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...

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Detalles Bibliográficos
Autores principales: Sun, Haoran, Fu, Tingting, Ling, Yuanhuai, He, Chaoming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
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

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8434611/
https://www.ncbi.nlm.nih.gov/pubmed/34502796
http://dx.doi.org/10.3390/s21175907

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