications in the metabolism, by using an architecture based on NEP (NEP architecture) and their specializations: Networks of Polarized Evolutionary Processors (NPEP) [1] and NEP Transducers (NEPT) [3]. In particular, we use this architecture to simulate the interplay between cellular processes related with the metabolism as the Krebs cycle and the malate-aspartate shuttle pathway (MAS) both being altered by signaling by calcium.

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n this paper we propose the use of Networks of Bio-inspired Processors (NBP) to model some biological phenomena within a computational framework. In particular, we propose the use of an extension of NBP named Network Evolutionary Processors Transducers to simulate chemical transformations of substances. Within a biological process, chemical transformations of substances are basic operations in the change of the state of the cell. Previously, it has been proved that NBP are computationally complete, that is, they are able to solve NP complete problems in linear time, using massively parallel computations. In addition, we propose a multilayer architecture that will allow us to design models of biological processes related to cellular communication as well as their implications in the metabolic pathways. Subsequently, these models can be applied not only to biological-cellular instances but, possibly, also to configure instances of interactive processes in many other fields like population interactions, ecological trophic networks, in dustrial ecosystems, etc.

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This paper presents a new simulation environment aimed at heterogeneous chained modular robots. This simulator allows testing the feasibility of the design, checking how modules are going to perform in the field and verifying hardware, electronics and communication designs before the prototype is built, saving time and resources. The paper shows how the simulator is built and how it can be set up to adapt to new designs. It also gives some examples of its use showing different heterogeneous modular robots running in different environments.

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In this paper, we describe our current work on bio-inspired locomotion systems using a deformable structure and smart materials, concretely Shape Memory Alloys, exploring the possibility of building motor-less and gear-less robots. A swimming underwater robot has been developed whose movements are generated using such actuators, used for bending the backbone of the fish, which in turn causes a change on the curvature of the body. This paper focuses on how standard swimming patterns can be reproduced with the proposed design, using an actuation dynamics model identified in prior work.

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Bats are animals that posses high maneuvering capabilities. Their wings contain dozens of articulations that allow the animal to perform aggressive maneuvers by means of controlling the wing shape during flight (morphing-wings). There is no other flying creature in nature with this level of wing dexterity and there is biological evidence that the inertial forces produced by the wings have a key role in the attitude movements of the animal. This can inspire the design of highly articulated morphing-wing micro air vehicles (not necessarily bat-like) with a significant wing-to-body mass ratio. This thesis presents the development of a novel bat-like micro air vehicle (BaTboT) inspired by the morphing-wing mechanism of bats. BaTboT’s morphology is alike in proportion compared to its biological counterpart Cynopterus brachyotis, which provides the biological foundations for developing accurate mathematical models and methods that allow for mimicking bat flight. In nature bats can achieve an amazing level of maneuverability by combining flapping and morphing wingstrokes. Attempting to reproduce the biological wing actuation system that provides that kind of motion using an artificial counterpart requires the analysis of alternative actuation technologies more likely muscle fiber arrays instead of standard servomotor actuators. Thus, NiTinol Shape Memory Alloys (SMAs) acting as artificial biceps and triceps muscles are used for mimicking the morphing wing mechanism of the bat flight apparatus. This antagonistic configuration of SMA-muscles response to an electrical heating power signal to operate. This heating power is regulated by a proper controller that allows for accurate and fast SMA actuation. Morphing-wings will enable to change wings geometry with the unique purpose of enhancing aerodynamics performance. During the downstroke phase of the wingbeat motion both wings are fully extended aimed at increasing the area surface to properly generate lift forces. Contrary during the upstroke phase of the wingbeat motion both wings are retracted to minimize the area and thus reducing drag forces. Morphing-wings do not only improve on aerodynamics but also on the inertial forces that are key to maneuver. Thus, a modeling framework is introduced for analyzing how BaTboT should maneuver by means of changing wing morphology. This allows the definition of requirements for achieving forward and turning flight according to the kinematics of the wing modulation. Motivated by the biological fact about the influence of wing inertia on the production of body accelerations, an attitude controller is proposed. The attitude control law incorporates wing inertia information to produce desired roll (φ) and pitch (θ) acceleration commands. This novel flight control approach is aimed at incrementing net body forces (Fnet) that generate propulsion. Mimicking the way how bats take advantage of inertial and aerodynamical forces produced by the wings in order to both increase lift and maneuver is a promising way to design more efficient flapping/morphing wings MAVs. The novel wing modulation strategy and attitude control methodology proposed in this thesis provide a totally new way of controlling flying robots, that eliminates the need of appendices such as flaps and rudders, and would allow performing more efficient maneuvers, especially useful in confined spaces. As a whole, the BaTboT project consists of five major stages of development: - Study and analysis of biological bat flight data reported in specialized literature aimed at defining design and control criteria. - Formulation of mathematical models for: i) wing kinematics, ii) dynamics, iii) aerodynamics, and iv) SMA muscle-like actuation. It is aimed at modeling the effects of modulating wing inertia into the production of net body forces for maneuvering. - Bio-inspired design and fabrication of: i) skeletal structure of wings and body, ii) SMA muscle-like mechanisms, iii) the wing-membrane, and iv) electronics onboard. It is aimed at developing the bat-like platform (BaTboT) that allows for testing the methods proposed. - The flight controller: i) control of SMA-muscles (morphing-wing modulation) and ii) flight control (attitude regulation). It is aimed at formulating the proper control methods that allow for the proper modulation of BaTboT’s wings. - Experiments: it is aimed at quantifying the effects of properly wing modulation into aerodynamics and inertial production for maneuvering. It is also aimed at demonstrating and validating the hypothesis of improving flight efficiency thanks to the novel control methods presented in this thesis. This thesis introduces the challenges and methods to address these stages. Windtunnel experiments will be oriented to discuss and demonstrate how the wings can considerably affect the dynamics/aerodynamics of flight and how to take advantage of wing inertia modulation that the morphing-wings enable to properly change wings’ geometry during flapping. Resumen: Los murciélagos son mamíferos con una alta capacidad de maniobra. Sus alas están conformadas por docenas de articulaciones que permiten al animal maniobrar gracias al cambio geométrico de las alas durante el vuelo. Esta característica es conocida como (alas mórficas). En la naturaleza, no existe ningún especimen volador con semejante grado de dexteridad de vuelo, y se ha demostrado, que las fuerzas inerciales producidas por el batir de las alas juega un papel fundamental en los movimientos que orientan al animal en vuelo. Estas características pueden inspirar el diseño de un micro vehículo aéreo compuesto por alas mórficas con redundantes grados de libertad, y cuya proporción entre la masa de sus alas y el cuerpo del robot sea significativa. Esta tesis doctoral presenta el desarrollo de un novedoso robot aéreo inspirado en el mecanismo de ala mórfica de los murciélagos. El robot, llamado BaTboT, ha sido diseñado con parámetros morfológicos muy similares a los descritos por su símil biológico Cynopterus brachyotis. El estudio biológico de este especimen ha permitido la definición de criterios de diseño y modelos matemáticos que representan el comportamiento del robot, con el objetivo de imitar lo mejor posible la biomecánica de vuelo de los murciélagos. La biomecánica de vuelo está definida por dos tipos de movimiento de las alas: aleteo y cambio de forma. Intentar imitar como los murciélagos cambian la forma de sus alas con un prototipo artificial, requiere el análisis de métodos alternativos de actuación que se asemejen a la biomecánica de los músculos que actúan las alas, y evitar el uso de sistemas convencionales de actuación como servomotores ó motores DC. En este sentido, las aleaciones con memoria de forma, ó por sus siglas en inglés (SMA), las cuales son fibras de NiTinol que se contraen y expanden ante estímulos térmicos, han sido usados en este proyecto como músculos artificiales que actúan como bíceps y tríceps de las alas, proporcionando la funcionalidad de ala mórfica previamente descrita. De esta manera, los músculos de SMA son mecánicamente posicionados en una configuración antagonista que permite la rotación de las articulaciones del robot. Los actuadores son accionados mediante una señal de potencia la cual es regulada por un sistema de control encargado que los músculos de SMA respondan con la precisión y velocidad deseada. Este sistema de control mórfico de las alas permitirá al robot cambiar la forma de las mismas con el único propósito de mejorar el desempeño aerodinámico. Durante la fase de bajada del aleteo, las alas deben estar extendidas para incrementar la producción de fuerzas de sustentación. Al contrario, durante el ciclo de subida del aleteo, las alas deben contraerse para minimizar el área y reducir las fuerzas de fricción aerodinámica. El control de alas mórficas no solo mejora el desempeño aerodinámico, también impacta la generación de fuerzas inerciales las cuales son esenciales para maniobrar durante el vuelo. Con el objetivo de analizar como el cambio de geometría de las alas influye en la definición de maniobras y su efecto en la producción de fuerzas netas, simulaciones y experimentos han sido llevados a cabo para medir cómo distintos patrones de modulación de las alas influyen en la producción de aceleraciones lineales y angulares. Gracias a estas mediciones, se propone un control de vuelo, ó control de actitud, el cual incorpora información inercial de las alas para la definición de referencias de aceleración angular. El objetivo de esta novedosa estrategia de control radica en el incremento de fuerzas netas para la adecuada generación de movimiento (Fnet). Imitar como los murciélagos ajustan sus alas con el propósito de incrementar las fuerzas de sustentación y mejorar la maniobra en vuelo es definitivamente un tópico de mucho interés para el diseño de robots aéros mas eficientes. La propuesta de control de vuelo definida en este trabajo de investigación podría dar paso a una nueva forma de control de vuelo de robots aéreos que no necesitan del uso de partes mecánicas tales como alerones, etc. Este control también permitiría el desarrollo de vehículos con mayor capacidad de maniobra. El desarrollo de esta investigación se centra en cinco etapas: - Estudiar y analizar el vuelo de los murciélagos con el propósito de definir criterios de diseño y control. - Formular modelos matemáticos que describan la: i) cinemática de las alas, ii) dinámica, iii) aerodinámica, y iv) actuación usando SMA. Estos modelos permiten estimar la influencia de modular las alas en la producción de fuerzas netas. - Diseño y fabricación de BaTboT: i) estructura de las alas y el cuerpo, ii) mecanismo de actuación mórfico basado en SMA, iii) membrana de las alas, y iv) electrónica abordo. - Contro de vuelo compuesto por: i) control de la SMA (modulación de las alas) y ii) regulación de maniobra (actitud). - Experimentos: están enfocados en poder cuantificar cuales son los efectos que ejercen distintos perfiles de modulación del ala en el comportamiento aerodinámico e inercial. El objetivo es demostrar y validar la hipótesis planteada al inicio de esta investigación: mejorar eficiencia de vuelo gracias al novedoso control de orientación (actitud) propuesto en este trabajo. A lo largo del desarrollo de cada una de las cinco etapas, se irán presentando los retos, problemáticas y soluciones a abordar. Los experimentos son realizados utilizando un túnel de viento con la instrumentación necesaria para llevar a cabo las mediciones de desempeño respectivas. En los resultados se discutirá y demostrará que la inercia producida por las alas juega un papel considerable en el comportamiento dinámico y aerodinámico del sistema y como poder tomar ventaja de dicha característica para regular patrones de modulación de las alas que conduzcan a mejorar la eficiencia del robot en futuros vuelos.

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Las Redes de Procesadores Evolutivos-NEP propuestas en [Mitrana et al., 2001], son un modelo computacional bio-inspirado a partir de la evolución de poblaciones de células, definiendo a nivel sintáctico algunas propiedades biológicas. En este modelo, las células están representadas por medio de palabras que describen secuencias de ADN. Informalmente, en algún instante de tiempo, el sistema evolutivo está representado por una colección de palabras cada una de las cuales representa una célula. El espacio genotipo de las especies, es un conjunto que recoge aquellas palabras que son aceptadas como sobrevivientes (es decir, como \correctas"). Desde el punto de vista de la evolución, las células pertenecen a especies y su comunidad evoluciona de acuerdo a procesos biológicos como la mutación y la división celular. éstos procesos representan el proceso natural de evolución y ponen de manifiesto una característica intrínseca de la naturaleza: el paralelismo. En este modelo, estos procesos son vistos como operaciones sobre palabras. Formalmente, el modelo de las NEP constituyen una arquitectura paralela y distribuida de procesamiento simbólico inspirada en la Máquina de conexión [Hillis, 1981], en el Paradigma de Flujo Lógico [Errico and Jesshope, 1994] y en las Redes de Procesadores Paralelos de Lenguajes (RPPL) [Csuhaj-Varju and Salomaa, 1997]. Al modelo NEP se han ido agregando nuevas y novedosas extensiones hasta el punto que actualmente podemos hablar de una familia de Redes de Procesadores Bio-inspirados (NBP) [Mitrana et al., 2012b]. Un considerable número de trabajos a lo largo de los últimos años han demostrado la potencia computacional de la familia NBP. En general, éstos modelos son computacionalmente completos, universales y eficientes [Manea et al., 2007], [Manea et al., 2010b], [Mitrana and Martín-Vide, 2005]. De acuerdo a lo anterior, se puede afirmar que el modelo NEP ha adquirido hasta el momento un nivel de madurez considerable. Sin embargo, aunque el modelo es de inspiración biológica, sus metas siguen estando motivadas en la Teoría de Lenguajes Formales y las Ciencias de la Computación. En este sentido, los aspectos biológicos han sido abordados desde una perspectiva cualitativa y el acercamiento a la realidad biológica es de forma meramente sintáctica. Para considerar estos aspectos y lograr dicho acercamiento es necesario que el modelo NEP tenga una perspectiva más amplia que incorpore la interacción de aspectos tanto cualitativos como cuantitativos. La contribución de esta Tesis puede considerarse como un paso hacia adelante en una nueva etapa de los NEPs, donde el carácter cuantitativo del modelo es de primordial interés y donde existen posibilidades de un cambio visible en el enfoque de interés del dominio de los problemas a considerar: de las ciencias de la computación hacia la simulación/modelado biológico y viceversa, entre otros. El marco computacional que proponemos en esta Tesis extiende el modelo de las Redes de Procesadores Evolutivos (NEP) y define arquitectura inspirada en la definición de bloques funcionales del proceso de señalización celular para la solución de problemas computacionales complejos y el modelado de fenómenos celulares desde una perspectiva discreta. En particular, se proponen dos extensiones: (1) los Transductores basados en Redes de Procesadores Evolutivos (NEPT), y (2) las Redes Parametrizadas de Procesadores Evolutivos Polarizados (PNPEP). La conservación de las propiedades y el poder computacional tanto de NEPT como de PNPEP se demuestra formalmente. Varias simulaciones de procesos relacionados con la señalización celular son abordadas sintáctica y computacionalmente, con el _n de mostrar la aplicabilidad e idoneidad de estas dos extensiones. ABSTRACT Network of Evolutionary Processors -NEP was proposed in [Mitrana et al., 2001], as a computational model inspired by the evolution of cell populations, which might model some properties of evolving cell communities at the syntactical level. In this model, cells are represented by words which encode their DNA sequences. Informally, at any moment of time, the evolutionary system is described by a collection of words, where each word represents one cell. Cells belong to species and their community evolves according to mutations and division which are defined by operations on words. Only those cells accepted as survivors (correct) are represented by a word in a given set of words, called the genotype space of the species. This feature is analogous with the natural process of evolution. Formally, NEP is based on an architecture for parallel and distributed processing inspired from the Connection Machine [Hillis, 1981], the Flow Logic Paradigm [Errico and Jesshope, 1994] and the Networks of Parallel Language Processors (RPPL) [Csuhaj-Varju and Salomaa, 1997]. Since the date when NEP was proposed, several extensions and variants have appeared engendering a new set of models named Networks of Bio-inspired Processors (NBP) [Mitrana et al., 2012b]. During this time, several works have proved the computational power of NBP. Specifically, their efficiency, universality, and computational completeness have been thoroughly investigated [Manea et al., 2007, Manea et al., 2010b, Mitrana and Martín-Vide, 2005]. Therefore, we can say that the NEP model has reached its maturity. Nevertheless, although the NEP model is biologically inspired, this model is mainly motivated by mathematical and computer science goals. In this context, the biological aspects are only considered from a qualitative and syntactical perspective. In view of this lack, it is important to try to keep the NEP theory as close as possible to the biological reality, extending their perspective incorporating the interplay of qualitative and quantitative aspects. The contribution of this Thesis, can be considered as a starting point in a new era of the NEP model. Then, the quantitative character of the NEP model is mandatory and it can address completely new different types of problems with respect to the classical computational domain (e.g. from the computer science to system biology). Therefore, the computational framework that we propose extends the NEP model and defines an architecture inspired by the functional blocks from cellular signaling in order to solve complex computational problems and cellular phenomena modeled from a discrete perspective. Particularly, we propose two extensions, namely: (1) Transducers based on Network of Evolutionary Processors (NEPT), and (2) Parametrized Network of Polarized Evolutionary Processors (PNPEP). Additionally, we have formally proved that the properties and computational power of NEP is kept in both extensions. Several simulations about processes related with cellular signaling both syntactical and computationally have been considered to show the model suitability.

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Los peces son animales, donde en la mayoría de los casos, son considerados como nadadores muy eficientes y con una alta capacidad de maniobra. En general los peces se caracterizan por su capacidad de maniobra, locomoción silencioso, giros y partidas rápidas y viajes de larga distancia. Los estudios han identificado varios tipos de locomoción que los peces usan para generar maniobras y natación constante. A bajas velocidades la mayoría de los peces utilizan sus aletas pares y / o impares para su locomoción, que ofrecen una mayor maniobrabilidad y mejor eficiencia de propulsión. A altas velocidades la locomoción implica el cuerpo y / o aleta caudal porque esto puede lograr un mayor empuje y aceleración. Estas características pueden inspirar el diseo y fabricación de una piel muy flexible, una aleta caudal mórfica y una espina dorsal no articulada con una gran capacidad de maniobra. Esta tesis presenta el desarrollo de un novedoso pez robot bio-inspirado y biomimético llamado BR3, inspirado en la capacidad de maniobra y nado constante de los peces vertebrados. Inspirado por la morfología de los peces Micropterus salmoides o también conocido como lubina negra, el robot BR3 utiliza su fundamento biológico para desarrollar modelos y métodos matemáticos precisos que permiten imitar la locomoción de los peces reales. Los peces Largemouth Bass pueden lograr un nivel increíble de maniobrabilidad y eficacia de la propulsión mediante la combinación de los movimientos ondulatorios y aletas morficas. Para imitar la locomoción de los peces reales en una contraparte artificial se necesita del análisis de tecnologías de actuación alternativos, como arreglos de fibras musculares en lugar de servo actuadores o motores DC estándar, así como un material flexible que proporciona una estructura continua sin juntas. Las aleaciones con memoria de forma (SMAs) proveen la posibilidad de construir robots livianos, que no emiten ruido, sin motores, sin juntas y sin engranajes. Asi es como un pez robot submarino se ha desarrollado y cuyos movimientos son generados mediante SMAs. Estos actuadores son los adecuados para doblar la espina dorsal continua del pez robot, que a su vez provoca un cambio en la curvatura del cuerpo. Este tipo de arreglo estructural está inspirado en los músculos rojos del pescado, que son usados principalmente durante la natación constante para la flexión de una estructura flexible pero casi incompresible como lo es la espina dorsal de pescado. Del mismo modo la aleta caudal se basa en SMAs y se modifica para llevar a cabo el trabajo necesario. La estructura flexible proporciona empuje y permite que el BR3 nade. Por otro lado la aleta caudal mórfica proporciona movimientos de balanceo y guiada. Motivado por la versatilidad del BR3 para imitar todos los modos de natación (anguilliforme, carangiforme, subcarangiforme y tunniforme) se propone un controlador de doblado y velocidad. La ley de control de doblado y velocidad incorpora la información del ángulo de curvatura y de la frecuencia para producir el modo de natación deseado y a su vez controlar la velocidad de natación. Así mismo de acuerdo con el hecho biológico de la influencia de la forma de la aleta caudal en la maniobrabilidad durante la natación constante se propone un control de actitud. Esta novedoso robot pescado es el primero de su tipo en incorporar sólo SMAs para doblar una estructura flexible continua y sin juntas y engranajes para producir empuje e imitar todos los modos de natación, así como la aleta caudal que es capaz de cambiar su forma. Este novedoso diseo mecatrónico presenta un futuro muy prometedor para el diseo de vehículos submarinos capaces de modificar su forma y nadar mas eficientemente. La nueva metodología de control propuesto en esta tesis proporcionan una forma totalmente nueva de control de robots basados en SMAs, haciéndolos energéticamente más eficientes y la incorporación de una aleta caudal mórfica permite realizar maniobras más eficientemente. En su conjunto, el proyecto BR3 consta de cinco grandes etapas de desarrollo: • Estudio y análisis biológico del nado de los peces con el propósito de definir criterios de diseño y control. • Formulación de modelos matemáticos que describan la: i) cinemática del cuerpo, ii) dinámica, iii) hidrodinámica iv) análisis de los modos de vibración y v) actuación usando SMA. Estos modelos permiten estimar la influencia de modular la aleta caudal y el doblado del cuerpo en la producción de fuerzas de empuje y fuerzas de rotación necesarias en las maniobras y optimización del consumo de energía. • Diseño y fabricación de BR3: i) estructura esquelética de la columna vertebral y el cuerpo, ii) mecanismo de actuación basado en SMAs para el cuerpo y la aleta caudal, iii) piel artificial, iv) electrónica embebida y v) fusión sensorial. Está dirigido a desarrollar la plataforma de pez robot BR3 que permite probar los métodos propuestos. • Controlador de nado: compuesto por: i) control de las SMA (modulación de la forma de la aleta caudal y regulación de la actitud) y ii) control de nado continuo (modulación de la velocidad y doblado). Está dirigido a la formulación de los métodos de control adecuados que permiten la modulación adecuada de la aleta caudal y el cuerpo del BR3. • Experimentos: está dirigido a la cuantificación de los efectos de: i) la correcta modulación de la aleta caudal en la producción de rotación y su efecto hidrodinámico durante la maniobra, ii) doblado del cuerpo para la producción de empuje y iii) efecto de la flexibilidad de la piel en la habilidad para doblarse del BR3. También tiene como objetivo demostrar y validar la hipótesis de mejora en la eficiencia de la natación y las maniobras gracias a los nuevos métodos de control presentados en esta tesis. A lo largo del desarrollo de cada una de las cinco etapas, se irán presentando los retos, problemáticas y soluciones a abordar. Los experimentos en canales de agua estarán orientados a discutir y demostrar cómo la aleta caudal y el cuerpo pueden afectar considerablemente la dinámica / hidrodinámica de natación / maniobras y cómo tomar ventaja de la modulación de curvatura que la aleta caudal mórfica y el cuerpo permiten para cambiar correctamente la geometría de la aleta caudal y del cuerpo durante la natación constante y maniobras. ABSTRACT Fishes are animals where in most cases are considered as highly manoeuvrable and effortless swimmers. In general fishes are characterized for his manoeuvring skills, noiseless locomotion, rapid turning, fast starting and long distance cruising. Studies have identified several types of locomotion that fish use to generate maneuvering and steady swimming. At low speeds most fishes uses median and/or paired fins for its locomotion, offering greater maneuverability and better propulsive efficiency At high speeds the locomotion involves the body and/or caudal fin because this can achieve greater thrust and accelerations. This can inspire the design and fabrication of a highly deformable soft artificial skins, morphing caudal fins and non articulated backbone with a significant maneuverability capacity. This thesis presents the development of a novel bio-inspired and biomimetic fishlike robot (BR3) inspired by the maneuverability and steady swimming ability of ray-finned fishes (Actinopterygii, bony fishes). Inspired by the morphology of the Largemouth Bass fish, the BR3 uses its biological foundation to develop accurate mathematical models and methods allowing to mimic fish locomotion. The Largemouth Bass fishes can achieve an amazing level of maneuverability and propulsive efficiency by combining undulatory movements and morphing fins. To mimic the locomotion of the real fishes on an artificial counterpart needs the analysis of alternative actuation technologies more likely muscle fiber arrays instead of standard servomotor actuators as well as a bendable material that provides a continuous structure without joins. The Shape Memory Alloys (SMAs) provide the possibility of building lightweight, joint-less, noise-less, motor-less and gear-less robots. Thus a swimming underwater fish-like robot has been developed whose movements are generated using SMAs. These actuators are suitable for bending the continuous backbone of the fish, which in turn causes a change in the curvature of the body. This type of structural arrangement is inspired by fish red muscles, which are mainly recruited during steady swimming for the bending of a flexible but nearly incompressible structure such as the fishbone. Likewise the caudal fin is based on SMAs and is customized to provide the necessary work out. The bendable structure provides thrust and allows the BR3 to swim. On the other hand the morphing caudal fin provides roll and yaw movements. Motivated by the versatility of the BR3 to mimic all the swimming modes (anguilliform, caranguiform, subcaranguiform and thunniform) a bending-speed controller is proposed. The bending-speed control law incorporates bend angle and frequency information to produce desired swimming mode and swimming speed. Likewise according to the biological fact about the influence of caudal fin shape in the maneuverability during steady swimming an attitude control is proposed. This novel fish robot is the first of its kind to incorporate only SMAs to bend a flexible continuous structure without joints and gears to produce thrust and mimic all the swimming modes as well as the caudal fin to be morphing. This novel mechatronic design is a promising way to design more efficient swimming/morphing underwater vehicles. The novel control methodology proposed in this thesis provide a totally new way of controlling robots based on SMAs, making them more energy efficient and the incorporation of a morphing caudal fin allows to perform more efficient maneuvers. As a whole, the BR3 project consists of five major stages of development: • Study and analysis of biological fish swimming data reported in specialized literature aimed at defining design and control criteria. • Formulation of mathematical models for: i) body kinematics, ii) dynamics, iii) hydrodynamics, iv) free vibration analysis and v) SMA muscle-like actuation. It is aimed at modelling the e ects of modulating caudal fin and body bend into the production of thrust forces for swimming, rotational forces for maneuvering and energy consumption optimisation. • Bio-inspired design and fabrication of: i) skeletal structure of backbone and body, ii) SMA muscle-like mechanisms for the body and caudal fin, iii) the artificial skin, iv) electronics onboard and v) sensor fusion. It is aimed at developing the fish-like platform (BR3) that allows for testing the methods proposed. • The swimming controller: i) control of SMA-muscles (morphing-caudal fin modulation and attitude regulation) and ii) steady swimming control (bend modulation and speed modulation). It is aimed at formulating the proper control methods that allow for the proper modulation of BR3’s caudal fin and body. • Experiments: it is aimed at quantifying the effects of: i) properly caudal fin modulation into hydrodynamics and rotation production for maneuvering, ii) body bending into thrust generation and iii) skin flexibility into BR3 bending ability. It is also aimed at demonstrating and validating the hypothesis of improving swimming and maneuvering efficiency thanks to the novel control methods presented in this thesis. This thesis introduces the challenges and methods to address these stages. Waterchannel experiments will be oriented to discuss and demonstrate how the caudal fin and body can considerably affect the dynamics/hydrodynamics of swimming/maneuvering and how to take advantage of bend modulation that the morphing-caudal fin and body enable to properly change caudal fin and body’ geometry during steady swimming and maneuvering.

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In this paper, we describe our research on bio-inspired locomotion systems using deformable structures and smart materials, concretely shape memory alloys (SMAs). These types of materials allow us to explore the possibility of building motor-less and gear-less robots. A swimming underwater fish-like robot has been developed whose movements are generated using SMAs. These actuators are suitable for bending the continuous backbone of the fish, which in turn causes a change in the curvature of the body. This type of structural arrangement is inspired by fish red muscles, which are mainly recruited during steady swimming for the bending of a flexible but nearly incompressible structure such as the fishbone. This paper reviews the design process of these bio-inspired structures, from the motivations and physiological inspiration to the mechatronics design, control and simulations, leading to actual experimental trials and results. The focus of this work is to present the mechanisms by which standard swimming patterns can be reproduced with the proposed design. Moreover, the performance of the SMA-based actuators’ control in terms of actuation speed and position accuracy is also addressed.

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Esta tesis doctoral se enmarca dentro de la computación con membranas. Se trata de un tipo de computación bio-inspirado, concretamente basado en las células de los organismos vivos, en las que se producen múltiples reacciones de forma simultánea. A partir de la estructura y funcionamiento de las células se han definido diferentes modelos formales, denominados P sistemas. Estos modelos no tratan de modelar el comportamiento biológico de una célula, sino que abstraen sus principios básicos con objeto de encontrar nuevos paradigmas computacionales. Los P sistemas son modelos de computación no deterministas y masivamente paralelos. De ahí el interés que en los últimos años estos modelos han suscitado para la resolución de problemas complejos. En muchos casos, consiguen resolver de forma teórica problemas NP-completos en tiempo polinómico o lineal. Por otra parte, cabe destacar también la aplicación que la computación con membranas ha tenido en la investigación de otros muchos campos, sobre todo relacionados con la biología. Actualmente, una gran cantidad de estos modelos de computación han sido estudiados desde el punto de vista teórico. Sin embargo, el modo en que pueden ser implementados es un reto de investigación todavía abierto. Existen varias líneas en este sentido, basadas en arquitecturas distribuidas o en hardware dedicado, que pretenden acercarse en lo posible a su carácter no determinista y masivamente paralelo, dentro de un contexto de viabilidad y eficiencia. En esta tesis doctoral se propone la realización de un análisis estático del P sistema, como vía para optimizar la ejecución del mismo en estas plataformas. Se pretende que la información recogida en tiempo de análisis sirva para configurar adecuadamente la plataforma donde se vaya a ejecutar posteriormente el P sistema, obteniendo como consecuencia una mejora en el rendimiento. Concretamente, en esta tesis se han tomado como referencia los P sistemas de transiciones para llevar a cabo el estudio de dicho análisis estático. De manera un poco más específica, el análisis estático propuesto en esta tesis persigue que cada membrana sea capaz de determinar sus reglas activas de forma eficiente en cada paso de evolución, es decir, aquellas reglas que reúnen las condiciones adecuadas para poder ser aplicadas. En esta línea, se afronta el problema de los estados de utilidad de una membrana dada, que en tiempo de ejecución permitirán a la misma conocer en todo momento las membranas con las que puede comunicarse, cuestión que determina las reglas que pueden aplicarse en cada momento. Además, el análisis estático propuesto en esta tesis se basa en otra serie de características del P sistema como la estructura de membranas, antecedentes de las reglas, consecuentes de las reglas o prioridades. Una vez obtenida toda esta información en tiempo de análisis, se estructura en forma de árbol de decisión, con objeto de que en tiempo de ejecución la membrana obtenga las reglas activas de la forma más eficiente posible. Por otra parte, en esta tesis se lleva a cabo un recorrido por un número importante de arquitecturas hardware y software que diferentes autores han propuesto para implementar P sistemas. Fundamentalmente, arquitecturas distribuidas, hardware dedicado basado en tarjetas FPGA y plataformas basadas en microcontroladores PIC. El objetivo es proponer soluciones que permitan implantar en dichas arquitecturas los resultados obtenidos del análisis estático (estados de utilidad y árboles de decisión para reglas activas). En líneas generales, se obtienen conclusiones positivas, en el sentido de que dichas optimizaciones se integran adecuadamente en las arquitecturas sin penalizaciones significativas. Summary Membrane computing is the focus of this doctoral thesis. It can be considered a bio-inspired computing type. Specifically, it is based on living cells, in which many reactions take place simultaneously. From cell structure and operation, many different formal models have been defined, named P systems. These models do not try to model the biological behavior of the cell, but they abstract the basic principles of the cell in order to find out new computational paradigms. P systems are non-deterministic and massively parallel computational models. This is why, they have aroused interest when dealing with complex problems nowadays. In many cases, they manage to solve in theory NP problems in polynomial or lineal time. On the other hand, it is important to note that membrane computing has been successfully applied in many researching areas, specially related to biology. Nowadays, lots of these computing models have been sufficiently characterized from a theoretical point of view. However, the way in which they can be implemented is a research challenge, that it is still open nowadays. There are some lines in this way, based on distributed architectures or dedicated hardware. All of them are trying to approach to its non-deterministic and parallel character as much as possible, taking into account viability and efficiency. In this doctoral thesis it is proposed carrying out a static analysis of the P system in order to optimize its performance in a computing platform. The general idea is that after data are collected in analysis time, they are used for getting a suitable configuration of the computing platform in which P system is going to be performed. As a consequence, the system throughput will improve. Specifically, this thesis has made use of Transition P systems for carrying out the study in static analysis. In particular, the static analysis proposed in this doctoral thesis tries to achieve that every membrane can efficiently determine its active rules in every evolution step. These rules are the ones that can be applied depending on the system configuration at each computational step. In this line, we are going to tackle the problem of the usefulness states for a membrane. This state will allow this membrane to know the set of membranes with which communication is possible at any time. This is a very important issue in determining the set of rules that can be applied. Moreover, static analysis in this thesis is carried out taking into account other properties such as membrane structure, rule antecedents, rule consequents and priorities among rules. After collecting all data in analysis time, they are arranged in a decision tree structure, enabling membranes to obtain the set of active rules as efficiently as possible in run-time system. On the other hand, in this doctoral thesis is going to carry out an overview of hardware and software architectures, proposed by different authors in order to implement P systems, such as distributed architectures, dedicated hardware based on PFGA, and computing platforms based on PIC microcontrollers. The aim of this overview is to propose solutions for implementing the results of the static analysis, that is, usefulness states and decision trees for active rules. In general, conclusions are satisfactory, because these optimizations can be properly integrated in most of the architectures without significant penalties.

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In this conceptual paper, we discuss two areas of research in robotics, robotic models of emotion and morphofunctional machines, and we explore the scope for potential cross-fertilization between them. We shift the focus in robot models of emotion from information-theoretic aspects of appraisal to the interactive significance of bodily dispositions. Typical emotional phenomena such as arousal and action readiness can be interpreted as morphofunctional processes, and their functionality may be replicated in robotic systems with morphologies that can be modulated for real-time adaptation. We investigate the control requirements for such systems, and present a possible bio-inspired architecture, based on the division of control between neural and endocrine systems in humans and animals. We suggest that emotional epi- sodes can be understood as emergent from the coordination of action control and action-readiness, respectively. This stress on morphology complements existing research on the information-theoretic aspects of emotion.

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The aim of automatic pathological voice detection systems is to serve as tools, to medical specialists, for a more objective, less invasive and improved diagnosis of diseases. In this respect, the gold standard for those system include the usage of a optimized representation of the spectral envelope, either based on cepstral coefficients from the mel-scaled Fourier spectral envelope (Mel-Frequency Cepstral Coefficients) or from an all-pole estimation (Linear Prediction Coding Cepstral Coefficients) forcharacterization, and Gaussian Mixture Models for posterior classification. However, the study of recently proposed GMM-based classifiers as well as Nuisance mitigation techniques, such as those employed in speaker recognition, has not been widely considered inpathology detection labours. The present work aims at testing whether or not the employment of such speaker recognition tools might contribute to improve system performance in pathology detection systems, specifically in the automatic detection of Obstructive Sleep Apnea. The testing procedure employs an Obstructive Sleep Apnea database, in conjunction with GMM-based classifiers looking for a better performance. The results show that an improved performance might be obtained by using such approach.

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The present work describes a new methodology for the automatic detection of the glottal space from laryngeal images based on active contour models (snakes). In order to obtain an appropriate image for the use of snakes based techniques, the proposed algorithm combines a pre-processing stage including some traditional techniques (thresholding and median filter) with more sophisticated ones such as anisotropic filtering. The value selected for the thresholding was fixed to the 85% of the maximum peak of the image histogram, and the anisotropic filter permits to distinguish two intensity levels, one corresponding to the background and the other one to the foreground (glottis). The initialization carried out is based on the magnitude obtained using the Gradient Vector Flow field, ensuring an automatic process for the selection of the initial contour. The performance of the algorithm is tested using the Pratt coefficient and compared against a manual segmentation. The results obtained suggest that this method provided results comparable with other techniques such as the proposed in (Osma-Ruiz et al., 2008).

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Dynamic and Partial Reconfiguration (DPR) allows a system to be able to modify certain parts of itself during run-time. This feature gives rise to the capability of evolution: changing parts of the configuration according to the online evaluation of performance or other parameters. The evolution is achieved through a bio-inspired model in which the features of the system are identified as genes. The objective of the evolution may not be a single one; in this work, power consumption is taken into consideration, together with the quality of filtering, as the measure of performance, of a noisy image. Pareto optimality is applied to the evolutionary process, in order to find a representative set of optimal solutions as for performance and power consumption. The main contributions of this paper are: implementing an evolvable system on a low-power Spartan-6 FPGA included in a Wireless Sensor Network node and, by enabling the availability of a real measure of power consumption at run-time, achieving the capability of multi-objective evolution, that yields different optimal configurations, among which the selected one will depend on the relative “weights” of performance and power consumption.