Autonomous Maneuvering Decision-Making Algorithm for Unmanned Aerial Vehicles Based on Node Clustering and Deep Deterministic Policy Gradient

Decision-making for autonomous maneuvering in dynamic, uncertain, and nonlinear environments represents a challenging frontier problem. Deep deterministic policy gradient (DDPG) is an effective method to solve such problems, but it is found that complex strategies require extensive computation and t...

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Главные авторы:	Xianyong Jing, Fuzhong Cong, Jichuan Huang, Chunyan Tian, Zikang Su
Формат:	Artigo
Язык:	Inglês
Опубликовано:	MDPI AG 2024-12-01
Серии:	Aerospace
Предметы:	unmanned aerial vehicle (UAV) autonomous decision-making maneuvering decision-making deep deterministic policy gradient (DDPG) node clustering (NC) reinforcement learning (RL)
Online-ссылка:	https://www.mdpi.com/2226-4310/11/12/1055
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