Set-membership target search and tracking within an unknown cluttered area using cooperating UAVs equipped with vision systems

TL;DR

This paper presents a cooperative UAV system with embedded vision for searching and tracking multiple moving targets in unknown cluttered environments, utilizing set-membership methods for robust target localization.

Contribution

It introduces a novel set-membership approach for target localization using vision data, enabling cooperative search and tracking in unknown environments.

Findings

Effective target localization with set-membership guarantees.

Successful cooperative search and tracking demonstrated in complex environments.

Robust handling of multiple moving targets.

Abstract

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.