Deep Reinforcement Learning Approach with Multiple Experience Pools for UAV’s Autonomous Motion Planning in Complex Unknown Environments

Autonomous motion planning (AMP) of unmanned aerial vehicles (UAVs) is aimed at enabling a UAV to safely fly to the target without human intervention. Recently, several emerging deep reinforcement learning (DRL) methods have been employed to address the AMP problem in some simplified environments, a...

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Detalles Bibliográficos
Autores principales: Hu, Zijian, Wan, Kaifang, Gao, Xiaoguang, Zhai, Yiwei, Wang, Qianglong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7180781/
https://www.ncbi.nlm.nih.gov/pubmed/32235308
http://dx.doi.org/10.3390/s20071890

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7180781/
https://www.ncbi.nlm.nih.gov/pubmed/32235308
http://dx.doi.org/10.3390/s20071890

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