Autonomous Navigation of UAVs in Large-Scale Complex Environments: A Deep Reinforcement Learning Approach

• Published in: IEEE transactions on vehicular technology Vol. 68; no. 3; pp. 2124 - 2136
• Main Authors: Wang, Chao, Wang, Jian, Shen, Yuan, Zhang, Xudong
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.03.2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Aerospace electronics; Algorithms; Autonomous navigation; deep reinforcement learning; Markov analysis; Markov processes; Navigation; partially observable Markov decision process; Path planning; Reinforcement learning; Sensors; Simultaneous localization and mapping; Task complexity; Unmanned aerial vehicles; Virtual environments

In this paper, we propose a deep reinforcement learning (DRL)-based method that allows unmanned aerial vehicles (UAVs) to execute navigation tasks in large-scale complex environments. This technique is important for many applications such as goods delivery and remote surveillance. The problem is for...