Title:

OS15-2 Research on Underwater Robot Recognition

Publication: ICAROB2017
Volume: 22
Pages: 152-155
ISSN: 2188-7829
DOI: 10.5954/ICAROB.2017.OS15-2
Author(s): Binhu Song, Fengzhi Dai, Qijia Kang, Haifang Man, Hongtao Zhang, Long Li, Hongwei Jiao
Publication Date: January 19, 2017
Keywords: support vector machine, genetic algorithm, underwater robot fish, histogram of oriented gradient
Abstract: The underwater robot fish needs to keep shaking the tail fin to move, but the wave of the water is very difficult to be predicted, in which the robot fish will show different shape. This paper proposes to use of Histogram of Oriented Gradient method for image feature extraction, and then use the genetic algorithm method to optimize the parameters of the support vector machine. We use the parameters optimized for the classification training of experimental images to recognition the robot fish.
PDF File: https://alife-robotics.co.jp/members2017/icarob/data/html/data/OS_pdf/OS15/OS15-2.pdf
Copyright: © The authors.
This article is distributed under the terms of the Creative Commons Attribution License 4.0, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited.
See for details: https://creativecommons.org/licenses/by-nc/4.0/

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