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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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| Veröffentlicht in: | Sensors (Basel) |
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| Hauptverfasser: | , , , , , |
| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
MDPI
2019
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| Schlagworte: | |
| Online Zugang: | 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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