Bio-inspired neural networks with central pattern generators for learning multi-skill locomotion.

ABSTRACT: Biological neural circuits, central pattern generators (CPGs), located at the spinal cord are the underlying mechanisms that play a crucial role in generating rhythmic locomotion patterns. In this paper, we propose a novel approach that leverages the inherent rhythmicity of CPGs to enhance the locomotion capabilities of quadruped robots. Our proposed network architecture incorporates CPGs for rhythmic pattern generation and a multi-layer perceptron (MLP) network for fusing multi-dimensional sensory feedback. In particular, we also proposed a method to reformulate CPGs into a fully-differentiable, stateless network, allowing CPGs and MLP to be jointly trained using gradient-based learning. The effectiveness and performance of our approach are demonstrated through extensive experiments. Our

SUBMITTER: Yang C 

PROVIDER: S-EPMC11933333 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature