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：本文针对利用协作无人机群在包含未知数量运动地面目标的未知感兴趣区域内进行目标搜索与跟踪的问题展开研究。每架无人机均配备嵌入式计算机视觉系统（CVS），可提供带有标记像素的观测环境图像及其深度图。当无人机识别到目标时，还能获取图像帧中对应像素的包围盒。针对像素分类、深度图构建及目标识别算法所提供的信息，本文提出相应假设，以支持其在集员方法框架下的应用。基于计算机视觉系统输出的信息，本文开发了一种集员目标位置估计器。每架无人机能够评估保证包含已识别目标位置的信息集合，以及可能包含待识别目标位置的信息集合。随后，各无人机利用这些集合实现对目标的协作搜索与跟踪。