Modeling the kinematics of an Autonomous Underwater Vehicle for range-bearing simultaneous localization and Mapping

O. Matsebe, S. Holtzhausen, C. M. Kumile, N. S. Tlale

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

    2 Citations (Scopus)

    Abstract

    The "solution" of the Simultaneous Localisation and Mapping (SLAM) problem has been one of the notable successes of the robotics community. SLAM has been formulated and solved as a theoretical problem in a number of different forms. SLAM has also been implemented in a number of different domains from indoor robots to outdoor, underwater, and airborne systems. At a theoretical and conceptual level, SLAM can now be considered a solved problem. However, substantial issues remain in practically realizing more general SLAM solutions and notably in building and using perceptually rich maps as part of a SLAM algorithm. This paper describes the Autonomous Underwater Vehicle (AUV) kinematic and sensor models, it overviews the basic theoretical solution to the Extended Kalman Filter (EKF) SLAM problem, it also describes the way-point guidance based on Line of Sight (LOS). In this paper, it has been shown through Matlab simulation that the vehicle is able to localize its position using features that it observes in the environment and at the same time map those features. The vehicle is expected to follow a pre-defined sinusoidal path.

    Original languageEnglish
    Title of host publication15th International Conference on Mechatronics and Machine Vision in Practice, M2VIP'08
    Pages412-417
    Number of pages6
    DOIs
    Publication statusPublished - 2008
    Event15th International Conference on Mechatronics and Machine Vision in Practice, M2VIP'08 - Auckland, New Zealand
    Duration: Dec 2 2008Dec 4 2008

    Other

    Other15th International Conference on Mechatronics and Machine Vision in Practice, M2VIP'08
    CountryNew Zealand
    CityAuckland
    Period12/2/0812/4/08

    Fingerprint

    Bearings (structural)
    Autonomous underwater vehicles
    Kinematics
    Extended Kalman filters
    Robotics
    Robots

    All Science Journal Classification (ASJC) codes

    • Computer Vision and Pattern Recognition
    • Control and Systems Engineering
    • Electrical and Electronic Engineering
    • Mechanical Engineering

    Cite this

    Matsebe, O., Holtzhausen, S., Kumile, C. M., & Tlale, N. S. (2008). Modeling the kinematics of an Autonomous Underwater Vehicle for range-bearing simultaneous localization and Mapping. In 15th International Conference on Mechatronics and Machine Vision in Practice, M2VIP'08 (pp. 412-417). [4749569] https://doi.org/10.1109/MMVIP.2008.4749569
    Matsebe, O. ; Holtzhausen, S. ; Kumile, C. M. ; Tlale, N. S. / Modeling the kinematics of an Autonomous Underwater Vehicle for range-bearing simultaneous localization and Mapping. 15th International Conference on Mechatronics and Machine Vision in Practice, M2VIP'08. 2008. pp. 412-417
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    Matsebe, O, Holtzhausen, S, Kumile, CM & Tlale, NS 2008, Modeling the kinematics of an Autonomous Underwater Vehicle for range-bearing simultaneous localization and Mapping. in 15th International Conference on Mechatronics and Machine Vision in Practice, M2VIP'08., 4749569, pp. 412-417, 15th International Conference on Mechatronics and Machine Vision in Practice, M2VIP'08, Auckland, New Zealand, 12/2/08. https://doi.org/10.1109/MMVIP.2008.4749569

    Modeling the kinematics of an Autonomous Underwater Vehicle for range-bearing simultaneous localization and Mapping. / Matsebe, O.; Holtzhausen, S.; Kumile, C. M.; Tlale, N. S.

    15th International Conference on Mechatronics and Machine Vision in Practice, M2VIP'08. 2008. p. 412-417 4749569.

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

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    Matsebe O, Holtzhausen S, Kumile CM, Tlale NS. Modeling the kinematics of an Autonomous Underwater Vehicle for range-bearing simultaneous localization and Mapping. In 15th International Conference on Mechatronics and Machine Vision in Practice, M2VIP'08. 2008. p. 412-417. 4749569 https://doi.org/10.1109/MMVIP.2008.4749569