Bounded-error target localization and tracking using a fleet of UAVs

Among the various applications for fleets of UAVs, searching and tracking mobile targets remains a challenging task. In this paper, distributed set-membership estimation control scheme is presented. This relies on description uncertainty noise as bounded processes. Constraints field view, well presence false targets, are taken into account. Each UAV maintains several set estimates: one each detected identified true target, but not yet which also subset state space still to be explored. These sets updated by using information coming from its sensors received neighbors. A model predictive approach considered compute trajectories UAVs. The input minimizing measure volume estimates predicted h-step ahead then evaluated. Simulations scenarios including illustrate ability proposed efficiently search track an unknown number moving within some delimited area.