Supervisory fuzzy learning control for underwater target tracking

Kia, C., Arshad, M.R., Adom, A.D. and Wilson, P.A. (2005) Supervisory fuzzy learning control for underwater target tracking. In, Proceedings of Enformatika. Enformatika '05 Istanbul, Turkey, World Enformatika Society, 92-95. (Enformatika Transactions on Engineering, Computing and Technology, 6).


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This paper presents recent work on the improvement
of the robotics vision based control strategy for underwater pipeline
tracking system. The study focuses on developing image processing
algorithms and a fuzzy inference system for the analysis of the
terrain. The main goal is to implement the supervisory fuzzy learning
control technique to reduce the errors on navigation decision due to
the pipeline occlusion problem. The system developed is capable of
interpreting underwater images containing occluded pipeline, seabed
and other unwanted noise. The algorithm proposed in previous work
does not explore the cooperation between fuzzy controllers,
knowledge and learnt data to improve the outputs for underwater
pipeline tracking. Computer simulations and prototype simulations
demonstrate the effectiveness of this approach. The system accuracy
level has also been discussed.

Item Type: Book Section
ISBNs: 9759845814 (hardback)
Related URLs:
Keywords: fuzzy logic, underwater target tracking, autonomous underwater vehicles, artificial intelligence, simulations, robot navigation, vision system
Subjects: T Technology > T Technology (General)
V Naval Science > VM Naval architecture. Shipbuilding. Marine engineering
V Naval Science > V Naval Science (General)
Q Science > QA Mathematics > QA76 Computer software
Divisions : University Structure - Pre August 2011 > School of Engineering Sciences
University Structure - Pre August 2011 > School of Engineering Sciences > Fluid-Structure Interactions
ePrint ID: 23213
Accepted Date and Publication Date:
Date Deposited: 25 May 2006
Last Modified: 31 Mar 2016 11:43

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