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Parameters Identification of the Flexible Fin Kinematics Model Using Vision and Genetic Algorithms Cover

Parameters Identification of the Flexible Fin Kinematics Model Using Vision and Genetic Algorithms

Open Access
|Jul 2020

Abstract

Recently a new type of autonomous underwater vehicle uses artificial fins to imitate the movements of marine animals, e.g. fish. These vehicles are biomimetic and their driving system is an undulating propulsion. There are two main methods of reproducing undulating motion. The first method uses a flexible tail fin, which is connected to a rigid hull by a movable axis. The second method is based on the synchronised operation of several mechanical joints to imitate the tail movement that can be observed among real marine animals such as fish. This paper will examine the first method of reproducing tail fin movement. The goal of the research presented in the paper is to identify the parameters of the one-piece flexible fin kinematics model. The model needs further analysis, e.g. using it with Computational Fluid Dynamics (CFD) in order to select the most suitable prototype for a Biomimetic Underwater Vehicle (BUV). The background of the work is explained in the first section of the paper and the kinematic model for the flexible fin is described in the next section. The following section is entitled Materials and Methods, and includes a description of a laboratory test of a water tunnel, a description of a Vision Algorithm (VA)which was used to determine the positions of the fin, and a Genetic Algorithm (GA) which was used to find the parameters of the kinematic fin. In the next section, the results of the research are presented and discussed. At the end of the paper, the summary including main conclusions and a schedule of the future research is inserted.

DOI: https://doi.org/10.2478/pomr-2020-0025 | Journal eISSN: 2083-7429 | Journal ISSN: 1233-2585
Language: English
Page range: 39 - 47
Published on: Jul 17, 2020
Published by: Gdansk University of Technology
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2020 Karolina Jurczyk, Paweł Piskur, Piotr Szymak, published by Gdansk University of Technology
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.