A parallel heterogeneous policy deep reinforcement learning algorithm for bipedal walking motion design

Considering the dynamics and non-linear characteristics of biped robots, gait optimization is an extremely challenging task. To tackle this issue, a parallel heterogeneous policy Deep Reinforcement Learning (DRL) algorithm for gait optimization is proposed. Firstly, the Deep Deterministic Policy Gra...

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Detalles Bibliográficos
Autores principales: Li, Chunguang, Li, Mengru, Tao, Chongben
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10442573/
https://www.ncbi.nlm.nih.gov/pubmed/37614967
http://dx.doi.org/10.3389/fnbot.2023.1205775

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10442573/
https://www.ncbi.nlm.nih.gov/pubmed/37614967
http://dx.doi.org/10.3389/fnbot.2023.1205775

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