Energy Management Module for Mobile Robots in Hostile Environments

In hostile environments at CERN and other similar scientific facilities, having a reliable mobile robot system is essential for successful execution of robotic missions and to avoid situations of manual recovery of the robots in the event that the robot runs out of energy. Because of environmental constraints, such mobile robots are usually battery-powered and hence energy management and optimization is one of the key challenges in this field. The ability to know beforehand the energy consumed by various elements of the robot (such as locomotion, sensors, controllers, computers and communication) will allow flexibility in planning or managing the tasks to be performed by the robot.

Haptic teleoperation of mobile robots for augmentation of operator perception in environments with low-wireless signal

Wireless teleoperation of field robots for maintenance, inspection and rescue missions is often performed in environments with low wireless connectivity, caused by signal losses from the environment and distance from the wireless transmitters. Various studies from the literature have addressed these problems with time-delay robust control systems and multi-hop wireless relay networks. However, such approaches do not solve the issue of how to present wireless data to the operator to avoid losing control of the robot. Despite the fact that teleoperation for maintenance often already involves haptic devices, no studies look at the possibility of using this existing feedback to aid operators in navigating within areas of variable wireless connectivity. We propose a method to incorporate haptic information into the velocity control of an omnidirectional robot to augment the operators perception of wireless signal strength in the remote environment. In this paper we introduce a mapping between wireless signal strength from multiple receivers to the force feedback of a 6 Degree of Freedom haptic master and evaluate the proposed approach using experimental data and randomly generated wireless maps

Wireless communication enhancement methods for mobile robots in radiation environments

En entornos hostiles tales como aquellas instalaciones científicas donde la radiación ionizante es el principal peligro, el hecho de reducir las intervenciones humanas mediante el incremento de las operaciones robotizadas está siendo cada vez más de especial interés. CERN, la Organización Europea para la Investigación Nuclear, tiene alrededor de unos 50 km de superficie subterránea donde robots móviles controlador de forma remota podrían ayudar en su funcionamiento, por ejemplo, a la hora de llevar a cabo inspecciones remotas sobre radiación en los diferentes áreas destinados al efecto. No solo es preciso considerar que los robots deben ser capaces de recorrer largas distancias y operar durante largos periodos de tiempo, sino que deben saber desenvolverse en los correspondientes túneles subterráneos, tener en cuenta la presencia de campos electromagnéticos, radiación ionizante, etc. y finalmente, el hecho de que los robots no deben interrumpir el funcionamiento de los aceleradores. El hecho de disponer de un sistema de comunicaciones inalámbrico fiable y robusto es esencial para la correcta ejecución de las misiones que los robots deben afrontar y por supuesto, para evitar tales situaciones en las que es necesario la recuperación manual de los robots al agotarse su energía o al perder el enlace de comunicaciones. El objetivo de esta Tesis es proveer de las directrices y los medios necesarios para reducir el riesgo de fallo en la misión y maximizar las capacidades de los robots móviles inalámbricos los cuales disponen de almacenamiento finito de energía al trabajar en entornos peligrosos donde no se dispone de línea de vista directa. Para ello se proponen y muestran diferentes estrategias y métodos de comunicación inalámbrica. Teniendo esto en cuenta, se presentan a continuación los objetivos de investigación a seguir a lo largo de la Tesis: predecir la cobertura de comunicaciones antes y durante las misiones robotizadas; optimizar la capacidad de red inalámbrica de los robots móviles con respecto a su posición; y mejorar el rango operacional de esta clase de robots. Por su parte, las contribuciones a la Tesis se citan más abajo. El primer conjunto de contribuciones son métodos novedosos para predecir el consumo de energía y la autonomía en la comunicación antes y después de disponer de los robots en el entorno seleccionado. Esto es importante para proporcionar conciencia de la situación del robot y evitar fallos en la misión. El consumo de energía se predice usando una estrategia propuesta la cual usa modelos de consumo provenientes de diferentes componentes en un robot. La predicción para la cobertura de comunicaciones se desarrolla usando un nuevo filtro de RSS (Radio Signal Strength) y técnicas de estimación con la ayuda de Filtros de Kalman. El segundo conjunto de contribuciones son métodos para optimizar el rango de comunicaciones usando novedosas técnicas basadas en muestreo espacial que son robustas frente a ruidos de campos de detección y radio y que proporcionan redundancia. Se emplean métodos de diferencia central finitos para determinar los gradientes 2D RSS y se usa la movilidad del robot para optimizar el rango de comunicaciones y la capacidad de red. Este método también se valida con un caso de estudio centrado en la teleoperación háptica de robots móviles inalámbricos. La tercera contribución es un algoritmo robusto y estocástico descentralizado para la optimización de la posición al considerar múltiples robots autónomos usados principalmente para extender el rango de comunicaciones desde la estación de control al robot que está desarrollando la tarea. Todos los métodos y algoritmos propuestos se verifican y validan usando simulaciones y experimentos de campo con variedad de robots móviles disponibles en CERN. En resumen, esta Tesis ofrece métodos novedosos y demuestra su uso para: predecir RSS; optimizar la posición del robot; extender el rango de las comunicaciones inalámbricas; y mejorar las capacidades de red de los robots móviles inalámbricos para su uso en aplicaciones dentro de entornos peligrosos, que como ya se mencionó anteriormente, se destacan las instalaciones científicas con emisión de radiación ionizante. En otros términos, se ha desarrollado un conjunto de herramientas para mejorar, facilitar y hacer más seguras las misiones de los robots en entornos hostiles. Esta Tesis demuestra tanto en teoría como en práctica que los robots móviles pueden mejorar la calidad de las comunicaciones inalámbricas mediante la profundización en el estudio de su movilidad para optimizar dinámicamente sus posiciones y mantener conectividad incluso cuando no existe línea de vista. Los métodos desarrollados en la Tesis son especialmente adecuados para su fácil integración en robots móviles y pueden ser aplicados directamente en la capa de aplicación de la red inalámbrica. ABSTRACT In hostile environments such as in scientific facilities where ionising radiation is a dominant hazard, reducing human interventions by increasing robotic operations are desirable. CERN, the European Organization for Nuclear Research, has around 50 km of underground scientific facilities, where wireless mobile robots could help in the operation of the accelerator complex, e.g. in conducting remote inspections and radiation surveys in different areas. The main challenges to be considered here are not only that the robots should be able to go over long distances and operate for relatively long periods, but also the underground tunnel environment, the possible presence of electromagnetic fields, radiation effects, and the fact that the robots shall in no way interrupt the operation of the accelerators. Having a reliable and robust wireless communication system is essential for successful execution of such robotic missions and to avoid situations of manual recovery of the robots in the event that the robot runs out of energy or when the robot loses its communication link. The goal of this thesis is to provide means to reduce risk of mission failure and maximise mission capabilities of wireless mobile robots with finite energy storage capacity working in a radiation environment with non-line-of-sight (NLOS) communications by employing enhanced wireless communication methods. Towards this goal, the following research objectives are addressed in this thesis: predict the communication range before and during robotic missions; optimise and enhance wireless communication qualities of mobile robots by using robot mobility and employing multi-robot network. This thesis provides introductory information on the infrastructures where mobile robots will need to operate, the tasks to be carried out by mobile robots and the problems encountered in these environments. The reporting of research work carried out to improve wireless communication comprises an introduction to the relevant radio signal propagation theory and technology followed by explanation of the research in the following stages: An analysis of the wireless communication requirements for mobile robot for different tasks in a selection of CERN facilities; predictions of energy and communication autonomies (in terms of distance and time) to reduce risk of energy and communication related failures during missions; autonomous navigation of a mobile robot to find zone(s) of maximum radio signal strength to improve communication coverage area; and autonomous navigation of one or more mobile robots acting as mobile wireless relay (repeater) points in order to provide a tethered wireless connection to a teleoperated mobile robot carrying out inspection or radiation monitoring activities in a challenging radio environment. The specific contributions of this thesis are outlined below. The first sets of contributions are novel methods for predicting the energy autonomy and communication range(s) before and after deployment of the mobile robots in the intended environments. This is important in order to provide situational awareness and avoid mission failures. The energy consumption is predicted by using power consumption models of different components in a mobile robot. This energy prediction model will pave the way for choosing energy-efficient wireless communication strategies. The communication range prediction is performed using radio signal propagation models and applies radio signal strength (RSS) filtering and estimation techniques with the help of Kalman filters and Gaussian process models. The second set of contributions are methods to optimise the wireless communication qualities by using novel spatial sampling based techniques that are robust to sensing and radio field noises and provide redundancy features. Central finite difference (CFD) methods are employed to determine the 2-D RSS gradients and use robot mobility to optimise the communication quality and the network throughput. This method is also validated with a case study application involving superior haptic teleoperation of wireless mobile robots where an operator from a remote location can smoothly navigate a mobile robot in an environment with low-wireless signals. The third contribution is a robust stochastic position optimisation algorithm for multiple autonomous relay robots which are used for wireless tethering of radio signals and thereby to enhance the wireless communication qualities. All the proposed methods and algorithms are verified and validated using simulations and field experiments with a variety of mobile robots available at CERN. In summary, this thesis offers novel methods and demonstrates their use to predict energy autonomy and wireless communication range, optimise robots position to improve communication quality and enhance communication range and wireless network qualities of mobile robots for use in applications in hostile environmental characteristics such as scientific facilities emitting ionising radiations. In simpler terms, a set of tools are developed in this thesis for improving, easing and making safer robotic missions in hostile environments. This thesis validates both in theory and experiments that mobile robots can improve wireless communication quality by exploiting robots mobility to dynamically optimise their positions and maintain connectivity even when the (radio signal) environment possess non-line-of-sight characteristics. The methods developed in this thesis are well-suited for easier integration in mobile robots and can be applied directly at the application layer of the wireless network. The results of the proposed methods have outperformed other comparable state-of-the-art methods.

Auto-Emergencia de Comunicación Sintáctica en Entornos Estáticos y Dinámicos para Grupos de Robots mediante Evolución Gramatical y Aprendizaje por Refuerzo

La idea de dotar a un grupo de robots o agentes artificiales de un lenguaje ha sido objeto de intenso estudio en las ultimas décadas. Como no podía ser de otra forma los primeros intentos se enfocaron hacia el estudio de la emergencia de vocabularios compartidos convencionalmente por el grupo de robots. Las ventajas que puede ofrecer un léxico común son evidentes, como también lo es que un lenguaje con una estructura más compleja, en la que se pudieran combinar palabras, sería todavía más beneficioso. Surgen así algunas propuestas enfocadas hacia la emergencia de un lenguaje consensuado que muestre una estructura sintáctica similar al lenguaje humano, entre las que se encuentra este trabajo. Tomar el lenguaje humano como modelo supone adoptar algunas de las hipótesis y teorías que disciplinas como la filosofía, la psicología o la lingüística entre otras se han encargado de proponer. Según estas aproximaciones teóricas el lenguaje presenta una doble dimension formal y funcional. En base a su dimensión formal parece claro que el lenguaje sigue unas reglas, por lo que el uso de una gramática se ha considerado esencial para su representación, pero también porque las gramáticas son un dispositivo muy sencillo y potente que permite generar fácilmente estructuras simbólicas. En cuanto a la dimension funcional se ha tenido en cuenta la teoría quizá más influyente de los últimos tiempos, que no es otra que la Teoría de los Actos del Habla. Esta teoría se basa en la idea de Wittgenstein por la que el significado reside en el uso del lenguaje, hasta el punto de que éste se entiende como una manera de actuar y de comportarse, en definitiva como una forma de vida. Teniendo presentes estas premisas en esta tesis se pretende experimentar con modelos computacionales que permitan a un grupo de robots alcanzar un lenguaje común de manera autónoma, simplemente mediante interacciones individuales entre los robots, en forma de juegos de lenguaje. Para ello se proponen tres modelos distintos de lenguaje: • Un modelo basado en gramáticas probabilísticas y aprendizaje por refuerzo en el que las interacciones y el uso del lenguaje son claves para su emergencia y que emplea una gramática generativa estática y diseñada de antemano. Este modelo se aplica a dos grupos distintos: uno formado exclusivamente por robots y otro que combina robots y un humano, de manera que en este segundo caso se plantea un aprendizaje supervisado por humanos. • Un modelo basado en evolución gramatical que permite estudiar no solo el consenso sintáctico, sino también cuestiones relativas a la génesis del lenguaje y que emplea una gramática universal a partir de la cual los robots pueden evolucionar por sí mismos la gramática más apropiada según la situación lingüística que traten en cada momento. • Un modelo basado en evolución gramatical y aprendizaje por refuerzo que toma aspectos de los anteriores y amplia las posibilidades de los robots al permitir desarrollar un lenguaje que se adapta a situaciones lingüísticas dinámicas que pueden cambiar en el tiempo y también posibilita la imposición de restricciones de orden muy frecuentes en las estructuras sintácticas complejas. Todos los modelos implican un planteamiento descentralizado y auto-organizado, de manera que ninguno de los robots es el dueño del lenguaje y todos deben cooperar y colaborar de forma coordinada para lograr el consenso sintáctico. En cada caso se plantean experimentos que tienen como objetivo validar los modelos propuestos, tanto en lo relativo al éxito en la emergencia del lenguaje como en lo relacionado con cuestiones paralelas de importancia, como la interacción hombre-máquina o la propia génesis del lenguaje. ABSTRACT The idea of giving a language to a group of robots or artificial agents has been the subject of intense study in recent decades. The first attempts have focused on the development and emergence of a conventionally shared vocabulary. The advantages that can provide a common vocabulary are evident and therefore a more complex language that combines words would be even more beneficial. Thus some proposals are put forward towards the emergence of a consensual language with a sintactical structure in similar terms to the human language. This work follows this trend. Taking the human language as a model means taking some of the assumptions and theories that disciplines such as philosophy, psychology or linguistics among others have provided. According to these theoretical positions language has a double formal and functional dimension. Based on its formal dimension it seems clear that language follows rules, so that the use of a grammar has been considered essential for representation, but also because grammars are a very simple and powerful device that easily generates these symbolic structures. As for the functional dimension perhaps the most influential theory of recent times, the Theory of Speech Acts has been taken into account. This theory is based on the Wittgenstein’s idea about that the meaning lies in the use of language, to the extent that it is understood as a way of acting and behaving. Having into account these issues this work implements some computational models in order to test if they allow a group of robots to reach in an autonomous way a shared language by means of individual interaction among them, that is by means of language games. Specifically, three different models of language for robots are proposed: • A reinforcement learning based model in which interactions and language use are key to its emergence. This model uses a static probabilistic generative grammar which is designed beforehand. The model is applied to two different groups: one formed exclusively by robots and other combining robots and a human. Therefore, in the second case the learning process is supervised by the human. • A model based on grammatical evolution that allows us to study not only the syntactic consensus, but also the very genesis of language. This model uses a universal grammar that allows robots to evolve for themselves the most appropriate grammar according to the current linguistic situation they deal with. • A model based on grammatical evolution and reinforcement learning that takes aspects of the previous models and increases their possibilities. This model allows robots to develop a language in order to adapt to dynamic language situations that can change over time and also allows the imposition of syntactical order restrictions which are very common in complex syntactic structures. All models involve a decentralized and self-organized approach so that none of the robots is the language’s owner and everyone must cooperate and work together in a coordinated manner to achieve syntactic consensus. In each case experiments are presented in order to validate the proposed models, both in terms of success about the emergence of language and it relates to the study of important parallel issues, such as human-computer interaction or the very genesis of language.

CAS: A tool for improving autonomous work

The EHEA proposes a student-centered teaching model. Therefore, it seems necessary to actively involve the students in the teaching-learning process. Increasing the active participation of the students is not always easy in mathematical topics, since, when the students just enter the University, their ability to carry out autonomous mathematical work is scarce. In this paper we present some experiences related with the use of Computer Algebra Systems (CAS). All the experiences are designed in order to develop some mathematical competencies and mainly self-learning, the use of technology and team-work. The experiences include some teachers? proposals including: small projects to be executed in small groups, participation in competitions, the design of different CAS-Toolboxes, etc. The results obtained in the experiences, carried out with different groups of students from different engineering studies at different universities, makes us slightly optimistic about the educational value of the model.

Human-robot interaction for telemanipulation in large workspaces

Independientemente de la existencia de técnicas altamente sofisticadas y capacidades de cómputo cada vez más elevadas, los problemas asociados a los robots que interactúan con entornos no estructurados siguen siendo un desafío abierto en robótica. A pesar de los grandes avances de los sistemas robóticos autónomos, hay algunas situaciones en las que una persona en el bucle sigue siendo necesaria. Ejemplos de esto son, tareas en entornos de fusión nuclear, misiones espaciales, operaciones submarinas y cirugía robótica. Esta necesidad se debe a que las tecnologías actuales no pueden realizar de forma fiable y autónoma cualquier tipo de tarea. Esta tesis presenta métodos para la teleoperación de robots abarcando distintos niveles de abstracción que van desde el control supervisado, en el que un operador da instrucciones de alto nivel en la forma de acciones, hasta el control bilateral, donde los comandos toman la forma de señales de control de bajo nivel. En primer lugar, se presenta un enfoque para llevar a cabo la teleoperación supervisada de robots humanoides. El objetivo es controlar robots terrestres capaces de ejecutar tareas complejas en entornos de búsqueda y rescate utilizando enlaces de comunicación limitados. Esta propuesta incorpora comportamientos autónomos que el operador puede utilizar para realizar tareas de navegación y manipulación mientras se permite cubrir grandes áreas de entornos remotos diseñados para el acceso de personas. Los resultados experimentales demuestran la eficacia de los métodos propuestos. En segundo lugar, se investiga el uso de dispositivos rentables para telemanipulación guiada. Se presenta una aplicación que involucra un robot humanoide bimanual y un traje de captura de movimiento basado en sensores inerciales. En esta aplicación, se estudian las capacidades de adaptación introducidas por el factor humano y cómo estas pueden compensar la falta de sistemas robóticos de alta precisión. Este trabajo es el resultado de una colaboración entre investigadores del Biorobotics Laboratory de la Universidad de Harvard y el Centro de Automática y Robótica UPM-CSIC. En tercer lugar, se presenta un nuevo controlador háptico que combina velocidad y posición. Este controlador bilateral híbrido hace frente a los problemas relacionados con la teleoperación de un robot esclavo con un gran espacio de trabajo usando un dispositivo háptico pequeño como maestro. Se pueden cubrir amplias áreas de trabajo al cambiar automáticamente entre los modos de control de velocidad y posición. Este controlador háptico es ideal para sistemas maestro-esclavo con cinemáticas diferentes, donde los comandos se transmiten en el espacio de la tarea del entorno remoto. El método es validado para realizar telemanipulación hábil de objetos con un robot industrial. Por último, se introducen dos contribuciones en el campo de la manipulación robótica. Por un lado, se presenta un nuevo algoritmo de cinemática inversa, llamado método iterativo de desacoplamiento cinemático. Este método se ha desarrollado para resolver el problema cinemático inverso de un tipo de robot de seis grados de libertad donde una solución cerrada no está disponible. La eficacia del método se compara con métodos numéricos convencionales. Además, se ha diseñado una taxonomía robusta de agarres que permite controlar diferentes manos robóticas utilizando una correspondencia, basada en gestos, entre los espacios de trabajo de la mano humana y de la mano robótica. El gesto de la mano humana se identifica mediante la lectura de los movimientos relativos del índice, el pulgar y el dedo medio del usuario durante las primeras etapas del agarre. ABSTRACT Regardless of the availability of highly sophisticated techniques and ever increasing computing capabilities, the problems associated with robots interacting with unstructured environments remains an open challenge. Despite great advances in autonomous robotics, there are some situations where a humanin- the-loop is still required, such as, nuclear, space, subsea and robotic surgery operations. This is because the current technologies cannot reliably perform all kinds of task autonomously. This thesis presents methods for robot teleoperation strategies at different levels of abstraction ranging from supervisory control, where the operator gives high-level task actions, to bilateral teleoperation, where the commands take the form of low-level control inputs. These strategies contribute to improve the current human-robot interfaces specially in the case of slave robots deployed at large workspaces. First, an approach to perform supervisory teleoperation of humanoid robots is presented. The goal is to control ground robots capable of executing complex tasks in disaster relief environments under constrained communication links. This proposal incorporates autonomous behaviors that the operator can use to perform navigation and manipulation tasks which allow covering large human engineered areas of the remote environment. The experimental results demonstrate the efficiency of the proposed methods. Second, the use of cost-effective devices for guided telemanipulation is investigated. A case study involving a bimanual humanoid robot and an Inertial Measurement Unit (IMU) Motion Capture (MoCap) suit is introduced. Herein, it is corroborated how the adaptation capabilities offered by the human-in-the-loop factor can compensate for the lack of high-precision robotic systems. This work is the result of collaboration between researchers from the Harvard Biorobotics Laboratory and the Centre for Automation and Robotics UPM-CSIC. Thirdly, a new haptic rate-position controller is presented. This hybrid bilateral controller copes with the problems related to the teleoperation of a slave robot with large workspace using a small haptic device as master. Large workspaces can be covered by automatically switching between rate and position control modes. This haptic controller is ideal to couple kinematic dissimilar master-slave systems where the commands are transmitted in the task space of the remote environment. The method is validated to perform dexterous telemanipulation of objects with a robotic manipulator. Finally, two contributions for robotic manipulation are introduced. First, a new algorithm, the Iterative Kinematic Decoupling method, is presented. It is a numeric method developed to solve the Inverse Kinematics (IK) problem of a type of six-DoF robotic arms where a close-form solution is not available. The effectiveness of this IK method is compared against conventional numerical methods. Second, a robust grasp mapping has been conceived. It allows to control a wide range of different robotic hands using a gesture based correspondence between the human hand space and the robotic hand space. The human hand gesture is identified by reading the relative movements of the index, thumb and middle fingers of the user during the early stages of grasping.

A simulation environment for bio-inspired heterogeneous chained modular robots

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.

Autonomous Acquisition of Natural Situated Communication

An important part of human intelligence, both historically and operationally, is our ability to communicate. We learn how to communicate, and maintain our communicative skills, in a society of communicators – a highly effective way to reach and maintain proficiency in this complex skill. Principles that might allow artificial agents to learn language this way are in completely known at present – the multi-dimensional nature of socio-communicative skills are beyond every machine learning framework so far proposed. Our work begins to address the challenge of proposing a way for observation-based machine learning of natural language and communication. Our framework can learn complex communicative skills with minimal up-front knowledge. The system learns by incrementally producing predictive models of causal relationships in observed data, guided by goal-inference and reasoning using forward-inverse models. We present results from two experiments where our S1 agent learns human communication by observing two humans interacting in a realtime TV-style interview, using multimodal communicative gesture and situated language to talk about recycling of various materials and objects. S1 can learn multimodal complex language and multimodal communicative acts, a vocabulary of 100 words forming natural sentences with relatively complex sentence structure, including manual deictic reference and anaphora. S1 is seeded only with high-level information about goals of the interviewer and interviewee, and a small ontology; no grammar or other information is provided to S1 a priori. The agent learns the pragmatics, semantics, and syntax of complex utterances spoken and gestures from scratch, by observing the humans compare and contrast the cost and pollution related to recycling aluminum cans, glass bottles, newspaper, plastic, and wood. After 20 hours of observation S1 can perform an unscripted TV interview with a human, in the same style, without making mistakes.

Autonomous Acquisition of Natural Language

An important part of human intelligence is the ability to use language. Humans learn how to use language in a society of language users, which is probably the most effective way to learn a language from the ground up. Principles that might allow an artificial agents to learn language this way are not known at present. Here we present a framework which begins to address this challenge. Our auto-catalytic, endogenous, reflective architecture (AERA) supports the creation of agents that can learn natural language by observation. We present results from two experiments where our S1 agent learns human communication by observing two humans interacting in a realtime mock television interview, using gesture and situated language. Results show that S1 can learn multimodal complex language and multimodal communicative acts, using a vocabulary of 100 words with numerous sentence formats, by observing unscripted interaction between the humans, with no grammar being provided to it a priori, and only high-level information about the format of the human interaction in the form of high-level goals of the interviewer and interviewee and a small ontology. The agent learns both the pragmatics, semantics, and syntax of complex sentences spoken by the human subjects on the topic of recycling of objects such as aluminum cans, glass bottles, plastic, and wood, as well as use of manual deictic reference and anaphora.

Cognitive risk perception system for obstacle avoidance in outdoor mUAV missions

La robótica ha evolucionado exponencialmente en las últimas décadas, permitiendo a los sistemas actuales realizar tareas sumamente complejas con gran precisión, fiabilidad y velocidad. Sin embargo, este desarrollo ha estado asociado a un mayor grado de especialización y particularización de las tecnologías implicadas, siendo estas muy eficientes en situaciones concretas y controladas, pero incapaces en entornos cambiantes, dinámicos y desestructurados. Por eso, el desarrollo de la robótica debe pasar por dotar a los sistemas de capacidad de adaptación a las circunstancias, de entendedimiento sobre los cambios observados y de flexibilidad a la hora de interactuar con el entorno. Estas son las caracteristicas propias de la interacción del ser humano con su entorno, las que le permiten sobrevivir y las que pueden proporcionar a un sistema inteligencia y capacidad suficientes para desenvolverse en un entorno real de forma autónoma e independiente. Esta adaptabilidad es especialmente importante en el manejo de riesgos e incetidumbres, puesto que es el mecanismo que permite contextualizar y evaluar las amenazas para proporcionar una respuesta adecuada. Así, por ejemplo, cuando una persona se mueve e interactua con su entorno, no evalúa los obstáculos en función de su posición, velocidad o dinámica (como hacen los sistemas robóticos tradicionales), sino mediante la estimación del riesgo potencial que estos elementos suponen para la persona. Esta evaluación se consigue combinando dos procesos psicofísicos del ser humano: por un lado, la percepción humana analiza los elementos relevantes del entorno, tratando de entender su naturaleza a partir de patrones de comportamiento, propiedades asociadas u otros rasgos distintivos. Por otro lado, como segundo nivel de evaluación, el entendimiento de esta naturaleza permite al ser humano conocer/estimar la relación de los elementos con él mismo, así como sus implicaciones en cuanto a nivel de riesgo se refiere. El establecimiento de estas relaciones semánticas -llamado cognición- es la única forma de definir el nivel de riesgo de manera absoluta y de generar una respuesta adecuada al mismo. No necesariamente proporcional, sino coherente con el riesgo al que se enfrenta. La investigación que presenta esta tesis describe el trabajo realizado para trasladar esta metodología de análisis y funcionamiento a la robótica. Este se ha centrado especialmente en la nevegación de los robots aéreos, diseñando e implementado procedimientos de inspiración humana para garantizar la seguridad de la misma. Para ello se han estudiado y evaluado los mecanismos de percepción, cognición y reacción humanas en relación al manejo de riesgos. También se ha analizado como los estímulos son capturados, procesados y transformados por condicionantes psicológicos, sociológicos y antropológicos de los seres humanos. Finalmente, también se ha analizado como estos factores motivan y descandenan las reacciones humanas frente a los peligros. Como resultado de este estudio, todos estos procesos, comportamientos y condicionantes de la conducta humana se han reproducido en un framework que se ha estructurado basadandose en factores análogos. Este emplea el conocimiento obtenido experimentalmente en forma de algoritmos, técnicas y estrategias, emulando el comportamiento humano en las mismas circunstancias. Diseñado, implementeado y validado tanto en simulación como con datos reales, este framework propone una manera innovadora -tanto en metodología como en procedimiento- de entender y reaccionar frente a las amenazas potenciales de una misión robótica. ABSTRACT Robotics has undergone a great revolution in the last decades. Nowadays this technology is able to perform really complex tasks with a high degree of accuracy and speed, however this is only true in precisely defined situations with fully controlled variables. Since the real world is dynamic, changing and unstructured, flexible and non context-dependent systems are required. The ability to understand situations, acknowledge changes and balance reactions is required by robots to successfully interact with their surroundings in a fully autonomous fashion. In fact, it is those very processes that define human interactions with the environment. Social relationships, driving or risk/incertitude management... in all these activities and systems, context understanding and adaptability are what allow human beings to survive: contrarily to the traditional robotics, people do not evaluate obstacles according to their position but according to the potential risk their presence imply. In this sense, human perception looks for information which goes beyond location, speed and dynamics (the usual data used in traditional obstacle avoidance systems). Specific features in the behaviour of a particular element allows the understanding of that element’s nature and therefore the comprehension of the risk posed by it. This process defines the second main difference between traditional obstacle avoidance systems and human behaviour: the ability to understand a situation/scenario allows to get to know the implications of the elements and their relationship with the observer. Establishing these semantic relationships -named cognition- is the only way to estimate the actual danger level of an element. Furthermore, only the application of this knowledge allows the generation of coherent, suitable and adjusted responses to deal with any risk faced. The research presented in this thesis summarizes the work done towards translating these human cognitive/reasoning procedures to the field of robotics. More specifically, the work done has been focused on employing human-based methodologies to enable aerial robots to navigate safely. To this effect, human perception, cognition and reaction processes concerning risk management have been experimentally studied; as well as the acquisition and processing of stimuli. How psychological, sociological and anthropological factors modify, balance and give shape to those stimuli has been researched. And finally, the way in which these factors motivate the human behaviour according to different mindsets and priorities has been established. This associative workflow has been reproduced by establishing an equivalent structure and defining similar factors and sources. Besides, all the knowledge obtained experimentally has been applied in the form of algorithms, techniques and strategies which emulate the analogous human behaviours. As a result, a framework capable of understanding and reacting in response to stimuli has been implemented and validated.

Online Learning-based Robust Visual Tracking for Autonomous Landing of Unmanned Aerial Vehicles

Autonomous landing is a challenging and important technology for both military and civilian applications of Unmanned Aerial Vehicles (UAVs). In this paper, we present a novel online adaptive visual tracking algorithm for UAVs to land on an arbitrary field (that can be used as the helipad) autonomously at real-time frame rates of more than twenty frames per second. The integration of low-dimensional subspace representation method, online incremental learning approach and hierarchical tracking strategy allows the autolanding task to overcome the problems generated by the challenging situations such as significant appearance change, variant surrounding illumination, partial helipad occlusion, rapid pose variation, onboard mechanical vibration (no video stabilization), low computational capacity and delayed information communication between UAV and Ground Control Station (GCS). The tracking performance of this presented algorithm is evaluated with aerial images from real autolanding flights using manually- labelled ground truth database. The evaluation results show that this new algorithm is highly robust to track the helipad and accurate enough for closing the vision-based control loop.

Toward Visual Autonomous Ship Board Landing of a VTOL UAV

In this paper we tackle the problem of landing a helicopter autonomously on a ship deck, using as the main sensor, an on-board colour camera. To create a test-bed, we first adequately simulate the movement of a ship landing platform on the Sea, for different Sea States, for different ships, randomly and realistically enough. We use a commercial parallel robot to get this movement. Once we had this, we developed an accurate and robust computer vision system to measure the pose of the helipad with respect to the on-board camera. To deal with the noise and the possible fails of the computer vision, a state estimator was created. With all of this, we are now able to develop and test a controller that closes the loop and finish the autonomous landing task.

A Ground-Truth Video Dataset for the Development and Evaluation of Vision-based Sense-and-Avoid systems

The importance of vision-based systems for Sense-and-Avoid is increasing nowadays as remotely piloted and autonomous UAVs become part of the non-segregated airspace. The development and evaluation of these systems demand flight scenario images which are expensive and risky to obtain. Currently Augmented Reality techniques allow the compositing of real flight scenario images with 3D aircraft models to produce useful realistic images for system development and benchmarking purposes at a much lower cost and risk. With the techniques presented in this paper, 3D aircraft models are positioned firstly in a simulated 3D scene with controlled illumination and rendering parameters. Realistic simulated images are then obtained using an image processing algorithm which fuses the images obtained from the 3D scene with images from real UAV flights taking into account on board camera vibrations. Since the intruder and camera poses are user-defined, ground truth data is available. These ground truth annotations allow to develop and quantitatively evaluate aircraft detection and tracking algorithms. This paper presents the software developed to create a public dataset of 24 videos together with their annotations and some tracking application results.

Online Learning-based Robust Visual Tracking for Autonomous Landing of Unmanned Aerial Vehicles

Autonomous landing is a challenging and important technology for both military and civilian applications of Unmanned Aerial Vehicles (UAVs). In this paper, we present a novel online adaptive visual tracking algorithm for UAVs to land on an arbitrary field (that can be used as the helipad) autonomously at real-time frame rates of more than twenty frames per second. The integration of low-dimensional subspace representation method, online incremental learning approach and hierarchical tracking strategy allows the autolanding task to overcome the problems generated by the challenging situations such as significant appearance change, variant surrounding illumination, partial helipad occlusion, rapid pose variation, onboard mechanical vibration (no video stabilization), low computational capacity and delayed information communication between UAV and Ground Control Station (GCS). The tracking performance of this presented algorithm is evaluated with aerial images from real autolanding flights using manually- labelled ground truth database. The evaluation results show that this new algorithm is highly robust to track the helipad and accurate enough for closing the vision-based control loop.

Fault management techniques for systems with SRAM-based FPGAs

Las Field-Programmable Gate Arrays (FPGAs) SRAM se construyen sobre una memoria de configuración de tecnología RAM Estática (SRAM). Presentan múltiples características que las hacen muy interesantes para diseñar sistemas empotrados complejos. En primer lugar presentan un coste no-recurrente de ingeniería (NRE) bajo, ya que los elementos lógicos y de enrutado están pre-implementados (el diseño de usuario define su conexionado). También, a diferencia de otras tecnologías de FPGA, pueden ser reconfiguradas (incluso en campo) un número ilimitado de veces. Es más, las FPGAs SRAM de Xilinx soportan Reconfiguración Parcial Dinámica (DPR), la cual permite reconfigurar la FPGA sin interrumpir la aplicación. Finalmente, presentan una alta densidad de lógica, una alta capacidad de procesamiento y un rico juego de macro-bloques. Sin embargo, un inconveniente de esta tecnología es su susceptibilidad a la radiación ionizante, la cual aumenta con el grado de integración (geometrías más pequeñas, menores tensiones y mayores frecuencias). Esta es una precupación de primer nivel para aplicaciones en entornos altamente radiativos y con requisitos de alta confiabilidad. Este fenómeno conlleva una degradación a largo plazo y también puede inducir fallos instantáneos, los cuales pueden ser reversibles o producir daños irreversibles. En las FPGAs SRAM, los fallos inducidos por radiación pueden aparecer en en dos capas de arquitectura diferentes, que están físicamente superpuestas en el dado de silicio. La Capa de Aplicación (o A-Layer) contiene el hardware definido por el usuario, y la Capa de Configuración contiene la memoria de configuración y la circuitería de soporte. Los fallos en cualquiera de estas capas pueden hacer fracasar el sistema, lo cual puede ser ás o menos tolerable dependiendo de los requisitos de confiabilidad del sistema. En el caso general, estos fallos deben gestionados de alguna manera. Esta tesis trata sobre la gestión de fallos en FPGAs SRAM a nivel de sistema, en el contexto de sistemas empotrados autónomos y confiables operando en un entorno radiativo. La tesis se centra principalmente en aplicaciones espaciales, pero los mismos principios pueden aplicarse a aplicaciones terrenas. Las principales diferencias entre ambas son el nivel de radiación y la posibilidad de mantenimiento. Las diferentes técnicas para la gestión de fallos en A-Layer y C-Layer son clasificados, y sus implicaciones en la confiabilidad del sistema son analizados. Se proponen varias arquitecturas tanto para Gestores de Fallos de una capa como de doble-capa. Para estos últimos se propone una arquitectura novedosa, flexible y versátil. Gestiona las dos capas concurrentemente de manera coordinada, y permite equilibrar el nivel de redundancia y la confiabilidad. Con el objeto de validar técnicas de gestión de fallos dinámicas, se desarrollan dos diferentes soluciones. La primera es un entorno de simulación para Gestores de Fallos de C-Layer, basado en SystemC como lenguaje de modelado y como simulador basado en eventos. Este entorno y su metodología asociada permite explorar el espacio de diseño del Gestor de Fallos, desacoplando su diseño del desarrollo de la FPGA objetivo. El entorno incluye modelos tanto para la C-Layer de la FPGA como para el Gestor de Fallos, los cuales pueden interactuar a diferentes niveles de abstracción (a nivel de configuration frames y a nivel físico JTAG o SelectMAP). El entorno es configurable, escalable y versátil, e incluye capacidades de inyección de fallos. Los resultados de simulación para algunos escenarios son presentados y comentados. La segunda es una plataforma de validación para Gestores de Fallos de FPGAs Xilinx Virtex. La plataforma hardware aloja tres Módulos de FPGA Xilinx Virtex-4 FX12 y dos Módulos de Unidad de Microcontrolador (MCUs) de 32-bits de propósito general. Los Módulos MCU permiten prototipar Gestores de Fallos de C-Layer y A-Layer basados en software. Cada Módulo FPGA implementa un enlace de A-Layer Ethernet (a través de un switch Ethernet) con uno de los Módulos MCU, y un enlace de C-Layer JTAG con el otro. Además, ambos Módulos MCU intercambian comandos y datos a través de un enlace interno tipo UART. Al igual que para el entorno de simulación, se incluyen capacidades de inyección de fallos. Los resultados de pruebas para algunos escenarios son también presentados y comentados. En resumen, esta tesis cubre el proceso completo desde la descripción de los fallos FPGAs SRAM inducidos por radiación, pasando por la identificación y clasificación de técnicas de gestión de fallos, y por la propuesta de arquitecturas de Gestores de Fallos, para finalmente validarlas por simulación y pruebas. El trabajo futuro está relacionado sobre todo con la implementación de Gestores de Fallos de Sistema endurecidos para radiación. ABSTRACT SRAM-based Field-Programmable Gate Arrays (FPGAs) are built on Static RAM (SRAM) technology configuration memory. They present a number of features that make them very convenient for building complex embedded systems. First of all, they benefit from low Non-Recurrent Engineering (NRE) costs, as the logic and routing elements are pre-implemented (user design defines their connection). Also, as opposed to other FPGA technologies, they can be reconfigured (even in the field) an unlimited number of times. Moreover, Xilinx SRAM-based FPGAs feature Dynamic Partial Reconfiguration (DPR), which allows to partially reconfigure the FPGA without disrupting de application. Finally, they feature a high logic density, high processing capability and a rich set of hard macros. However, one limitation of this technology is its susceptibility to ionizing radiation, which increases with technology scaling (smaller geometries, lower voltages and higher frequencies). This is a first order concern for applications in harsh radiation environments and requiring high dependability. Ionizing radiation leads to long term degradation as well as instantaneous faults, which can in turn be reversible or produce irreversible damage. In SRAM-based FPGAs, radiation-induced faults can appear at two architectural layers, which are physically overlaid on the silicon die. The Application Layer (or A-Layer) contains the user-defined hardware, and the Configuration Layer (or C-Layer) contains the (volatile) configuration memory and its support circuitry. Faults at either layers can imply a system failure, which may be more ore less tolerated depending on the dependability requirements. In the general case, such faults must be managed in some way. This thesis is about managing SRAM-based FPGA faults at system level, in the context of autonomous and dependable embedded systems operating in a radiative environment. The focus is mainly on space applications, but the same principles can be applied to ground applications. The main differences between them are the radiation level and the possibility for maintenance. The different techniques for A-Layer and C-Layer fault management are classified and their implications in system dependability are assessed. Several architectures are proposed, both for single-layer and dual-layer Fault Managers. For the latter, a novel, flexible and versatile architecture is proposed. It manages both layers concurrently in a coordinated way, and allows balancing redundancy level and dependability. For the purpose of validating dynamic fault management techniques, two different solutions are developed. The first one is a simulation framework for C-Layer Fault Managers, based on SystemC as modeling language and event-driven simulator. This framework and its associated methodology allows exploring the Fault Manager design space, decoupling its design from the target FPGA development. The framework includes models for both the FPGA C-Layer and for the Fault Manager, which can interact at different abstraction levels (at configuration frame level and at JTAG or SelectMAP physical level). The framework is configurable, scalable and versatile, and includes fault injection capabilities. Simulation results for some scenarios are presented and discussed. The second one is a validation platform for Xilinx Virtex FPGA Fault Managers. The platform hosts three Xilinx Virtex-4 FX12 FPGA Modules and two general-purpose 32-bit Microcontroller Unit (MCU) Modules. The MCU Modules allow prototyping software-based CLayer and A-Layer Fault Managers. Each FPGA Module implements one A-Layer Ethernet link (through an Ethernet switch) with one of the MCU Modules, and one C-Layer JTAG link with the other. In addition, both MCU Modules exchange commands and data over an internal UART link. Similarly to the simulation framework, fault injection capabilities are implemented. Test results for some scenarios are also presented and discussed. In summary, this thesis covers the whole process from describing the problem of radiationinduced faults in SRAM-based FPGAs, then identifying and classifying fault management techniques, then proposing Fault Manager architectures and finally validating them by simulation and test. The proposed future work is mainly related to the implementation of radiation-hardened System Fault Managers.