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Adaptive Quadruped Balance Control for Dynamic Environments Using Maximum-Entropy Reinforcement Learning
External disturbance poses the primary threat to robot balance in dynamic environments. This paper provides a learning-based control architecture for quadrupedal self-balancing, which is adaptable to multiple unpredictable scenes of external continuous disturbance. Different from conventional method...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8434611/ https://www.ncbi.nlm.nih.gov/pubmed/34502796 http://dx.doi.org/10.3390/s21175907 |