Supervisory fuzzy learning control for underwater target tracking

• Main Authors: Kia, C., Arshad, M.R., Abdul Hamid, Adom, Wilson, P.A.
• Format: Working Paper
• Language: English
• Published: School of Mechatronics Engineering 2013
• Subjects: Artificial intelligence; Autonomous underwater vehicles; Fuzzy control; Fuzzy controller; Image processing; Pipelines
• Online Access: http://dspace.unimap.edu.my/xmlui/handle/123456789/30800

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 superv...