Supervisory fuzzy learning control for underwater target tracking
Supervisory fuzzy learning control for underwater target tracking
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.
fuzzy logic, underwater target tracking, autonomous underwater vehicles, artificial intelligence, simulations, robot navigation, vision system
9759845814
92-95
World Enformatika Society
Kia, C.
91e50ac6-cdb4-4bab-bc37-501a3976f350
Arshad, M.R.
0c09f2ec-5da6-4992-944d-e47da4b07bb5
Adom, A.D.
466529f6-106c-4a8d-9555-f99ff3f5b940
Wilson, P.A.
8307fa11-5d5e-47f6-9961-9d43767afa00
2005
Kia, C.
91e50ac6-cdb4-4bab-bc37-501a3976f350
Arshad, M.R.
0c09f2ec-5da6-4992-944d-e47da4b07bb5
Adom, A.D.
466529f6-106c-4a8d-9555-f99ff3f5b940
Wilson, P.A.
8307fa11-5d5e-47f6-9961-9d43767afa00
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.
.
Record type:
Conference or Workshop Item
(Paper)
Abstract
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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More information
Published date: 2005
Venue - Dates:
Enformatika '05, Istanbul, Turkey, 2005-06-23 - 2005-06-25
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
Catalogue record
Date deposited: 25 May 2006
Last modified: 09 Jan 2022 02:34
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Contributors
Author:
C. Kia
Author:
M.R. Arshad
Author:
A.D. Adom
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