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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Detalhes bibliográficos

Principais autores:	Xianyong Jing, Fuzhong Cong, Jichuan Huang, Chunyan Tian, Zikang Su
Formato:	Artigo
Idioma:	Inglês
Publicado em:	MDPI AG 2024-12-01
coleção:	Aerospace
Assuntos:	unmanned aerial vehicle (UAV) autonomous decision-making maneuvering decision-making deep deterministic policy gradient (DDPG) node clustering (NC) reinforcement learning (RL)
Acesso em linha:	https://www.mdpi.com/2226-4310/11/12/1055
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