The neural-based approaches inspired by biological neural mechanisms of locomotion are becoming increasingly popular in robot control.This paper investigates a systematic method to formulate a Central Pattern Generator(CPG) based control model for mul-timodal swimming of a multi-articulated robotic fish with flexible pectoral fins.A CPG network is created to yield diverse swim-ming in three dimensions by coupling a set of nonlinear neural oscillators using nearest-neighbor interactions.In particular,a sensitivity analysis of characteristic parameters and a stability proof of the CPG network are given.Through the coordinated con-trol of the joint CPG,caudal fin CPG,and pectoral fin CPG,a diversity of swimming modes are defined and successfully imple-mented.The latest results obtained demonstrate the effectiveness of the proposed method.It is also confirmed that the CPG-based swimming control exhibits better dynamic invariability in preserving rhythm than the conventional body wave method.
