Training methods of a non-linear fuzzy logic controller for an underwater autonomous crawler

Training methods of a non-linear fuzzy logic controller for an underwater autonomous crawler

A non-linear, fuzzy logic controller was developed for an autonomous underwater crawler. Due to fuzzy rules based on linguistic variables, the controller is applicable to many autonomous applications. The controller is hierarchical in design with an obstacle avoidance, a path finding, and a supervis...

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Bibliographic Details
Published in:2005 IEEE International Conference on Systems, Man and Cybernetics Vol. 4; pp. 3130 - 3136 Vol. 4
Main Authors: Welling, D.M., Edwards, D.B.
Format: Conference Proceeding
Language:English
Published: IEEE 2005
Subjects:
ALWSE
Autonomous
Crawler
Crawlers
Fuzzy logic
Hierarchical
Humans
Mechanical engineering
Mechanical variables control
Mobile robots
Non-Linear
Optimization
Optimization methods
Remotely operated vehicles
Simplex
Sonar navigation
Underwater vehicles
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Summary:A non-linear, fuzzy logic controller was developed for an autonomous underwater crawler. Due to fuzzy rules based on linguistic variables, the controller is applicable to many autonomous applications. The controller is hierarchical in design with an obstacle avoidance, a path finding, and a supervisor model. An optimization procedure was developed using an algorithm based on the simplex method and simulations done in an autonomous vehicle simulator. Vehicle performance was quantified using a performance function designed to penalize a vehicle for colliding with obstacles and deviating from a straight line path. Optimization was performed using two different methods to determine the optimal numeric values to the linguistic variables. Both methods resulted in enhanced vehicle performance.
ISBN:9780780392984
0780392981
ISSN:1062-922X
2577-1655
DOI:10.1109/ICSMC.2005.1571627