Neural Multimodal Control for Versatile Motion Generation and Continuous Transitions of a Lower-Limb Exoskeleton

The paper proposes a neural multimodal control for versatile motion generation and continuous transitions between activities of a mobile lower-limb exoskeleton. The control method combines neural rhythmic oscillators as central pattern generators (CPGs) for basic rhythmic pattern generation and shaping networks using the radial basis function (RBF) networks to encode different demonstrated patterns e.g., sit-to-stand, climbing up the stairs, and walking on a level floor and a treadmill. Additionally, single recurrent neurons are used as low-pass filters to ensure smoothness. This approach is verified on a real exoskeleton in both static and dynamic situations. The experiment results show successful assistance with frequency adaptation to deal with different movement speeds.