Response threshold models, stochastic learning automata and ant colony optimization-based decentralized self-coordination algorithms for heterogeneous multi-tasks distribution in multi-robot systems

In recent decades, there has been an increasing interest in systems comprised of several autonomous mobile robots, and as a result, there has been a substantial amount of development in the eld of Articial Intelligence, especially in Robotics. There are several studies in the literature by some researchers from the scientic community that focus on the creation of intelligent machines and devices capable to imitate the functions and movements of living beings. Multi-Robot Systems (MRS) can often deal with tasks that are dicult, if not impossible, to be accomplished by a single robot. In the context of MRS, one of the main challenges is the need to control, coordinate and synchronize the operation of multiple robots to perform a specic task. This requires the development of new strategies and methods which allow us to obtain the desired system behavior in a formal and concise way. This PhD thesis aims to study the coordination of multi-robot systems, in particular, addresses the problem of the distribution of heterogeneous multi-tasks. The main interest in these systems is to understand how from simple rules inspired by the division of labor in social insects, a group of robots can perform tasks in an organized and coordinated way. We are mainly interested on truly distributed or decentralized solutions in which the robots themselves, autonomously and in an individual manner, select a particular task so that all tasks are optimally distributed. In general, to perform the multi-tasks distribution among a team of robots, they have to synchronize their actions and exchange information. Under this approach we can speak of multi-tasks selection instead of multi-tasks assignment, which means, that the agents or robots select the tasks instead of being assigned a task by a central controller. The key element in these algorithms is the estimation ix of the stimuli and the adaptive update of the thresholds. This means that each robot performs this estimate locally depending on the load or the number of pending tasks to be performed. In addition, it is very interesting the evaluation of the results in function in each approach, comparing the results obtained by the introducing noise in the number of pending loads, with the purpose of simulate the robot's error in estimating the real number of pending tasks. The main contribution of this thesis can be found in the approach based on self-organization and division of labor in social insects. An experimental scenario for the coordination problem among multiple robots, the robustness of the approaches and the generation of dynamic tasks have been presented and discussed. The particular issues studied are: Threshold models: It presents the experiments conducted to test the response threshold model with the objective to analyze the system performance index, for the problem of the distribution of heterogeneous multitasks in multi-robot systems; also has been introduced additive noise in the number of pending loads and has been generated dynamic tasks over time. Learning automata methods: It describes the experiments to test the learning automata-based probabilistic algorithms. The approach was tested to evaluate the system performance index with additive noise and with dynamic tasks generation for the same problem of the distribution of heterogeneous multi-tasks in multi-robot systems. Ant colony optimization: The goal of the experiments presented is to test the ant colony optimization-based deterministic algorithms, to achieve the distribution of heterogeneous multi-tasks in multi-robot systems. In the experiments performed, the system performance index is evaluated by introducing additive noise and dynamic tasks generation over time.

A level II reliability approach to tunnel support design

A reliability approach to tunnel support design is presented in this paper. The aim of the work is the incorporation of classical Level II techniques to the current design method based on the study of the ground-support interaction diagram.

Treatment of singularities in 2-D domains using BIEM

The singularities which arise when there is a sudden change of boundary conditions are modelled using spectral shape interpolation functions. The procedure can be used for elasticity as well as potential theory and to any degree of accuracy with respect to the smooth part of the curve.

A fatigue damage model for seismic response of RC structures

Numerous damage models have been developed in order to analyze seismic behavior. Among the different possibilities existing in the literature, it is very clear that models developed along the lines of continuum damage mechanics are more consistent with the definition of damage as a phenomenon with mechanical consequences because they include explicitly the coupling between damage and mechanical behavior. On the other hand, for seismic processes, phenomena such as low cycle fatigue may have a pronounced effect on the overall behavior of the frames and, therefore, its consideration turns out to be very important. However, most of existing models evaluate the damage only as a function of the maximum amplitude of cyclic deformation without considering the number of cycles. In this paper, a generalization of the simplified model proposed by Cipollina et al. [Cipollina A, López-Hinojosa A, Flórez-López J. Comput Struct 1995;54:1113–26] is made in order to include the low cycle fatigue. Such a model employs in its formulation irreversible thermodynamics and internal state variable theory.

Neutron spectrometry using artificial neural networks for a bonner sphere spectrometer with 3He detector

Neutron spectra unfolding and dose equivalent calculation are complicated tasks in radiation protection, are highly dependent of the neutron energy, and a precise knowledge on neutron spectrometry is essential for all dosimetry-related studies as well as many nuclear physics experiments. In previous works have been reported neutron spectrometry and dosimetry results, by using the ANN technology as alternative solution, starting from the count rates of a Bonner spheres system with a LiI(Eu) thermal neutrons detector, 7 polyethylene spheres and the UTA4 response matrix with 31 energy bins. In this work, an ANN was designed and optimized by using the RDANN methodology for the Bonner spheres system used at CIEMAT Spain, which is composed of a He neutron detector, 12 moderator spheres and a response matrix for 72 energy bins. For the ANN design process a neutrons spectra catalogue compiled by the IAEA was used. From this compilation, the neutrons spectra were converted from lethargy to energy spectra. Then, the resulting energy ?uence spectra were re-binned by using the MCNP code to the corresponding energy bins of the He response matrix before mentioned. With the response matrix and the re-binned spectra the counts rate of the Bonner spheres system were calculated and the resulting re-binned neutrons spectra and calculated counts rate were used as the ANN training data set.

Performance of artificial neural networks and genetical evolved artificial neural networks unfolding techniques

With the Bonner spheres spectrometer neutron spectrum is obtained through an unfolding procedure. Monte Carlo methods, Regularization, Parametrization, Least-squares, and Maximum Entropy are some of the techniques utilized for unfolding. In the last decade methods based on Artificial Intelligence Technology have been used. Approaches based on Genetic Algorithms and Artificial Neural Networks have been developed in order to overcome the drawbacks of previous techniques. Nevertheless the advantages of Artificial Neural Networks still it has some drawbacks mainly in the design process of the network, vg the optimum selection of the architectural and learning ANN parameters. In recent years the use of hybrid technologies, combining Artificial Neural Networks and Genetic Algorithms, has been utilized to. In this work, several ANN topologies were trained and tested using Artificial Neural Networks and Genetically Evolved Artificial Neural Networks in the aim to unfold neutron spectra using the count rates of a Bonner sphere spectrometer. Here, a comparative study of both procedures has been carried out.

Experimental and Analytical Study of Masonry Infill Reinforced Concrete Frames Retrofitted with Steel Braces

In the present work a seismic retrofitting technique is proposed for masonry infilled reinforced concrete frames based on the replacement of infill panels by K-bracing with vertical shear link. The performance of this technique is evaluated through experimental tests. A simplified numerical model for structural damage evaluation is also formulated according to the notions and principles of continuum damage mechanics. The proposed model is calibrated with the experimental results. The experimental results have shown an excellent energy dissipation capacity with the proposed technique. Likewise, the numerical predictions with the proposed model are in good agreement with experimental results.

Reacondicionamiento sísmico de pórticos de hormigón armado con relleno de mampostería

Tanto las investigaciones experimentales y numéricas como las observaciones llevadas a cabo en áreas afectadas por terremotos aportan de forma continua nuevos datos sobre el comportamiento sísmico de las construcciones. Los avances en este campo redundan en normativas más exigentes y sistemas constructivos más efectivos. Dentro de la ingeniería sísmica, uno de los objetivos está en proporcionar métodos simplificados de evaluación del daño potencial en una estructura sometida a acciones sísmicas como forma de medir la posible reparabilidad de la misma. En el presente trabajo se propone una técnica de reacondicionamiento sísmico aplicada a pórticos de hormigón armado con relleno de mampostería. La eficiencia de dicha técnica es evaluada mediante ensayos experimentales. Asimismo se propone un modelo numérico simplificado de evaluación de daño estructural cuya validación es llevada a cabo con los resultados experimentales anteriores.

Abutments influence in the dynamic response of bridges

A simplified analytical model of a short span bridge is proposed. The inertial interaction effects of pier foundations and abutments has been included in order to evaluate the response sensitivities to different soil-structure interaction variables. The modification of natural frequency and damping properties is shown for typical short span bridges of the integral deck-abutment type for longitudinal vibrations or general bridges for the transverse ones.

Physical and mathematical modeling of wave propagation in the Ariane 5 VEB structure

The separation of the lower stage of the ARIANE 5 Vehicle Equipment Bay (VEB) Structure is to be done using a pyrotechnic device. The wave propagation effects produced by the explosion can affect the electronic equipment, so it was decided to analyze, using both physical and numerical modeling, a small piece of the structure to determine the distribution of the accelerations and the relative importance of damping, stiffness, connections, etc. on the response of the equipment.

QL-CONST1: an expert system for quality level prediction in concrete structures

Current trends in the fields of artifical intelligence and expert systems are moving towards the exciting possibility of reproducing and simulating human expertise and expert behaviour into a knowledge base, coupled with an appropriate, partially ‘intelligent’, computer code. This paper deals with the quality level prediction in concrete structures using the helpful assistance of an expert system, QL-CONST1, which is able to reason about this specific field of structural engineering. Evidence, hypotheses and factors related to this human knowledge field have been codified into a knowledge base. This knowledge base has been prepared in terms of probabilities of the presence of either hypotheses or evidence and the conditional presence of both. Human experts in the fields of structural engineering and the safety of structures gave their invaluable knowledge and assistance to the construction of the knowledge base. Some illustrative examples for, the validation of the expert system behaviour are included.

Dynamic impedances of bridge abutments

The soil-structure interaction at bridge abutments may introduce important changes in the dynamic properties of short to medium span bridges. The paper presents the results obtained, through the use of the Boundary Element Method (B.E.M.) technique in several typical situations, including semiinfinite and layered media. Both stiffness and damping properties are included.

Importance of local modes in seismic response of bridges

The paper describes a simple approach to study the importance of local modes in the dimensioning load of bridge columns.

Expert systems for quality prediction in structural engineering

This work deals with quality level prediction in concrete structures through the helpful assistance of an expert system wich is able to apply reasoning to this field of structural engineering. Evidences, hypotheses and factors related to this human knowledge field have been codified into a Knowledge Base in terms of probabilities for the presence of either hypotheses or evidences,and conditional presence of both. Human experts in structural engineering and safety of structures gave their invaluable knowledge and assistance necessary when constructing the "computer knowledge body".

Graph based study of allergen cross-reactivity of plant lipid transfer proteins (LTPs) using microarray in a multicenter study.

The study of cross-reactivity in allergy is key to both understanding. the allergic response of many patients and providing them with a rational treatment In the present study, protein microarrays and a co-sensitization graph approach were used in conjunction with an allergen microarray immunoassay. This enabled us to include a wide number of proteins and a large number of patients, and to study sensitization profiles among members of the LTP family. Fourteen LTPs from the most frequent plant food-induced allergies in the geographical area studied were printed into a microarray specifically designed for this research. 212 patients with fruit allergy and 117 food-tolerant pollen allergic subjects were recruited from seven regions of Spain with different pollen profiles, and their sera were tested with allergen microarray. This approach has proven itself to be a good tool to study cross-reactivity between members of LTP family, and could become a useful strategy to analyze other families of allergens.