多型的なＣＰＧ回路モデルによる２脚ロボットの実時間行動遷移

Abstract

In order to create agile locomotion for legged robots, so far various methods have been proposed with the concept of neural circuits, or so-called Central Pattern Generator (CPG) . In contrast to these approaches in which monolithic CPG neural circuits are employed to control locomotion, this paper focus on a polymorphic CPG neural circuit. This allows us to dynamically change the properties of CPG circuit according to the current situation in real-time. To this aim, the concept of neuromodulation mechanism is introduced to modulate a CPG circuit. To verify the feasibility of this approach, this concept is applied to the control of a 3-D biped robot which is intrinsically unstable. In order to explore the parameters of the CPG circuit with a neuromodulation mechanism, an evolutionary algorithm is employed in this study. Simulation results show that the neuromodulation mechanism dynamically changes synaptic weights of the CPG circuit. This synaptic change leads to creating different behaviors, such as walking behavior and stepping behavior, from the same circuit.