DocumentCode :
498339
Title :
A Fuzzy-Q Method to Improve the Adaptability of AUV in Variable Ocean Current Environment
Author :
Yang, Ge ; Zhang, Rubo ; Xu, Dong
Author_Institution :
Sch. of Comput. Sci. & Technol., Harbin Eng. Univ., Harbin, China
Volume :
3
fYear :
2009
fDate :
19-21 May 2009
Firstpage :
78
Lastpage :
82
Abstract :
It is very difficult to keep AUV following the planned routes during the AUVpsilas navigation under the strong ocean current. This article integrated Q-learning with fuzzy logic, which makes AUV can resist the influence of ocean current. A fuzzy behavior is defined to resist the ocean current by giving a extra angle towards its direction. And Q-learning is used to adjust the central point of fuzzy membership function of the resisting ocean current behavior. This behavior is complemented by two other behaviors, the moving-to-goal behavior and collision avoiding behavior. The recommendations of these three behaviors are integrated through adjustable weighting factors to generate the final motion command for the AUV. Simulation shows it improve the adaptability of AUV under different ocean current greatly.
Keywords :
collision avoidance; fuzzy logic; fuzzy set theory; learning (artificial intelligence); navigation; remotely operated vehicles; underwater vehicles; A fuzzy behavior; AUV navigation; adaptability; collision avoiding behavior; fuzzy logic; fuzzy membership function; fuzzy-Q method; integrated Q-learning; motion command; moving-to-goal behavior; ocean current behavior; ocean current environment; planned routes; Computer science; Fuzzy logic; Intelligent structures; Intelligent systems; Learning; Marine technology; Navigation; Oceans; Orbital robotics; Resists; AUV; Q-leaning; fuzzy logic; navigation; ocean current;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Systems, 2009. GCIS '09. WRI Global Congress on
Conference_Location :
Xiamen
Print_ISBN :
978-0-7695-3571-5
Type :
conf
DOI :
10.1109/GCIS.2009.62
Filename :
5209188
Link To Document :
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