Finding answers to biological control methods using modulated patterns: An application to bio-inspired robotic fish

Abstract

This paper presents a bio-inspired robotic fish undulatory swimming behaviour modeling and control using modulated pattern generators (MPG). Carangiform fish locomotion pattern is closely mimicked using a LH body wave (with its parameters: Tail-beat frequency (TBF) and Caudal amplitude (CA)) modulated by rhythmic central pattern generator (CPG) signal. A Matsuoka based non-linear oscillator CPG structure is used to generate desired rhythmic pattern preserving control properties like system stability (limit cycle behaviour) and synchronization. A two level locomotion control architecture based on vertebrate fish biology is proposed. Higher level controller generates desired trajectory as encoded patterns MPGs. Synchronization of the desired trajectories at each joint with the robotic fish dynamics generates desired fishlike locomotion behavior. Lower level control scheme uses an inverse dynamics model based policy for tracking this locomotion pattern (joint positions). It is shown that MPGs can represent the shape (amplitude) and phase (frequency) patterns of high-dimensional periodic inputs using simple kinematic parameters. Proposed inverse dynamics model based tracking control strategy is found to perform in a stable operating margin..