Abstract
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 multimodal swimming of a multi-articulated robotic fish with flexible pectoral fins. A CPG network is created to yield diverse swimming 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 control of the joint CPG, caudal fin CPG, and pectoral fin CPG, a diversity of swimming modes are defined and successfully implemented. 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.
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Wang, M., Yu, J., Tan, M. et al. Multimodal swimming control of a robotic fish with pectoral fins using a CPG network. Chin. Sci. Bull. 57, 1209–1216 (2012). https://doi.org/10.1007/s11434-012-5005-6
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DOI: https://doi.org/10.1007/s11434-012-5005-6