Online learning and object recognition for AUV optical vision

Author

Yuan, Xiaohai ; Hu, Zhen ; Chen, Jianping ; Chen, Rongsheng ; Liu, Peilin

Author_Institution

China Ship Sci. Res. Center, Wuxi, China

Volume

6

fYear

1999

fDate

1999

Firstpage

857

Abstract

Optical vision is very important for an AUV (autonomous underwater vehicle) to navigate, avoid obstacles and operate autonomously. A neural network for online learning and recognition is presented in the paper. The major attribute that distinguishes this ANN from others is its analysis speed. Another very important feature is the ability to dynamically change the “knowledge base”. Additionally, the ANN can cope with missing values in the data. The ANN is applied to AUV optical vision. An experiment shows that the ANN performs very well

Keywords

feature extraction; learning (artificial intelligence); mobile robots; neural nets; object recognition; path planning; robot vision; underwater vehicles; analysis speed; autonomous underwater vehicle; knowledge base; navigation; obstacle avoidance; online learning; optical vision; Artificial neural networks; Biological neural networks; Feature extraction; Image processing; Navigation; Object recognition; Optical attenuators; Optical computing; Optical network units; Optical sensors;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man, and Cybernetics, 1999. IEEE SMC '99 Conference Proceedings. 1999 IEEE International Conference on

Conference_Location

Tokyo

ISSN

1062-922X

Print_ISBN

0-7803-5731-0

Type

conf

DOI

10.1109/ICSMC.1999.816664

Filename

816664