Multilayered learning architecture applied to humanoid locomotion.

The article presents a new learning architecture applied to humanoid stability control based on pluridisciplinary bibliographical study. The study shows that the proposed intelligent control is designed to reproduce the central nervous system (CNS) hierarchical architecture and the different areas functioning mode. Moreover, multi-level multi-layered modules have able to deal the change of gait through weighted signals.