  This paper addresses the problem of target search and tracking using a fleet
of cooperating UAVs evolving in some unknown region of interest containing an a
priori unknown number of moving ground targets. Each drone is equipped with an
embedded Computer Vision System (CVS), providing an image with labeled pixels
and a depth map of the observed part of its environment. Moreover, a box
containing the corresponding pixels in the image frame is available when a UAV
identifies a target. Hypotheses regarding information provided by the pixel
classification, depth map construction, and target identification algorithms
are proposed to allow its exploitation by set-membership approaches. A
set-membership target location estimator is developed using the information
provided by the CVS. Each UAV evaluates sets guaranteed to contain the location
of the identified targets and a set possibly containing the locations of
targets still to be identified. Then, each UAV uses these sets to search and
track targets cooperatively.
