Robotics Vision-based Heuristic Reasoning for Underwater Target Tracking and Navigation

Article, Part of book or chapter of book, Preprint English OPEN
Kia, Chua ; Arshad, Mohd Rizal (2006)
  • Publisher: InTech
  • Journal: International Journal of Advanced Robotic Systems (issn: 1729-8806, eissn: 1729-8814)
  • Related identifiers: doi: 10.5772/5782
  • Subject: robot navigation | Electronics | fuzzylogic | autonomous underwater vehicles | simulation | Electronic computers. Computer science | underwater target tracking | TK7800-8360 | vision system. | QA75.5-76.95 | Computer Science - Robotics | artificial intelligence

This paper presents a robotics vision-based heuristic reasoning system for underwater target tracking and navigation. This system is introduced to improve the level of automation of underwater Remote Operated Vehicles (ROVs) operations. A prototype which combines computer vision with an underwater robotics system is successfully designed and developed to perform target tracking and intelligent navigation. This study focuses on developing image processing algorithms 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. The great achievement is the system's capability to recognize and perform target tracking of the object of interest (pipeline) in perspective view based on perceived condition. The effectiveness of this approach is demonstrated by computer and prototype simulations. This work 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.
  • References (13)
    13 references, page 1 of 2

    Arjuna Balasuriya; Ura, T, “Vision-based underwater cable detection and following using AUVs” Oceans '02 MTS/IEEE, 29-31 Oct. 2002, Vol. 3, pp. 1582-1587, 2002

    Bingham, D. , Drake, T. , Hill, A. , and Lott, R, “The Application of Autonomous Underwater Vehicle (AUV) Technology in the Oil Industry - Vision and Experiences,” FIG XXII International Congress Washington, D.C. USA, April 19-26 2002.

    Crovatot, D. , Rost, B. , Filippini, M. , Zampatot, M. and Frezza, R, “Segmentation of underwater Images for AUV navigation,” Proceedings of the 2000 IEEE international conference on control applications, 25-27 September 2000, pp. 566-569, 2000

    El-Hawary, F. and Yuyang, Jing, “A robust pre-filtering approach to EKF underwater target tracking,” Proceedings of OCEANS '93. Engineering in Harmony with Ocean, 18-21 Oct. 1993, Vol.2, pp. 235-240, 1993.

    El-Hawary, F. and Yuyang, Jing, “Robust regression-based EKF for tracking underwater targets,” IEEE Journal of Oceanic Engineering, Vol.20, Issue.1, pp.31-41, Jan. 1995.

    Evans, J.; Petillot, Y.; Redmond, P.; Wilson, M.; Lane, D, “AUTOTRACKER: AUV embedded control architecture for autonomous pipeline and cable tracking” OCEANS 2003. Proceedings, 22-26 Sept. 2003, Vol 5, pp. 2651-2658, 2003.

    Fairweather, A. J. R. , Hodgetts, M. A. and Greig, A. R, “Robust scene interpretation of underwater image sequences,” IPA97 Conference, 15-17 July 1997, Conference Publication No. 443, pp. 660-664, 1997.

    Foresti. G.L. and Gentili. S, “A vision based system for object detection in underwater images,” International journal of pattern recognition and artificial intelligence, vol. 14, no. 2, pp. 167-188, 2000

    Foresti, G. L. and Gentili, S, “A hierarchical classification system for object recognition in underwater environments” IEEE Journal of Oceanic Engineering, Vol. 27, No. 1, pp 66-78, 2002.

    Howard. A. , Tunstel. E. , Edwards. D. and Carlson. Alan, “Enhancing fuzzy robot navigation systems by mimicking human visual perception of natural terrain traversability,” Joint 9th IFSA World Congress and 20th NAFIPS International Conference, Vancouver, B.C., Canada, pp. 7-12, July 2001

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