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Supervisory fuzzy learning control for underwater target tracking

Record type: Conference or Workshop Item (Paper)

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.

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Citation

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. vol. 6, World Enformatika Society., pp. 92-95.

More information

Published date: 2005
Venue - Dates: Enformatika '05, 2005-06-24 - 2005-06-26
Keywords: fuzzy logic, underwater target tracking, autonomous underwater vehicles, artificial intelligence, simulations, robot navigation, vision system
Organisations: Fluid Structure Interactions Group

Identifiers

Local EPrints ID: 23213
URI: http://eprints.soton.ac.uk/id/eprint/23213
ISBN: 9759845814
PURE UUID: 9dd9b5ef-ffcf-4583-bd26-b67788fe13f8
ORCID for P.A. Wilson: ORCID iD orcid.org/0000-0002-6939-682X

Catalogue record

Date deposited: 25 May 2006
Last modified: 17 Jul 2017 16:18

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