Multimodal swimming control of a robotic fish with pectoral fins using a CPG network |
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Authors: | Ming Wang JunZhi Yu Min Tan JianWei Zhang |
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Institution: | [1]School oflnformation and Electrical Engineering, Shandong Jianzhu University, Jinan 250101, China [2]State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China [3]Department oflnformatics, University of Hamburg, Hamburg, D-22527, Germany |
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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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Keywords: | bio-inspired control central pattern generator (CPG) neural network robotic fish swimming control |
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