A hierarchical connectionist CPG controller for controlling the snake-like robot´s 3-dimensional gaits

Connectionist Central Pattern Generator models (CCPG) are helpful to understand how the CPG neural mechanism functions, and have relatively small complexity which makes them suitable for controlling snake-like robots. However, there are few CCPG models are constructed to generate the snake-like robot´s three-dimensional gaits, which are important for adapation, and their gaits generation ability is also very inadequate. According to the CPG mechanism, a hierarchical CCPG model (HCCPG) with small complexity is proposed to implement the three-dimensional gaits better. The HCCPG has a two-layers structure, namely the basic rhythmic signal generation layer and the output signal modulation layer. The HCCPG can generate three-dimensional gaits well and is extendable. Based on the HCCPG, a three-dimensional gait control method is proposed. The simulations and experiments validate this method.