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.

翻译：本文研究了在包含先验未知数量移动地面目标的未知感兴趣区域内，利用协作无人机编队进行目标搜索与跟踪的问题。每架无人机搭载嵌入式计算机视觉系统，可提供带像素标签的环境观测区域图像及深度图。当无人机识别目标时，系统会生成图像帧中对应像素的边界框。本文提出了关于像素分类、深度图构建和目标识别算法所提供信息的若干假设，以支持集合成员方法的运用。基于计算机视觉系统提供的信息，开发了集合成员目标定位估计器。每架无人机评估两个集合：确保包含已识别目标位置的集合，以及可能包含待识别目标位置的集合。随后，各无人机利用这些集合进行协作式目标搜索与跟踪。