Suchergebnisse

This thesis presents the study and the implementation of a system that manages autonomously the configuration of a formation of unmanned aerial vehicles, or UAVs. The purposes are to improve the safety and the efficiency of a group of military UAVs, and to fill the gap between mission planning layers and formation control layers. Formation flight is particularly suited for military applications in hostile environments, that require synchronizations on target arrivals or mutual support for jamming. One of the difficulties raised is the autonomous choice of the configuration. Our approach is to develop an intermediate layer, dedicated to the formation and to the management of its configuration, between the deliberative and functionnal layers. Once a configuration is specified, it has to be allocated to the UAVs according to the tactical constraints and the available ressources. As the safety of the flight is a prime issue, reconfiguration maneuvers are planned to switch between two configurations, with respect to a security distance. Solutions have been developed based on the Branch & Bound algorithm to solve the assigment problems, and on the A* algorithm for reconfiguration trajectories planning. Moreover, a formation control has been implemented, allowing to validate our approach, both with simulations and real experimentations. ; L'objet de cette thèse est l'étude et la mise en oeuvre d'un système de gestion automatique de la configuration d'une formation d'avions sans pilote, ou drones. Les objectifs sont, d'une part, d'améliorer la sécurité et l'efficacité d'un groupe de drones de combat, et, d'autre part, de faire le lien entre les niveaux de planification de missions et les niveaux fonctionnels de contrôle de la formation. Le vol en formation est particulièrement bien adapté pour des applications militaires en milieux hostiles, qui requièrent des synchronisations pour l'arrivée sur les cibles ou du support mutuel pour le brouillage. L'une des difficultés soulevées est le choix autonome de la ...

This thesis presents the study and the implementation of a system that manages autonomously the configuration of a formation of unmanned aerial vehicles, or UAVs. The purposes are to improve the safety and the efficiency of a group of military UAVs, and to fill the gap between mission planning layers and formation control layers. Formation flight is particularly suited for military applications in hostile environments, that require synchronizations on target arrivals or mutual support for jamming. One of the difficulties raised is the autonomous choice of the configuration. Our approach is to develop an intermediate layer, dedicated to the formation and to the management of its configuration, between the deliberative and functionnal layers. Once a configuration is specified, it has to be allocated to the UAVs according to the tactical constraints and the available ressources. As the safety of the flight is a prime issue, reconfiguration maneuvers are planned to switch between two configurations, with respect to a security distance. Solutions have been developed based on the Branch & Bound algorithm to solve the assigment problems, and on the A* algorithm for reconfiguration trajectories planning. Moreover, a formation control has been implemented, allowing to validate our approach, both with simulations and real experimentations. ; L'objet de cette thèse est l'étude et la mise en oeuvre d'un système de gestion automatique de la configuration d'une formation d'avions sans pilote, ou drones. Les objectifs sont, d'une part, d'améliorer la sécurité et l'efficacité d'un groupe de drones de combat, et, d'autre part, de faire le lien entre les niveaux de planification de missions et les niveaux fonctionnels de contrôle de la formation. Le vol en formation est particulièrement bien adapté pour des applications militaires en milieux hostiles, qui requièrent des synchronisations pour l'arrivée sur les cibles ou du support mutuel pour le brouillage. L'une des difficultés soulevées est le choix autonome de la ...

This thesis presents the study and the implementation of a system that manages autonomously the configuration of a formation of unmanned aerial vehicles, or UAVs. The purposes are to improve the safety and the efficiency of a group of military UAVs, and to fill the gap between mission planning layers and formation control layers. Formation flight is particularly suited for military applications in hostile environments, that require synchronizations on target arrivals or mutual support for jamming. One of the difficulties raised is the autonomous choice of the configuration. Our approach is to develop an intermediate layer, dedicated to the formation and to the management of its configuration, between the deliberative and functionnal layers. Once a configuration is specified, it has to be allocated to the UAVs according to the tactical constraints and the available ressources. As the safety of the flight is a prime issue, reconfiguration maneuvers are planned to switch between two configurations, with respect to a security distance. Solutions have been developed based on the Branch & Bound algorithm to solve the assigment problems, and on the A* algorithm for reconfiguration trajectories planning. Moreover, a formation control has been implemented, allowing to validate our approach, both with simulations and real experimentations. ; L'objet de cette thèse est l'étude et la mise en oeuvre d'un système de gestion automatique de la configuration d'une formation d'avions sans pilote, ou drones. Les objectifs sont, d'une part, d'améliorer la sécurité et l'efficacité d'un groupe de drones de combat, et, d'autre part, de faire le lien entre les niveaux de planification de missions et les niveaux fonctionnels de contrôle de la formation. Le vol en formation est particulièrement bien adapté pour des applications militaires en milieux hostiles, qui requièrent des synchronisations pour l'arrivée sur les cibles ou du support mutuel pour le brouillage. L'une des difficultés soulevées est le choix autonome de la ...

International audience ; In military missions in hostile environments involving teams of UAVs flying in formation, it is important to get the maximum benefits of the auto-protection systems of each aircraft to enhance the global security and efficiency of the team. One way to achieve this is to select a proper configuration for the formation. In this paper, we present an approach to autonomously adapt the configuration of a formation and we focus on its evaluation within a realistic framework where each UAV is simulated independently and communicate through a network.

International audience ; In military missions in hostile environments involving teams of UAVs flying in formation, it is important to get the maximum benefits of the auto-protection systems of each aircraft to enhance the global security and efficiency of the team. One way to achieve this is to select a proper configuration for the formation. In this paper, we present an approach to autonomously adapt the configuration of a formation and we focus on its evaluation within a realistic framework where each UAV is simulated independently and communicate through a network.

International audience ; In military missions in hostile environments involving teams of UAVs flying in formation, it is important to get the maximum benefits of the auto-protection systems of each aircraft to enhance the global security and efficiency of the team. One way to achieve this is to select a proper configuration for the formation. In this paper, we present an approach to autonomously adapt the configuration of a formation and we focus on its evaluation within a realistic framework where each UAV is simulated independently and communicate through a network.