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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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Podrobná bibliografie
Vydáno v:Sensors (Basel)
Hlavní autoři: Zeng, Junjie, Ju, Rusheng, Qin, Long, Hu, Yue, Yin, Quanjun, Hu, Cong
Médium: Artigo
Jazyk:Inglês
Vydáno: MDPI 2019
Témata:
On-line přístup:https://ncbi.nlm.nih.gov/pmc/articles/PMC6767106/
https://ncbi.nlm.nih.gov/pubmed/31491927
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/s19183837
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