Decentralized Trajectory Planning for Covert Video Surveillance of a Ground-Moving Target Using Multiple UAVs

摘要

In the field of autonomous aerial robotics, aerial drones or unmanned aerial vehicles (UAVs) find extensive application in target surveillance for various purposes, owing to their advantageous attributes, such as affordability, exceptional mobility, and flexibility. This article investigates the feasibility of employing multiple UAVs for covert video surveillance of a moving target. It presents an algorithm for efficiently planning collision-free flight paths for multiple UAVs engaged in the covert monitoring of a suspicious target on the ground. Specifically, the paper introduces an online decentralized trajectory planning technique that takes into account factors such as UAV camouflage, conflicted paths avoidance, and energy efficiency. This is achieved by formulating a multi-objective optimization problem for each UAV involved, with the aim of maximizing its effectiveness in covert surveillance while minimizing energy consumption. To address this optimization challenge, the study adopts a forward dynamic programming method. The generated trajectories are designed for a predefined future time frame. To validate the effectiveness of this proposed approach, comprehensive computer simulations have been conducted.