Archives Ouvertes HAL
Toutes les publications de l'ENAC en direct.
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We present a set of algorithmic solutions for a fleet of unmanned aerial vehicles evolving along in tight coordination in a constrained environment. The mission to achieve is defined by an ordered sequence of waypoints and a set of constraints to satisfy. The algorithms allow the determination of the geometric configuration of the UAVs, of the trajectories to switch from one configuration to an other, and the flight control of each individual UAV. All the algorithms are embedded within an architecture that ensures a safe and robust behavior of the formation.
A fleet of UAVs flying according a planned mission in hostile environments must optimize its configuration, so that the UAVs auto-protection systems ensure the fleet safety. Such an optimization can be done in the mission planning phase, and must also be reactively updated to tackle unpredicted threats. In this paper, we present an approach to the problem of selecting autonomously the fleet configuration. Algorithms that explicitly consider models of the threats and of the countermeasures systems are presented, and integrated within a global decisional architecture that ensures reactiveness and constraints satisfactions.
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.
This chapter depicts an architecture that aims at designing a multi-UAV framework enabling cooperative operations in a system in which some UAVs are directly controlled by an operator, others are only endowed with operational autonomy , and others have decisional autonomy capacities. The architecture provides with the possibility to configure dynamically the decisional scheme, depending on the available robots and on the operational context. A taxonomy of robots decisional autonomy is introduced, and used as a foundation to state the proposed architecture. The various functionalities on-board each robot are organized among a repartition that exhibits on-board functional...
In this communication, direction finding performances of a reconfigurable wideband vector antenna are predicted. The accurate estimation of the direction of arrivals across the 3D half-space of incoming electromagnetic fields is obtained over a 1.7:1 frequency range from only two colocated and orthogonal circular arrays of Vivaldi antennas.
Une antenne reconfigurable large-bande présentant des caractéristiques radioélectriques susceptibles de répondre aux besoins de la radiogoniométrie 3D est proposée dans cette communication. Il s'agit d'une antenne vectorielle constituée de deux réseaux semi-circulaires orthogonaux et colocalisés d'antennes Vivaldi, disposés sur support métallique. Cette antenne permet notamment de synthétiser les diagrammes de rayonnement de deux dipôles magnétiques et d'un dipôle électrique sur une bande de fréquence de 1.69 :1 (définie pour un ROS de 2.3).
This paper presents a decisional architecture and the associated algorithms for multi-UAV (Unmanned Aerial Vehicle) systems. The architecture enables different schemes of decision distribution in the system, depending on the available decision making capabilities of the UAVs and on the operational constraints related to the tasks to achieve. The paper mainly fo-cuses on the deliberative layer of the UAVs: we detail a planning scheme where a symbolic planner relies on refinement tools that exploit UAVs and environment models. Integration effort related to decisional features is highlighted, and preliminary simulation results are provided.
Arrival Manager (AMAN) operational horizon, in Europe, is foreseen to be extended up to 500 nautical miles around destination airports. In this context, arrivals need to be sequenced and scheduled a few hours before landing, when uncertainty is still significant. A computational study, based on a two-stage stochastic program, is presented and discussed to address the arrival sequencing and scheduling problem under uncertainty. This preliminary study focuses on a single Initial Approach Fix (IAF) and a single runway. Different problem characteristics, optimization parameters as well as fast solution methods for real-time implementation are analyzed in order to evaluate...
The Galileo program is implementing enhancements with respect to standard GNSS services. Some of these enhancements relate to complementing the Galileo Open Service with Navigation Message Authentication (NMA) and providing signal authentication through the Commercial Service. These new features will improve resilience of the GNSS applications and reduce the likelihood of successful attacks to GNSS users. However, these upcoming Galileo services still require a step to be completed on the user side: the definition and implementation of algorithms to successfully exploit them. In this context, the European Commission launched the Navigation Authentication through...
Field observations and focused interviews of Air Traffic Controllers have been used to generate a list of key complexity factors in Air Traffic Control. The underlying structure of the airspace was identified as relevant in many of the factors. A preliminary investigation has revealed that the structure appears to form the basis for abstractions that reduce the difficulty of maintaining Situational Awareness, particularly the projection of future traffic situations. Three examples of such abstractions were identified: standard flows, groupings, and critical points. Preliminary approaches to developing metrics including these structural considerations are discussed.