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Le problème de planification de mission en ligne pour une patrouille de mini-drones est un problème d'optimisation fortement combinatoire. Il s'agit d'affecter l'ensemble des objectifs de la mission aux drones de la patrouille et d'ordonner leur exécution pour que la patrouille finisse l'intégralité de la mission au plus tôt. Pour faire face aux incertitudes liées à l'exécution de la mission, les solutions sont recalculées de façon réactive si nécessaire pendant la mission. Dans cet article nous présentons un système complet de planification de mission en ligne sous contraintes pour une patrouille de mini-drones. Nous proposons un modèle du problème en ligne sous forme d'un CSP qui est résolu à l'aide de la librairie de contraintes FaCiLe.

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The ENAC University is using and developing the Paparazzi UAV system, which aims to provide a free and fully autonomous autopilot for a fleet of MAV, including fixed wing and rotary wing MAVs. The Paparazzi project has now succeeded in providing a fully autonomous navigation system for multiple fixed-wing aircraft system. One of the main concerns of the project is the development of autonomous decision making algorithms and cooperative behaviour between the different MAV of a fleet to increase the level of autonomy of the system. We can distinguish 4 different levels of autonomy: the manual level, the augmented stability level with or without pilot through video, the flight plan level where the mission is described in terms of trajectories and waypoints, and the mission level where the mission is described in terms of goals. In this paper, we focus on the latter, which implies to solve the automated mission planning problem for a fleet of MAV. We first present a formal model for this problem inspired by the MAV06, EMAV2006 and MAV07 contests, then we propose two different approaches to solve it. The first one is based on dynamic programming and computes a policy which gives the action to take for each state, regardless of prior history and taking the uncertainties into account, whereas the second one is a real-time planning and replanning algorithm based on the A* algorithm.