Vision based heuristic reasoning for intelligent auv navigation
| dc.contributor.author | Kia, Chua | |
| dc.date.accessioned | 2015-07-30T04:40:09Z | |
| dc.date.available | 2015-07-30T04:40:09Z | |
| dc.date.issued | 2006 | |
| dc.description.abstract | This work introduces a novel path planning strategy to improve the level of automation of underwater Remote Operated Vehicles (ROVs) operations. It is originated from the desire to develop robotics vision system with the ability to mimic the human expert's judgement and reasoning when maneuvering ROV in the traverse of the underwater terrain. The study focuses on applying image processing procedure and fuzzy inference system for the analysis of the terrain. The vision system developed is capable of interpreting underwater scene by extracting subjective uncertainties of the object of interest. Subjective uncertainties are further processed as multiple inputs of a fuzzy inference system that is capable of making crisp decisions concerning where to navigate. The important part of the image analysis is morphological filtering. The applications focus on binary images with the extension of gray-level concepts. An open-loop fuzzy control system is developed for classifying the traverse of terrain. Robustness is further enhanced by the implementation of supervised fuzzy learning control technique to the system. Supervision to the fuzzy control system allows for the incorporation of additional learnt information (knowledge) into the control decision-making process. As a whole, the system is designed to perform path planning for the purpose of target (pipeline) tracking and navigation from a perspective view perceived condition. Computer simulations and prototype simulations demonstrate the effectiveness of this approach. This method is found to be very practical and have great potential usefulness for application in Autonomous Underwater Vehicle (AUV) target tracking. | en_US |
| dc.identifier.uri | http://hdl.handle.net/123456789/1013 | |
| dc.language.iso | en | en_US |
| dc.subject | Heuristic reasoning | en_US |
| dc.subject | Intelligent auv | en_US |
| dc.title | Vision based heuristic reasoning for intelligent auv navigation | en_US |
| dc.type | Thesis | en_US |
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