To date, various methods using the concept of neural circuit or so-called central pattern generators (CPGs) have been proposed to create agile locomotion for legged robots. In contrast to these approaches, in this article we propose a polymorphic neural circuit that allows the dynamic change of its properties according to the current situation in real time to be employed instead. To this end, the concept of neuromodulation is introduced. To verify the feasibility of this approach, this concept is applied to the control of a three-dimensional biped robot that is intrinsically unstable. The importance of an adaptive controller is illustrated with the simulations of biped walking on uneven terrain, and the results show that the biped robot successfully copes with environmental perturbation by dynamically changing the torque outputs applied to the joints. Furthermore, the proposed approach outperforms a monolithic CPG model with sensory feedback.
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