L'objectif de cette thèse s'inscrit dans la cadre général du développement d'une stratégie de contrôle intelligent distribué en robotique collective. En effet, dans un avenir proche, de nombreux robots vont progressivement intégrer notre environnent aussi bien dans les milieux industriel que domestique. L'objectif de ces robots sera de fournir, de manière autonome, des services aux êtres humains afin de leurs faciliter la vie quotidienne comme par exemple dans le cas de robots compagnons. Ces services pourront être le résultat du travail d'un robot ou bien la conséquence de la coopération de plusieurs robots homogènes et/ou hétérogènes regroupés au sein d'un réseau. Dans ce contexte, si les progrès technologiques permettent sans problème de communiquer et d'échanger des données entre deux agents artificiels distants, la conception de stratégies de contrôle permettant l'auto-organisation de plusieurs robots dans le but de réaliser une tâche précise est encore aujourd'hui un verrou scientifique important. Cette thèse a donc pour but de proposer des pistes pour élaborer des stratégies de contrôle intelligent pour des systèmes multi-robots dans le cadre plus particulier de la logistique industrielle. En effet, le domaine de logistique industrielle nécessite l'utilisation de nombreux robots mobiles comme par exemple des AGV (Automatic Guided Vehicles) pour transporter et stoker des marchandises. Dans ce contexte, nous pensons que le domaine de la logistique peut tirer bénéfice de l'utilisation de systèmes multi-robots. Dans un premier temps, cette thèse aborde donc la problématique de transport d'objet volumineux et encombrant par une formation de robot. Effectivement, il semble que la solution qui consiste à utiliser un ensemble de robots identiques pour transporter des charges de grandes envergures soit, d'une part, très intéressante d'un point de vue économique et, d'autre part, plus robuste et flexible d'un point vue technologique. Dans un deuxième temps, cette thèse aborde l'utilisation d'un réseau de robots hétérogènes qui sont capables de s'organiser afin de réaliser une tâche précise dans un milieu dynamique. Les travaux effectués dans le cadre de la présente thèse doctorale ont donc abouti à la proposition des stratégies viables de contrôle intelligent pour des systèmes multi-robots. Une étude d'application des concepts étudiés a été réalisée, implantée et validée dans le cadre plus particulier de la logistique industrielle. Elle a concerné d'abord le contexte d'un groupe multi-robots homogène, puis a été étendue au contexte d'un système multi-robots hétérogènes. Les points forts des travaux réalisés peuvent être résumés comme ceci :- Proposition, conception, réalisation et validation expérimentale d'une stratégie de contrôle adaptatif par l'apprentissage artificiel pour un robot non-holonomique. Quatre publications internationales ont valorisé cette partie des travaux.- Proposition, conception, réalisation et validation expérimentale d'une stratégie de contrôle hybridant la vision artificielle et l'apprentissage artificiel pour un groupe de robots homogènes. Deux publications internationales ont valorisé cette partie des travaux.- Proposition, conception, réalisation et validation expérimentale d'une stratégie de contrôle hybridant la vision artificielle et l'apprentissage artificiel pour un groupe de robots hétérogènes. Deux publications internationales ont valorisé cette partie des travaux. Il est pertinent de souligner que les travaux relatifs aux aspects précités ont été couronnés par le prix : ″Innovation Award 2011″ de Industrial Robot / In this thesis, it concentrated the multi robot team navigating in an unknown environment. In our multi robot team, there is a humanoid robot as a leader and a team of two-wheel nonholonomic robots which form a vertical formation. Besides, a top camera and a computer which is a supervisor are the auxiliary robots in the multi robot team. The main purpose of the thesis is to propose an online and an offline navigation strategy for the closed and open area respectively. The core of navigation strategies is the same and it included path planning part and control part. Both the two parts constructed on the virtual structure of the formation robot team. In the former part, it improved the path planning part by the reinforcement Q learning and the image processing to acknowledge the unknown environment. And it applied the Adaptive Neural Fuzzy Inference System (ANFIS) algorithm to control of both the single nonholonomic robot and formation robot team. Furthermore, the strategies are applied to the formation robot team and the multi robot team in both closed and open environment. Simulations and real experiments are provided in the detail in the thesis. The strong points of the contribution are :- Proposition, conception, realization and experimental validation of machine learning based adaptive control for a nonholonomic single robot (in a group of robots). Four international publications have valorized this part of the doctoral Works. - Proposition, conception, realization and experimental validation of an adaptive intelligent control strategy hybridizing Artificial vision and Machine Learning for a group of nonholonomic homogeneous robots. Two international publications have valorized this part of the doctoral Works.- Proposition, conception, realization and experimental validation of an adaptive intelligent control strategy hybridizing Artificial vision and Machine Learning for a group of heterogeneous robots. Two international publications have valorized this part of the doctoral Works. It is pertinent to emphasize the investigations relative to the above-mentioned works have been awarded by: ″Innovation Award 2011″ of Industrial Robot

A aplicação de sistemas de múltiplos robôs é desejável em várias tarefas. Algumas delas são: exploração de ambientes, mineração, detecção de minas terrestres, segurança e operações de resgate. Uma estratégia eficiente de coordenação é decisiva para alcançar melhoras no desempenho. Neste projeto, duas novas estratégias são propostas para a coordenação de sistemas de múltiplos robôs, aplicadas para as tarefas de exploração, vigilância e formação. Elas são distribuídas, descentralizadas e ocorrem em tempo de execução. A inspiração para ambas advém de mecanismos biológicos que definem uma organização social de sistemas coletivos. Especificamente, considerou-se nesta tese uma versão modificada do sistema de colônia de formigas. As estratégias são adaptáveis para cenários em que o número de robôs e a estrutura do ambiente mudam. Em relação à primeira estratégia, os experimentos consideram dois critérios de desempenho: a média de ciclos de vigilância e a média de iterações em cada intervalo de segurança. Os resultados de simulação confirmam que a exploração e vigilância emergem da sinergia dos comportamentos individuais dos robôs. Os dados obtidos mostram que a estratégia de coordenação é eficiente e satisfatória para realizar as tarefas de exploração e vigilância. Quanto à segunda estratégia, o sistema apresenta as características desejáveis para que a formação seja mantida: separação, alinhamento e coesão. Evidências empíricas mostraram que o sistema possui boa habilidade dispersiva, o que promoveu o aumento da cobertura, e que o mesmo foi capaz de se adaptar a novas topologias de grupo e configurações de ambiente / The application of systems of multiple robots is desirable in various tasks. Some of them include: exploration, mining, land mine detection, security and rescue operations. An effective strategy for coordination is crucial to achieve performance improvements. In this project, two new strategies are proposed for the coordination of multiple robot systems, applied to the tasks of exploration, surveillance and formation. They are distributed, decentralized and performed in real time. The inspiration for both of them comes from the biological mechanisms that define a social organization of collective systems. Specifically, it was considered in this thesis a modified version of the Ant Colony System. The strategies are adaptable for scenarios where the number of robots and structure of the environment change. Regarding the first strategy, the experiments consider two performance criteria: average surveillance cycles and average iterations for each patrolling interval. Simulation results confirm that the exploration and surveillance emerge from the synergy of individual behaviors of robots. The data obtained show that the coordination strategy is efficient and and suitable to perform the tasks of exploration and surveillance. Regarding the second strategy, the system presents the characteristics desirable to maintain the formation: separation, alignment and cohesion. Empirical evidence showed that the system has good dispersive ability, which promoted an increase in coverage, and that it was able to adapt to new group topologies and environment settings

A aplicação de sistemas de múltiplos robôs é desejável em várias tarefas. Algumas delas são: exploração de ambientes, mineração, detecção de minas terrestres, segurança e operações de resgate. Uma estratégia eficiente de coordenação é decisiva para alcançar melhoras no desempenho. Neste projeto, duas novas estratégias são propostas para a coordenação de sistemas de múltiplos robôs, aplicadas para as tarefas de exploração, vigilância e formação. Elas são distribuídas, descentralizadas e ocorrem em tempo de execução. A inspiração para ambas advém de mecanismos biológicos que definem uma organização social de sistemas coletivos. Especificamente, considerou-se nesta tese uma versão modificada do sistema de colônia de formigas. As estratégias são adaptáveis para cenários em que o número de robôs e a estrutura do ambiente mudam. Em relação à primeira estratégia, os experimentos consideram dois critérios de desempenho: a média de ciclos de vigilância e a média de iterações em cada intervalo de segurança. Os resultados de simulação confirmam que a exploração e vigilância emergem da sinergia dos comportamentos individuais dos robôs. Os dados obtidos mostram que a estratégia de coordenação é eficiente e satisfatória para realizar as tarefas de exploração e vigilância. Quanto à segunda estratégia, o sistema apresenta as características desejáveis para que a formação seja mantida: separação, alinhamento e coesão. Evidências empíricas mostraram que o sistema possui boa habilidade dispersiva, o que promoveu o aumento da cobertura, e que o mesmo foi capaz de se adaptar a novas topologias de grupo e configurações de ambiente / The application of systems of multiple robots is desirable in various tasks. Some of them include: exploration, mining, land mine detection, security and rescue operations. An effective strategy for coordination is crucial to achieve performance improvements. In this project, two new strategies are proposed for the coordination of multiple robot systems, applied to the tasks of exploration, surveillance and formation. They are distributed, decentralized and performed in real time. The inspiration for both of them comes from the biological mechanisms that define a social organization of collective systems. Specifically, it was considered in this thesis a modified version of the Ant Colony System. The strategies are adaptable for scenarios where the number of robots and structure of the environment change. Regarding the first strategy, the experiments consider two performance criteria: average surveillance cycles and average iterations for each patrolling interval. Simulation results confirm that the exploration and surveillance emerge from the synergy of individual behaviors of robots. The data obtained show that the coordination strategy is efficient and and suitable to perform the tasks of exploration and surveillance. Regarding the second strategy, the system presents the characteristics desirable to maintain the formation: separation, alignment and cohesion. Empirical evidence showed that the system has good dispersive ability, which promoted an increase in coverage, and that it was able to adapt to new group topologies and environment settings