Evolution of Control Programs for a Swarm of Autonomous Unmanned Aerial Vehicles

Unmanned aerial vehicles (UAVs) are rapidly becoming a critical military asset. In the future, advances in miniaturization are going to drive the development of insect size UAVs. New approaches to controlling these swarms are required. The goal of this research is to develop a controller to direct a swarm of UAVs in accomplishing a given mission. While previous efforts have largely been limited to a two-dimensional model, a three-dimensional model has been developed for this project. Models of UAV capabilities including sensors, actuators and communications are presented. Genetic programming uses the principles of Darwinian evolution to generate computer programs to solve problems. A genetic programming approach is used to evolve control programs for UAV swarms. Evolved controllers are compared with a hand-crafted solution using quantitative and qualitative methods. Visualization and statistical methods are used to analyze solutions. Results indicate that genetic programming is capable of producing effective solutions to multi-objective control problems

Uma proposta evolutiva para controle inteligente em navegação autonoma de robos

Orientadores : Fernando Jose Von Zuben, Mauricio Fernandes FigueiredoDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de ComputaçãoResumo: Este trabalho apresenta um sistema autônomo evolutivo aplicado ao controle de um robô móvel em tarefas de navegação por ambientes desconhecidos. O sistema é reativo, não possui conhecimento inicial e aprende a lidar eficientemente com situações nas quais o robô tem que capturar alvos evitando colisões contra obstáculos. Para isto, ele desenvolve estratégias gerais de navegação, controlando a direção e a velocidade do robô sem qualquer auxílio externo. A abordagem evolutiva do sistema de navegação se baseia em uma versão de sistemas classificadores com aprendizado, contendo novos operadores, fluxos de controle adicionais e mecanismos específicos para o atendimento dos requisitos de navegação. Um extenso conjunto de experimentos é realizado, envolvendo: apenas simulação computacional; simulação computacional para síntese do controlador e transferência deste a um robô Khepera lI; e emprego do robô Khepera II tanto na síntese do controlador quanto na atuação em ambientes reais. Os resultados obtidos apontam para a validade da proposta, indicando a eficácia e capacidade de generalização do controlador autônomo quando submetido a variadas configurações de ambiente de navegaçãoAbstract: This work presents an autonomous evolutionary system applied to the control of a mobile robot when navigating in unknown environments. The system is reactive, it does not have initial knowledge and learns efficiently to deal with situations where the robot must capture targets avoiding collisions against obstacles. Toward this end, it develops general strategies, controlling the robot direction and speed without any external assistance. The evolutionary approach of the navigation system is based on a version of learning classifier systems, including new operators, additional control flows and specific mechanisms devoted to attending the navigation requirements. An extensive set of experiments is perfonned involving: just computer simulation; a controller matured by computer simulation, and then transferred to a Khepera II robot; and both the maturation and validation of the controller in real environments, Le. in a Khepera II robot. The obtained results indicate the validity of the proposal, attesting the efficiency and generalization capability of the autonomous controller when navigation environments with distinct configurations are considered.MestradoEngenharia de ComputaçãoMestre em Engenharia Elétric

Bioinspired computing systems : synthesis and application in computational intelligence and artificial homeostasis

Orientadores: Fernando Jose Von Zuben, Leandro Nunes de Castro SilvaTese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e ComputaçãoResumo: Este trabalho propõe uma classificação circunstancial para sistemas complexos, incluindo uma estrutura unificada de descrição a ser empregada na análise e síntese de sistemas computacionais bio-inspirados. Como um ramo dos sistemas complexos organizados, os sistemas computacionais bio-inspirados admitem uma sub-divisão em sistemas de inteligência computacional e sistemas homeostáticos artificiais. Com base neste formalismo, duas abordagens híbridas são concebidas e aplicadas em problemas de navegação autônoma de robôs. A primeira abordagem envolve sistemas classificadores com aprendizado e sistemas imunológicos artificiais, visando explorar conjuntamente conceitos intrínsecos a sistemas complexos, como auto-organização, evolução e cognição dinâmica. Fundamentada nas interações neuro-imuno-endócrinas do corpo humano, a segunda abordagem propõe um novo modelo de sistema homeostático artificial, explorando mudanças de contexto e efeitos do meio sobre o comportamento autônomo de um robô móvel. Embora preliminares, os resultados obtidos envolvem simulação computacional em ambientes virtuais e alguns experimentos com robôs reais, permitindo extrair conclusões relevantes acerca do potencial das abordagens propostas e abrindo perspectivas para a síntese de sistemas complexos adaptativos de interesse práticoAbstract: This work proposes a circumstantial classification for complex systems, including a unified description structure to be employed in the analysis and synthesis of biologically inspired computing metaphors. Considered as a branch of organized complex systems, these bio-inspired computing frameworks may be subdivided into computation intelligence systems and artificial homeostatic systems. Developed under this formalism, two novel hybrid systems are conceived and applied to robot autonomous navigation problems. The first approach involves learning classifier systems and artificial immune systems, in an attempt to investigate intrinsic concepts of complex systems as self-organization, evolution, and dynamic cognition. Drawn on the principles of the human nervous, immune and endocrine systems, the second approach envisages a new model of an artificial homeostatic system to explore context changes and environmental effects on the behaviour of an autonomous robotic agent. Though preliminary, the obtained results encompass computer simulation on virtual environments in addition to a number of real robot¿s experiments. Relevant conclusions can be invoked, mainly related to the potentiality of the proposed frameworks, thus opening attractive prospects for the synthesis of complex adaptive systems of practical interestDoutoradoEngenharia de ComputaçãoDoutor em Engenharia Elétric

Using MapReduce Streaming for Distributed Life Simulation on the Cloud

Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp