Strategi Self-Assembly Paralel pada Swarm Robot

ABSTRAK Dari banyaknya strategi yang diusulkan untuk proses self-assembly pada swarm robotics, hanya beberapa grup riset berkonsentrasi di bidang ini yang mengusulkan proses paralel pada penggabungan antar robot. Tetapi, strategi ini hanya digunakan ketika sebuah robot memerlukan tumpuan dari dua robot atau lebih pada satu waktu. Berdasar pada kebutuhan untuk menyebarkan ratusan hingga ribuan robot pada satu swarm, strategi penggabungan antar robot satu-demi-satu memerlukan waktu yang sangat lama untuk diselesaikan. Di artikel ini, strategi self-assembly antar robot pada suatu swarm secara paralel diusulkan untuk mengurangi waktu proses self-assembly dengan menempatkan sejumlah robot di posisi tertentu. Saat penggabungan, robot-robot ini akan bergerak menempatkan dirinya sesuai dengan posisi akhir yang ditargetkan. Hasil menunjukkan bahwa strategi ini dapat mereduksi waktu proses self-assembly hingga setengah dari waktu yang diperlukan dengan proses penggabungan satu-demi-satu. Kata kunci: swarm robot, self-assembly, proses paralel   ABSTRACT Despite the number of strategies proposed for self-assembly process in swarm robotics, only few research groups working in this area have proposed the parallel process of robots assembled each other. However, this strategy only works when a robot needs to be supported by two or more robots in a time. When deploying hundred to thousand robots in a swarm is required, the strategy of robots connecting to the structure of assembled robots in a one-by-one manner requires an extremely long time to accomplish. In this paper, a strategy of parallel selfassembly for robots in a swarm is proposed for reducing the self-assembly process time by placing a number of robots at particular positions. While connecting, they will move to position themselves appropriately to the targeted final structure. Result shows that this strategy can reduce the process of self-assembly time up to half of the time required for one-by-one process. Keywords: swarm robots, self-assembly, parallel proces

Locomotion through morphology, evolution and learning for legged and limbless robots

Mención Internacional en el título de doctorRobot locomotion is concerned with providing autonomous locomotion capabilities to mobile robots. Most current day robots feature some form of locomotion for navigating in their environment. Modalities of robot locomotion includes: (i) aerial locomotion, (ii) terrestrial locomotion, and (iii) aquatic locomotion (on or under water). Three main forms of terrestrial locomotion are, legged locomotion, limbless locomotion and wheel-based locomotion. A Modular Robot (MR), on the other hand, is a robotic system composed of several independent unit modules, where, each module is a robot by itself. The objective in this thesis is to develop legged locomotion in a humanoid robot, as well as, limbless locomotion in modular robotic configurations. Taking inspiration from biology, robot locomotion from the perspective of robot’s morphology, through evolution, and through learning are investigated in this thesis. Locomotion is one of the key distinguishing characteristics of a zoological organism. Almost all animal species, and even some plant species, produce some form of locomotion. In the past few years, robots have been “moving out” of the factory floor and research labs, and are becoming increasingly common in everyday life. So, providing stable and agile locomotion capabilities for robots to navigate a wide range of environments becomes pivotal. Developing locomotion in robots through biologically inspired methods, also facilitates furthering our understanding on how biological processes may function. Connected modules in a configuration, exert force on each other as a result of interaction between each other and their environment. This phenomenon is studied and quantified, and then used as implicit communication between robot modules for producing locomotion coordination in MRs. Through this, a strong link between robot morphology and the gait that emerge in it is established. A variety of locomotion controller, some periodic-function based and some morphology based, are developed for MR locomotion and bipedal gait generation. A hybrid Evolutionary Algorithm (EA) is implemented for evolving gaits, both in simulation as well as in the real-world on a physical modular robotic configuration. Limbless gaits in MRs are also learnt by learning optimal control policies, through Reinforcement Learning (RL).En robótica, la locomoción trata de proporcionar capacidades de locomoción autónoma a robots móviles. La mayoría de los robots actuales tiene alguna forma de locomoción para navegar en su entorno. Los modos de locomoción robótica se pueden repartir entre: (i) locomoción aérea, (ii) locomoción terrestre, y (iii) locomoción acuática (sobre o bajo el agua). Las tres formas básicas de locomoción terrestre son la locomoción mediante piernas, la locomoción sin miembros, y la locomoción basada en ruedas. Un Robot Modular, por otra parte, es un sistema robótico compuesto por varios módulos independientes, donde cada módulo es un robot en sí mismo. El objetivo de esta tesis es el desarrollo de la locomoción mediante piernas para un robot humanoide, así como el de la locomoción sin miembros para varias configuraciones de robots modulares. Inspirándose en la biología, también se investiga en esta tesis el desarrollo de la locomoción del robot según su morfología, gracias a técnicas de evolución y de aprendizaje. La locomoción es una de las características distintivas de un organismo zoológico. Casi todas las especies animales, e incluso algunas especies de plantas, poseen algún tipo de locomoción. En los últimos años, los robots han “migrado” desde las fábricas y los laboratorios de investigación, y se están integrando cada vez más en nuestra vida diaria. Por estas razones, es crucial proporcionar capacidades de locomoción estables y ágiles a los robots para que puedan navegar por todo tipo de entornos. El uso de métodos de inspiración biológica para alcanzar esta meta también nos ayuda a entender mejor cómo pueden funcionar los procesos biológicos equivalentes. En una configuración de módulos conectados, puesto que cada uno interacciona con su entorno, los módulos ejercen fuerza los unos sobre los otros. Este fenómeno se ha estudiado y cuantificado, y luego se ha usado como comunicación implícita entre los módulos para producir la coordinación en la locomoción de este robot. De esta manera, se establece un fuerte vínculo entre la morfología de un robot y el modo de andar que este desarrolla. Se han desarrollado varios controladores de locomoción para robots modulares y robots bípedos, algunos basados en funciones periódicas, otros en la morfología del robot. Un algoritmo evolutivo híbrido se ha implementado para la evolución de locomociones, tanto en simulación como en el mundo real en una configuración física de robot modular. También se pueden generar locomociones sin miembros para robots modulares, determinando las políticas de control óptimo gracias a técnicas de aprendizaje por refuerzo. Se presenta en primer lugar en esta tesis el estado del arte de la robótica modular, enfocándose en la locomoción de robots modulares, los controladores, la locomoción bípeda y la computación morfológica. A continuación se describen cinco configuraciones diferentes de robot modular que se utilizan en esta tesis, seguido de cuatro controladores de locomoción. Estos controladores son el controlador heterogéneo, el controlador basado en funciones periódicas, el controlador homogéneo y el controlador basado en la morfología del robot. Se desarrolla como parte de este trabajo un controlador de locomoción lineal, periódico, basado en features, para la locomoción bípeda de robots humanoides. Los parámetros de control se ajustan primero a mano para reproducir un modelo cart-table, y el controlador se evalúa en un robot humanoide simulado. A continuación, gracias a un algoritmo evolutivo, la optimización de los parámetros de control permite desarrollar una locomoción sin modelo predeterminado. Se desarrolla como parte de esta tesis un enfoque sobre algoritmos de Embodied Evolución, en otras palabras el uso de robots modulares físicos en la fase de evolución. La implementación material, la configuración experimental, y el Algoritmo Evolutivo implementado para Embodied Evolución, se explican detalladamente. El trabajo también incluye una visión general de las técnicas de aprendizaje por refuerzo y de los Procesos de Decisión de Markov. A continuación se presenta un algoritmo popular de aprendizaje por refuerzo, llamado Q-Learning, y su adaptación para aprender locomociones de robots modulares. Se proporcionan una implementación del algoritmo de aprendizaje y la evaluación experimental de la locomoción generada.Programa Oficial de Doctorado en Ingeniería Eléctrica, Electrónica y AutomáticaPresidente: Antonio Barrientos Cruz.- Secretario: Luis Santiago Garrido Bullón.- Vocal: Giuseppe Carbon

The State of the Art of Information Integration in Space Applications

This paper aims to present a comprehensive survey on information integration (II) in space informatics. With an ever-increasing scale and dynamics of complex space systems, II has become essential in dealing with the complexity, changes, dynamics, and uncertainties of space systems. The applications of space II (SII) require addressing some distinctive functional requirements (FRs) of heterogeneity, networking, communication, security, latency, and resilience; while limited works are available to examine recent advances of SII thoroughly. This survey helps to gain the understanding of the state of the art of SII in sense that (1) technical drivers for SII are discussed and classified; (2) existing works in space system development are analyzed in terms of their contributions to space economy, divisions, activities, and missions; (3) enabling space information technologies are explored at aspects of sensing, communication, networking, data analysis, and system integration; (4) the importance of first-time right (FTR) for implementation of a space system is emphasized, the limitations of digital twin (DT-I) as technological enablers are discussed, and a concept digital-triad (DT-II) is introduced as an information platform to overcome these limitations with a list of fundamental design principles; (5) the research challenges and opportunities are discussed to promote SII and advance space informatics in future

Analysis of kinematics and dynamics of modular robot assemblies

The development of self-reconfigurable modular robots has experienced significant progress. Continuous improvement during the past twenty years produced flexible and easy maintainable robot mechanisms. Self reconfiguring modular robots consist of various similar robotic modules and are designed to establish manifold connections between each of these link modules. Moreover these modules are able to perform movements to change the shape or the position of the robotic chain. In this thesis the main focus lies on the analysis of kinematics and dynamics of small modular robot organisms and their movement pattern. Although diverse linkage mechanisms do exist, practically no motion of one module can be accomplished without interacting with a second one. Therefore furthermore fundamental is the study and examination of dyad kinematics which represent the pattern of movement between solely two modules. However generation and simulation of models of modular robot kinematics and dynamics are complex and manual derivation needs tremendous efforts as every configuration and alternation of shape induce new changes of parameters´ values. Besides machinedriven computation requires a great deal of energy and increased storage capacity if every module constellation and applicable movements are predefined in a database. To avoid this squandering of resources a framework is implemented in Matlab based on Chen´s theory to design an accurate dynamic model. In the end, this thesis shall provide a farther step towards a robust and flexible modular robot organism which is able to perform reliable interaction with the environment to constitute to an optimized and effective realization of tasks assigned to it in industry or in the future private households

HCC Architecture - Hormonal Communications and Control Architecture

This thesis aims to provide a novel framework for a multiagent system implementation. The major feature of the proposed architecture is the introduction of the biological concept of hormones. The hormones are passed via the communication network to convey limited global system state knowledge. The agents\u27 response to a hormone is interpreted depending on its own local agent state. The primary focus of this thesis is the development of the particulars of the architecture. Prior work of multiagent systems research is reviewed and studied for contributions. Biological studies of hormones are employed to draw out interaction rules and analyze control mechanisms in a biological organism. The hormonal communication and control architecture is constructed, with major components detailed by flowcharts. The proposal is tested with two simulations: A minesweeping problem that has been modeled by other models, and an application of the architecture to a hypothetical ant colony. Research on biological ants is presented to suggest the behavior and goals of a model configured to employ the HCC architecture. The model is fleshed out, and the decisions made by considerations to the architecture are explained. The implementation of the simulation programming with the SWARM programming libraries for the Objective-C language is discussed. The data from experimental runs are analyzed with attention to global action

Towards a Boolean network-based Computational Model for Cell Differentiation and its applications to Robotics

Living organisms are the ultimate product of a series of complex processes that take place within—and among—biological cells. Most of these processes, such as cell differentiation, are currently poorly understood. Cell differentiation is the process by which cells progressively specialise. Being a fundamental process within cells, its dysregulations have dramatic implications in biological organisms ranging from developmental issues to cancer formation. The thesis objective is to contribute to the progress in the understanding of cell differentiation and explore the applications of its properties for designing artificial systems. The proposed approach, which relies on Boolean networks based modelling and on the theory of dynamical systems, aims at investigating the general mechanisms underlying cell differentiation. The results obtained contribute to taking a further step towards the formulation of a general theoretical framework—so far missing—for cellular differentiation. We conducted an in-depth analysis of the impact of self-loops in random Boolean networks ensembles. We proposed a new model of differentiation driven by a simplified bio-inspired methylation mechanism in Boolean models of genetic regulatory networks. On the artificial side, by introducing the conceptual metaphor of the “attractor landscape” and related proofs of concept that support its potential, we paved the way for a new research direction in robotics called behavioural differentiation robotics: a branch of robotics dealing with the designing of robots capable of expressing different behaviours in a way similar to that of biological cells that undergo differentiation. The implications of the results achieved may have beneficial effects on medical research. Indeed, the proposed approach can foster new questions, experiments and in turn, models that hopefully in the next future will take us to cure differentiation-related diseases such as cancer. Our work may also contribute to address questions concerning the evolution of complex behaviours and to help design robust and adaptive robots

Analysis and implementation of control strategies for multibody robotic systems

Multibody robotic organisms are reconfigurable dynamic systems. Thus the shape and the structure of a modular robot is not constant. Depending on the changing environment or on the current task of the robot its structure can be rearranged accordingly. Hence, that would also change the dynamic model of the robotic organism. Thus the kinematics and dynamics of the current modular structure of the robot, and with it also an appropriate control strategy, can not be calculated in advance

Self-repair during continuous motion with modular robots

Through the use of multiple modules with the ability to reconfigure to form different morphologies, modular robots provide a potential method to develop more adaptable and resilient robots. Robots operating in challenging and hard-to-reach environments such as infrastructure inspection, post-disaster search-and-rescue under rubble and planetary surface exploration, could benefit from the capabilities modularity offers, especially the inherent fault tolerance which reconfigurability can provide. With self-reconfigurable modular robots self-repair, removing failed modules from a larger structure to replace them with operating modules, allows the functionality of the multi-robot organism as a whole to be recovered when modules are damaged. Previous self-repair work has, for the duration of self-repair procedures, paused group tasks in which the multi-robot organism was engaged, this thesis investigates Self-repair during continuous motion, ``Dynamic Self-repair", as a way to allow repair and group tasks to proceed concurrently. In this thesis a new modular robotic platform, Omni-Pi-tent, with capabilities for Dynamic Self-repair is developed. This platform provides a unique combination of genderless docking, omnidirectional locomotion, 3D reconfiguration possibilities and onboard sensing and autonomy. The platform is used in a series of simulated experiments to compare the performance of newly developed dynamic strategies for self-repair and self-assembly to adaptations of previous work, and in hardware demonstrations to explore their practical feasibility. Novel data structures for defining modular robotic structures, and the algorithms to process them for self-repair, are explained. It is concluded that self-repair during continuous motion can allow modular robots to complete tasks faster, and more effectively, than self-repair strategies which require collective tasks to be halted. The hardware and strategies developed in this thesis should provide valuable lessons for bringing modular robots closer to real-world applications