FATES: A Framework with Adaptive Track-Explore Strategy for Moving Targets Search by a FANET

Abstract

Flying Ad-Hoc Network (FANET) is a special type of Mobile Ad-Hoc Network (MANET) which consists of multiple networked Unmanned Aerial Vehicles (UAVs). Compared to traditional target search using a single UAV, multiple cooperative UAVs within a FANET have the potential to accomplish this work more efficiently, and multi-UAV cooperative target search has attracted increasing research attention in recent years. In this paper, we conduct a comprehensive investigation on efficient multi-UAV cooperative search on moving targets. More specifically, we propose an adaptive Track-Explore adjustment strategy to dynamically assign the search task of each UAV at each time-step. Meanwhile, to improve the search performance, we introduce a novel on-line path planning method to guide the flying decision of each UAV. The proposed search framework is compared with random walk method and an ideal (not achievable) state in different scenarios, and the simulation results show that our FATES framework works efficiently on multiple moving targets search tasks with great adaptability and robustness.