A searching technique for obstacle-avoidance of autonomous underwater vehicles by using the self-tuning fuzzy controller

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

This study develops a heuristic searching technique for obstacle-avoidance of autonomous underwater vehicles (AUVs) in varying ocean environments by using the self-tuning fuzzy controller. The corresponding hydrodynamic coefficients for the AUV are obtained by the test of Planar Motion Mechanism (PMM), which serves as the important data inputs for the control system. Subsequently, the self-tuning fuzzy controller would be adopted to command the propulsion of AUVs. The function of obstacle-avoidance is based on the underwater image detection method with the BK triangle subproduct of fuzzy relations which can evaluate the safety and remoteness of the candidate routes and the successive optimal strategic routing can then be selected. In the present simulations, the current effect is used to investigate the maneuvering performance of obstacle-avoidance. Eventually, the present study indicates that the self-tuning fuzzy controller, combined with the image detection technique based on BK triangle sub-product of fuzzy relations, is verified to be a useful searching technique for obstacle-avoidance of AUVs in depth variation.

Original languageEnglish
Title of host publicationOcean Space Utilization; Professor Emeritus J. Randolph Paulling Honoring Symposium on Ocean Technology
PublisherAmerican Society of Mechanical Engineers (ASME)
ISBN (Electronic)9780791845493
DOIs
Publication statusPublished - 2014 Jan 1
EventASME 2014 33rd International Conference on Ocean, Offshore and Arctic Engineering, OMAE 2014 - San Francisco, United States
Duration: 2014 Jun 82014 Jun 13

Publication series

NameProceedings of the International Conference on Offshore Mechanics and Arctic Engineering - OMAE
Volume7

Other

OtherASME 2014 33rd International Conference on Ocean, Offshore and Arctic Engineering, OMAE 2014
CountryUnited States
CitySan Francisco
Period14-06-0814-06-13

All Science Journal Classification (ASJC) codes

  • Ocean Engineering
  • Energy Engineering and Power Technology
  • Mechanical Engineering

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