Autonomous Obstacle Avoidance and Target Tracking of UAV Based on Deep Reinforcement Learning

When using deep reinforcement learning algorithm to complete Unmanned Aerial Vehicle (UAV) autonomous obstacle avoidance and target tracking tasks, there are often some problems such as slow convergence speed and low success rate. Therefore, this paper proposes a new deep reinforcement learning algo...

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Veröffentlicht in:	Journal of intelligent & robotic systems Jg. 104; H. 4; S. 60
Hauptverfasser:	Xu, Guoqiang, Jiang, Weilai, Wang, Zhaolei, Wang, Yaonan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Dordrecht Springer Netherlands 01.04.2022 Springer Springer Nature B.V
Schlagworte:	Algorithms Analysis Artificial Intelligence Control Convergence Data mining Deep learning Drone aircraft Electrical Engineering Engineering label V Machine learning Mechanical Engineering Mechatronics Obstacle avoidance Pools Regular Paper Robotics Topical collection on Robotics Vision and Intelligent Control Tracking Unmanned aerial vehicles Unmanned Aerial Vehicle (UAV) Autonomous obstacle avoidance Deep reinforcement learning Target tracking Continuous control
ISSN:	0921-0296, 1573-0409
Online-Zugang:	Volltext
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