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    Sensors Utilisation and Data Collection of Underground Mining

    Moghaddam F 2022 Public.pdf (1.981Mb)
    Access Status
    Open access
    Authors
    Moghaddam, Fatemeh
    Date
    2022
    Supervisor
    David Belton
    Petra Helmholz
    David McMeekin
    Type
    Thesis
    Award
    MPhil
    
    Metadata
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    Faculty
    Science and Engineering
    School
    School of Earth and Planetary Sciences
    URI
    http://hdl.handle.net/20.500.11937/92353
    Collection
    • Curtin Theses
    Abstract

    This study reviews IMU significance and performance for underground mine drone localisation. This research has designed a Kalman filter which extracts reliable information from raw data. Kalman filter for INS combines different measurements considering estimated errors to produce a trajectory including time, position and attitude. To evaluate the feasibility of the proposed method, a prototype has been designed and evaluated. Experimental results indicate that the designed Kalman filter estimates the internal states of a system.

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