Multimodal swimming control of a robotic fish with pectoral fins using a CPG network

Ming Wang,Min Tan,Junzhi Yu,Jianwei Zhang

doi:10.1007/s11434-012-5005-6

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.

Highlights

SPECIAL TOPICS: Multimodal swimming control of a robotic fish with pectoral fins using a Central Pattern Generator (CPG) network
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
The objective of this paper is to generate and control bio-inspired multimodal swimming via a well-formulated CPG network model

Summary

Introduction

SPECIAL TOPICS: Multimodal swimming control of a robotic fish with pectoral fins using a CPG network. 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. It is confirmed that the CPG-based swimming control exhibits better dynamic invariability in preserving rhythm than the conventional body wave method. The current swimming control methods, from the perspective of cybernetics, tend to fall into two primary categories: bio-inspired and non-bio-inspired (conventional). The former is nourished by an abundance of biological knowledge of fish or other animals, while the latter relates to deriving control laws from a combined analysis of multi-body dynamics and kinematics. Inspired by the lamprey whose undulatory motions are governed by central pattern generators (CPGs), more recent studies employ CPGs to generate fishlike swimming in the context of neural-based control [11]

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