Recently, there has been an increasing interest in robotics related to multi-robot applications. Such systems can be involved in several tasks such as collaborative search and rescue, aerial transportation, surveillance, and monitoring, to name a few. There are two possible architectures for the autonomous control of multi-robot systems. In the centralized architecture, a master controller communicates with all the robots to collect information. It uses this information to make decisions for the entire system and then sends commands to each robot. In contrast, in the distributed architecture, each robot makes its own decision independent from a central authority. While distributed architecture is a more portable solution, it comes at the expense of extensive information exchange (communication). The extensive communication between robots can result in decision delays because of which distributed architecture is often impractical for systems with strict real-time constraints, e.g. when decisions have to be taken in the order of milliseconds. In this thesis, we propose a distributed framework that strikes a balance between limited communicated information and reasonable system-wide performance while running in real-time. We implement the proposed approach in a game setting of two competing teams of drones, defenders and attackers. Defending drones execute a proposed linear program algorithm (using only onboard computing modules) to obstruct attackers from infiltrating a defense zone while having minimal local message passing. Another main contribution is that we developed a realistic simulation environment as well as lab and outdoor hardware setups of customized drones for testing the system in realistic scenarios. Our software is completely open-source and fully integrated with the well-known Robot Operating System (ROS) in hopes to make our work easily reproducible and for rapid future improvements.

Research on autonomous intelligent systems has focused on how robots can robustly carry out missions in uncertain and harsh environments with very little or no human intervention. Robotic execution languages such as RAPs, ESL, and TDL improve robustness by managing functionally redundant procedures for achieving goals. The model-based programming approach extends this by guaranteeing correctness of execution through pre-planning of non-deterministic timed threads of activities. Executing model-based programs effectively on distributed autonomous platforms requires distributing this pre-planning process. This thesis presents a distributed planner for modelbased programs whose planning and execution is distributed among agents with widely varying levels of processor power and memory resources. We make two key contributions. First, we reformulate a model-based program, which describes cooperative activities, into a hierarchical dynamic simple temporal network. This enables efficient distributed coordination of robots and supports deployment on heterogeneous robots. Second, we introduce a distributed temporal planner, called DTP, which solves hierarchical dynamic simple temporal networks with the assistance of the distributed Bellman-Ford shortest path algorithm. The implementation of DTP has been demonstrated successfully on a wide range of randomly generated examples and on a pursuer-evader challenge problem in simulation.

This thesis focuses on the development of a distributed software project planning tool that enables more than one participant to prepare the different parts of the project scope, schedule and task assignment by allowing to utilize the predefined organizational level processes. For this purpose, we discuss the need for a distributed software project planning tool, identify tool requirements and compare available tools with respect to the requirements. In addition, we evaluate the tool based on two criteria: first one is the tool&rsquo / s adequacy to meet the identified functional attributes and the second one is the validation of the tool by utilizing the data of the project schedule of a real project. This tool enables preparation of project scope, schedule and task assignments in a more effective, accurate and seamless way.

Les travaux de cette thèse visent à mettre en place une gestion prédictive sous incertitudes de la ressource en eau pour les réseaux de voies navigables. L'objectif est de proposer un plan de gestion de l'eau pour optimiser les conditions de navigation de l'ensemble du réseau supervisé sur un horizon spécifié. La solution attendue doit rendre le réseau résilient aux effets probables du changement climatique et aux évolutions du trafic fluvial. Dans un premier temps, une modélisation générique d'une ressource distribuée sur un réseau est proposée. Celle-ci, basée sur les processus décisionnels markoviens, prend en compte les nombreuses incertitudes affectant les réseaux considérés. L'objectif de cette modélisation est de couvrir l'ensemble des cas possibles, prévus ou non, afin d'avoir une gestion résiliente de ces réseaux. La seconde contribution consiste en une distribution du modèle sur plusieurs agents afin de permettre son passage à l'échelle. Ceci consiste en une répartition des capacités de contrôle du réseau entre les agents. Chaque agent ne possède ainsi qu'une connaissance locale du réseau supervisé. De ce fait, les agents ont besoin de se cordonner pour proposer une gestion efficace du réseau. Une résolution itérative avec échanges de plans temporaires de chaque agent est utilisée pour l'obtention de politiques de gestion locales à chaque agent. Finalement, des expérimentations ont été réalisées sur des réseaux réels de voies navigables françaises pour observer la qualité des solutions produites. Plusieurs scénarios climatiques différents ont été simulés pour tester la résilience des politiques produites. / The work of this thesis aims to introduce and implement a predictive management under uncertainties of the water resource for inland waterway networks. The objective is to provide a water management plan to optimize the navigation conditions of the entire supervised network over a specified horizon. The expected solution must render the network resilient to probable effects of the climate change and changes in waterway traffic. Firstly, a generic modeling of a resource distributed on a network is proposed. This modeling, based on Markovian Decision Processes, takes into account the numerous uncertainties affecting considered networks. The objective of this modeling is to cover all possible cases, foreseen or not, in order to have a resilient management of those networks. The second contribution consists in a distribution of the model over several agents to facilitate the scaling. This consists of a repartition of the network's control capacities among the agents. Thus, each agent has only local knowledge of the supervised network. As a result, agents require coordination to provide an efficient management of the network. An iterative resolution, with exchanges of temporary plans from each agent, is used to obtain local management policies for each agent. Finally, experiments were carried out on realistic and real networks of the French waterways to observe the quality of the solutions produced. Several different climatic scenarios have been simulated to test the resilience of the produced policies.

Aujourd’hui, la production est souvent multi-site car les entreprises se recentrent sur leurs cœurs de métiers. Dans ce contexte, la gestion des projets est une tâche difficile car il faut prendre en compte la distribution de la décision et l’hétérogénéité qui peut exister entre les différentes applications de production des partenaires. Les Systèmes Multi-Agents, et notamment le modèle SCEP (Superviseur, Client, Environnement, Producteur), apportent une solution satisfaisante au problème de la distribution de la décision, en instaurant une coopération entre des agents responsables de la gestion des projets client et des agents représentant les sites de production distants. Néanmoins, ce modèle présente des limites à cause de sa faible capacité à communiquer et à coopérer avec des modèles et des systèmes de gestion hétérogènes ainsi qu’à sa difficulté à localiser les nouveaux partenaires. Dans ce mémoire, nous proposons une architecture distribuée et interopérable SCEP-SOA intégrant les concepts du modèle SCEP et ceux du modèle SOA (Service Oriented Architecture) qui offre des mécanismes de mise en relation des partenaires et permet des communications entre des systèmes et des applications hétérogènes. Pour garantir la bonne compréhension des informations échangées entre les partenaires, l’architecture SCEP-SOA met en œuvre une stratégie d’interopérabilité sémantique basée sur l’intégration des ontologies. Cette stratégie s’articule autour d’une ontologie globale et commune utilisée pour l’échange des informations, et des mécanismes de correspondances entre cette ontologie globale et les ontologies locales des partenaires. Cette architecture est illustrée sur un cas d’étude où l’on se focalise sur l’interopérabilité entre des applications dédiées à la planification des projets de fabrication multi-sites. / Today, the production is often multi-site because companies focus on their core competencies. In this context, projects’ management is a difficult task because it must take into account the distribution of the decision and the heterogeneity which can exist between the various production applications of the partners. The Multi-agents systems, in particular the SCEP model (Supervisor, Customer, Environment, Producer), offer a satisfactory solution for the decision distribution problem, by establishing a cooperation between agents responsible of the management of the customer projects and agents representing the remote production sites. Nevertheless, this model presents limits because of its weak ability to communicate and to cooperate with heterogeneous models and management systems, as well as in its difficulty to localize new partners. In this dissertation, we propose a distributed and interoperable architecture, SCEP-SOA, which integrates concepts of the SCEP model and SOA (Service Oriented Architecture) which offers mechanisms for putting in relation various partners and allows communication between heterogeneous systems and applications. To insure the good understanding of the information exchanged between the partners, the SCEP-SOA architecture implements a strategy of semantic interoperability based on the integration of ontologies. This strategy is based on the use of a shared global ontology for information exchange, and on mechanisms of mappings between the global ontology and the partners’ local ontologies. This architecture is illustrated by a study case in which we focus on the interoperability between applications dedicated to the planning of manufacturing multi-sites projects