Navigation in Unknown Dynamic Environments Based on Deep Reinforcement Learning

In this paper, we propose a novel Deep Reinforcement Learning (DRL) algorithm which can navigate non-holonomic robots with continuous control in an unknown dynamic environment with moving obstacles. We call the approach MK-A3C (Memory and Knowledge-based Asynchronous Advantage Actor-Critic) for shor...

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Detalles Bibliográficos
Autores principales: Zeng, Junjie, Ju, Rusheng, Qin, Long, Hu, Yue, Yin, Quanjun, Hu, Cong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6767106/
https://www.ncbi.nlm.nih.gov/pubmed/31491927
http://dx.doi.org/10.3390/s19183837

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6767106/
https://www.ncbi.nlm.nih.gov/pubmed/31491927
http://dx.doi.org/10.3390/s19183837

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