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Deep Reinforcement Learning for Indoor Mobile Robot Path Planning
This paper proposes a novel incremental training mode to address the problem of Deep Reinforcement Learning (DRL) based path planning for a mobile robot. Firstly, we evaluate the related graphic search algorithms and Reinforcement Learning (RL) algorithms in a lightweight 2D environment. Then, we de...
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| Publicado no: | Sensors (Basel) |
|---|---|
| Main Authors: | , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
MDPI
2020
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7582363/ https://ncbi.nlm.nih.gov/pubmed/32992750 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/s20195493 |
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