Please use this identifier to cite or link to this item: https://doi.org/10.5772/60085
Title: Brain-map based carangiform swimming behaviour modeling and control in a robotic fish underwater vehicle
Authors: Chowdhury, A.R 
Panda, S.K 
Keywords: Automobile bodies
Distributed parameter control systems
Fins (heat exchange)
Fish
Inverse problems
Kinematics
Level control
Logic circuits
Trajectories
Behavior model
Bioinspired systems
Carangiform
Des
Distributed control
Lighthill equations
Robotics
Issue Date: 2015
Citation: Chowdhury, A.R, Panda, S.K (2015). Brain-map based carangiform swimming behaviour modeling and control in a robotic fish underwater vehicle. International Journal of Advanced Robotic Systems 12 : 52. ScholarBank@NUS Repository. https://doi.org/10.5772/60085
Abstract: Fish swimming demonstrates impressive speeds and exceptional characteristics in the fluid environment. The objective of this paper is to mimic undulatory swimming behaviour and its control of a body caudal fin (BCF) carangiform fish in a robotic counterpart. Based on fish biology kinematics study, a 2-level behavior based distributed control scheme is proposed. The high-level control is modeled by robotic fish swimming behavior. It uses a Lighthill (LH) body wave to generate desired joint trajectory patterns. Generated LH body wave is influenced by intrinsic kinematic parameters Tail-beat frequency (TBF) and Caudal amplitude (CA) which can be modulated to change the trajectory pattern. Parameter information is retrieved from a fish memory (cerebellum) inspired brain map. This map stores operating region information on TBF and CA parameters obtained from yellow fin tuna kinematics study. Based on an environment based error feedback signal, robotic fish map selects the right parameter/s value showing adaptive behaviour. A finite state machine methodology has been used to model this brainkinematicmap control. The low-level control is implemented using inverse dynamics based computed torque method (CTM) with dynamic PD compensation. It tracks high-level generated and encoded patterns (trajectory) for fish-tail undulation. Three types of parameter adaptation for the two chosen parameters have been shown to successfully emulate robotic fish swimming behavior. Based on the proposed control strategy joint-position and velocity tracking results are discussed. They are found to be satisfactory with error magnitudes within permissible bounds. © 2015 The Author(s). Licensee InTech.
Source Title: International Journal of Advanced Robotic Systems
URI: https://scholarbank.nus.edu.sg/handle/10635/174637
ISSN: 1729-8806
DOI: 10.5772/60085
Appears in Collections:Elements
Staff Publications

Show full item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
10_5772_60085.pdf2.56 MBAdobe PDF

OPEN

PublishedView/Download

SCOPUSTM   
Citations

4
checked on Jan 25, 2023

Page view(s)

172
checked on Jan 26, 2023

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.