Home > Published Issues > 2023 > Volume 12, No. 5, September 2023 >
IJEETC 2023 Vol.12(5): 317-325
doi: 10.18178/ijeetc.12.5.317-325

Utilizing Deep Reinforcement Learning to Control UAV Movement for Environmental Monitoring

Thu Nga Nguyen1, Trong Binh Nguyen1, Trinh Van Chien2, and Tien Hoa Nguyen1*
1. School of Electrical and Electronic Engineering, Hanoi University of Science and Technology, Vietnam
2. School of Information and Communication Technology, Hanoi University of Science and Technology, Vietnam

Manuscript received March 22, 2023; revised May 26, 2023; accepted May 30, 2023.

Abstract—Unmanned aerial vehicles (UAVs) are increasingly used in various applications, including infrastructure inspection, traffic monitoring, remote sensing, mapping, and rescue. However, many applications have required UAVs to function autonomously, without human intervention to improve system performance. In this study, we propose a new approach to environmental monitoring using a group of UAVs equipped with sensors under the support of reinforcement learning. Regarding the communication system model, we assume that UAVs can cooperate with each other to learn and share information about the environment, and then relocate to an optimal position while managing connectivity and coverage. After that, we exploit reinforcement learning with a deep deterministic policy gradient (DDPG) algorithm to optimize environmental monitoring with the proposed algorithm. Specifically, the proposed algorithm aims to simulate an environmental monitoring system using UAVs with basic parameters. We further apply the proposed algorithm to evaluate network performance under different parameter settings. Numerical results validate the effectiveness of the proposed learning-based framework in monitoring and sensing data.

Index Terms—Connectivity maintenance, coverage maximization, deep reinforcement learning, Unmanned aerial vehicles (UAVs)

Cite: Thu Nga Nguyen, Trong Binh Nguyen, Trinh Van Chien, and Tien Hoa Nguyen, "Utilizing Deep Reinforcement Learning to Control UAV Movement for Environmental Monitoring," International Journal of Electrical and Electronic Engineering & Telecommunications, Vol. 12, No. 5, pp. 317-325, September 2023. doi: 10.18178/ijeetc.12.5.317-325

Copyright © 2023 by the authors. This is an open access article distributed under the Creative Commons Attribution License (CC BY-NC-ND 4.0), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.