Simulador de comportamiento de enjambre con Quorum Sensing bacteriano

One of the most useful tools in the design of path-planning solutions is simulators. Thanks to them, it is possible to predict the performance of certain control strategies. In this paper, a simulator is presented that implements a swarm of automatons, which perform a wild motion in a user-selected environment. The robots will have the quality to avoid collisions with different obstacles that affect their mobility since they are equipped with proximity sensors. The interface of this simulator was designed entirely with the Qt Designer software. Successful configurations that replicate the performance of the real prototype are presented.  Una de las herramientas más útiles en el diseño de soluciones de planificación de trayectorias son los simuladores. Gracias a ellos, es posible predecir el rendimiento de determinadas estrategias de control. En este trabajo se presenta un simulador que implementa un enjambre de autómatas que realizan un movimiento salvaje en un entorno seleccionado por el usuario. Los robots tendrán la cualidad de evitar colisiones con diferentes obstáculos que afecten a su movilidad ya que están equipados con sensores de proximidad. La interfaz de este simulador se ha diseñado íntegramente con el software Qt Designer. Se presentan configuraciones exitosas que replican el desempeño del prototipo real. &nbsp

Revisión de las estrategias de organización en bandadas para enjambres de robots

Robotics promises great benefits for human beings, both at the industrial level and concerning personal services. This has led to the continuous development and research in different problems, including control, manipulation, human-machine interaction, and of course, autonomous navigation. Robot swarm systems promise an alternative solution to the classic high-performance platforms, particularly in applications that require task distribution. Among these systems, flocking navigation schemes are currently attracting high attention. To establish a frame of reference, a general review of the literature to date related to flocking behavior, in particular, optimized schemes with some guarantee of safety, is presented. In most of the cases presented, the characteristics of these systems, such as minimal computational and communication requirements, and event-driven planning, are maintained.La robótica promete grandes beneficios, tanto a nivel industrial como con respecto a servicios personales. Esto ha incidido en el continuo desarrollo e investigación en diferentes problemas, entre ellos el control, la manipulación, la interacción hombre-máquina, y por supuesto, la navegación autónoma. Los sistemas de enjambres de robots prometen una alternativa de solución frente a las clásicas plataformas de alto de desempeño, particularmente en aplicaciones que requieren distribución de tareas. Entre estos sistemas, llama la atención los esquemas de navegación en bandada, los cuales tiene actualmente una alta atención. Para establecer un marco de referencia, se presenta una revisión general de la literatura a la fecha relacionada con comportamientos en bandada, en particular esquemas optimizados y con alguna garantía de seguridad. En la mayoría de los casos presentados se mantienen las características de estos sistemas, como son requisitos mínimos de computación y comunicación, y la planificación basada en eventos

Constructing Geometries for Group Control: Methods for Reasoning about Social Behaviors

Social behaviors in groups has been the subjects of hundreds of studies in a variety of research disciplines, including biology, physics, and robotics. In particular, flocking behaviors (commonly exhibited by birds and fish) are widely considered archetypical social behavioris and are due, in part, to the local interactions among the individuals and the environment. Despite a large number of investigations and a significant fraction of these providing algorithmic descriptions of flocking models, incompleteness and imprecision are readily identifiable in these algorithms, algorithmic input, and validation of the models. This has led to a limited understanding of the group level behaviors. Through two case-studies and a detailed meta-study of the literature, this dissertation shows that study of the individual behaviors are not adequate for understanding the behaviors displayed by the group. To highlight the limitations in only studying the individuals, this dissertation introduces a set of tools, that together, unify many of the existing microscopic approaches. A meta-study of the literature using these tools reveal that there are many small differences and ambiguities in the flocking scenarios being studied by different researchers and domains; unfortunately, these differences are of considerable significance. To address this issue, this dissertation exploits the predictable nature of the group’s behaviors in order to control the given group and thus hope to gain a fuller understanding of the collective. From the current literature, it is clear the environment is an important determinant in the resulting collective behaviors. This dissertation presents a method for reasoning about the effects the geometry of an environment has on individuals that exhibit collective behaviors in order to control them. This work formalizes the problem of controlling such groups by means of changing the environment in which the group operates and shows this problem to be PSPACE-Hard. A general methodology and basic framework is presented to address this problem. The proposed approach is general in that it is agnostic to the individual’s behaviors and geometric representations of the environment; allowing for a large variety in groups, desired behaviors, and environmental constraints to be considered. The results from both the simulations and over 80 robot trials show (1) the solution can automatically generate environments for reliably controlling various groups and (2) the solution can apply to other application domains; such as multi-agent formation planning for shepherding and piloting applications

Computational aspects of cellular intelligence and their role in artificial intelligence.

The work presented in this thesis is concerned with an exploration of the computational aspects of the primitive intelligence associated with single-celled organisms. The main aim is to explore this Cellular Intelligence and its role within Artificial Intelligence. The findings of an extensive literature search into the biological characteristics, properties and mechanisms associated with Cellular Intelligence, its underlying machinery - Cell Signalling Networks and the existing computational methods used to capture it are reported. The results of this search are then used to fashion the development of a versatile new connectionist representation, termed the Artificial Reaction Network (ARN). The ARN belongs to the branch of Artificial Life known as Artificial Chemistry and has properties in common with both Artificial Intelligence and Systems Biology techniques, including: Artificial Neural Networks, Artificial Biochemical Networks, Gene Regulatory Networks, Random Boolean Networks, Petri Nets, and S-Systems. The thesis outlines the following original work: The ARN is used to model the chemotaxis pathway of Escherichia coli and is shown to capture emergent characteristics associated with this organism and Cellular Intelligence more generally. The computational properties of the ARN and its applications in robotic control are explored by combining functional motifs found in biochemical network to create temporal changing waveforms which control the gaits of limbed robots. This system is then extended into a complete control system by combining pattern recognition with limb control in a single ARN. The results show that the ARN can offer increased flexibility over existing methods. Multiple distributed cell-like ARN based agents termed Cytobots are created. These are first used to simulate aggregating cells based on the slime mould Dictyostelium discoideum. The Cytobots are shown to capture emergent behaviour arising from multiple stigmergic interactions. Applications of Cytobots within swarm robotics are investigated by applying them to benchmark search problems and to the task of cleaning up a simulated oil spill. The results are compared to those of established optimization algorithms using similar cell inspired strategies, and to other robotic agent strategies. Consideration is given to the advantages and disadvantages of the technique and suggestions are made for future work in the area. The report concludes that the Artificial Reaction Network is a versatile and powerful technique which has application in both simulation of chemical systems, and in robotic control, where it can offer a higher degree of flexibility and computational efficiency than benchmark alternatives. Furthermore, it provides a tool which may possibly throw further light on the origins and limitations of the primitive intelligence associated with cells

Development of the huggable social robot Probo: on the conceptual design and software architecture

This dissertation presents the development of a huggable social robot named Probo. Probo embodies a stuffed imaginary animal, providing a soft touch and a huggable appearance. Probo's purpose is to serve as a multidisciplinary research platform for human-robot interaction focused on children. In terms of a social robot, Probo is classified as a social interface supporting non-verbal communication. Probo's social skills are thereby limited to a reactive level. To close the gap with higher levels of interaction, an innovative system for shared control with a human operator is introduced. The software architecture de nes a modular structure to incorporate all systems into a single control center. This control center is accompanied with a 3D virtual model of Probo, simulating all motions of the robot and providing a visual feedback to the operator. Additionally, the model allows us to advance on user-testing and evaluation of newly designed systems. The robot reacts on basic input stimuli that it perceives during interaction. The input stimuli, that can be referred to as low-level perceptions, are derived from vision analysis, audio analysis, touch analysis and object identification. The stimuli will influence the attention and homeostatic system, used to de ne the robot's point of attention, current emotional state and corresponding facial expression. The recognition of these facial expressions has been evaluated in various user-studies. To evaluate the collaboration of the software components, a social interactive game for children, Probogotchi, has been developed. To facilitate interaction with children, Probo has an identity and corresponding history. Safety is ensured through Probo's soft embodiment and intrinsic safe actuation systems. To convey the illusion of life in a robotic creature, tools for the creation and management of motion sequences are put into the hands of the operator. All motions generated from operator triggered systems are combined with the motions originating from the autonomous reactive systems. The resulting motion is subsequently smoothened and transmitted to the actuation systems. With future applications to come, Probo is an ideal platform to create a friendly companion for hospitalised children

Opinions and Outlooks on Morphological Computation

Morphological Computation is based on the observation that biological systems seem to carry out relevant computations with their morphology (physical body) in order to successfully interact with their environments. This can be observed in a whole range of systems and at many different scales. It has been studied in animals – e.g., while running, the functionality of coping with impact and slight unevenness in the ground is "delivered" by the shape of the legs and the damped elasticity of the muscle-tendon system – and plants, but it has also been observed at the cellular and even at the molecular level – as seen, for example, in spontaneous self-assembly. The concept of morphological computation has served as an inspirational resource to build bio-inspired robots, design novel approaches for support systems in health care, implement computation with natural systems, but also in art and architecture. As a consequence, the field is highly interdisciplinary, which is also nicely reflected in the wide range of authors that are featured in this e-book. We have contributions from robotics, mechanical engineering, health, architecture, biology, philosophy, and others

Advanced Knowledge Application in Practice

The integration and interdependency of the world economy leads towards the creation of a global market that offers more opportunities, but is also more complex and competitive than ever before. Therefore widespread research activity is necessary if one is to remain successful on the market. This book is the result of research and development activities from a number of researchers worldwide, covering concrete fields of research

An Approach Based on Particle Swarm Optimization for Inspection of Spacecraft Hulls by a Swarm of Miniaturized Robots

The remoteness and hazards that are inherent to the operating environments of space infrastructures promote their need for automated robotic inspection. In particular, micrometeoroid and orbital debris impact and structural fatigue are common sources of damage to spacecraft hulls. Vibration sensing has been used to detect structural damage in spacecraft hulls as well as in structural health monitoring practices in industry by deploying static sensors. In this paper, we propose using a swarm of miniaturized vibration-sensing mobile robots realizing a network of mobile sensors. We present a distributed inspection algorithm based on the bio-inspired particle swarm optimization and evolutionary algorithm niching techniques to deliver the task of enumeration and localization of an a priori unknown number of vibration sources on a simplified 2.5D spacecraft surface. Our algorithm is deployed on a swarm of simulated cm-scale wheeled robots. These are guided in their inspection task by sensing vibrations arising from failure points on the surface which are detected by on-board accelerometers. We study three performance metrics: (1) proximity of the localized sources to the ground truth locations, (2) time to localize each source, and (3) time to finish the inspection task given a 75% inspection coverage threshold. We find that our swarm is able to successfully localize the present so