International audience

This paper investigates the trajectory generation problem for a fleet of Unmanned Aerial Vehicles (UAVs) performing escort missions with respect to a convoy with a time-varying velocity. Using camera-equipped UAVs, we propose a framework allowing to adapt the UAVs altitudes to achieve a trade-off between the size of the covered surface and the image resolution by solving an optimization problem. Furthermore, we perform polynomial refinement based on the generated planar way-points to yield a minimum-jerk time-parameterized trajectory with dynamical constraints on the virtual leader to follow. The numerical simulations presented in this paper show the effectiveness of the optimization algorithm in adapting the UAVs altitudes to satisfy a compromise between the size of the covered area and its corresponding image resolution.

This paper proposes a trajectory generation strategy of quadcopter formation for area surveillance and inspection using multiple cameras. The proposed technique exploits a minimal virtual-leader based network topology to generate the executable trajectories where generating trajectories for each agent is no longer necessary. A coverage path planning algorithm is employed to generate a set of planar waypoints, which are then optimised to yield a minimum-jerk time-parametrised trajectory with dynamical constraints of the virtual leader to follow. In order to establish a formation pattern, the desired distance among the agents is then computed based on the operation mode, size of the area to cover, and the number of deployed UAVs. Numerical simulations demonstrate the effectiveness of the proposed method.