Path Planning Research of a UAV Base Station Searching for Disaster Victims’ Location Information Based on Deep Reinforcement Learning

Aiming at the path planning problem of unmanned aerial vehicle (UAV) base stations when performing search tasks, this paper proposes a Double DQN-state splitting Q network (DDQN-SSQN) algorithm that combines state splitting and optimal state to complete the optimal path planning of UAV based on the...

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Detalles Bibliográficos
Autores principales: Zhao, Jinduo, Gan, Zhigao, Liang, Jiakai, Wang, Chao, Yue, Keqiang, Li, Wenjun, Li, Yilin, Li, Ruixue
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9778616/
https://www.ncbi.nlm.nih.gov/pubmed/36554172
http://dx.doi.org/10.3390/e24121767

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9778616/
https://www.ncbi.nlm.nih.gov/pubmed/36554172
http://dx.doi.org/10.3390/e24121767

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