Set-membership target search and tracking within an unknown cluttered area using cooperating UAVs equipped with vision systems
<|reference_start|>Set-membership target search and tracking within an unknown cluttered area using cooperating UAVs equipped with vision systems: 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.<|reference_end|>
@article{zagar2024set-membership,
    title={Set-membership target search and tracking within an unknown cluttered
  area using cooperating UAVs equipped with vision systems},
    author={Maxime Zagar and Luc Meyer and Michel Kieffer and H'el`eene
  Piet-Lahanier},
    journal={arXiv preprint arXiv:2403.15113},
    year={2024},
    archivePrefix={arXiv},
    eprint={2403.15113},
    primaryClass={eess.SY cs.RO cs.SY}
}