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Research Topic : Structural Engineering
Field of Research : Civil Engineering
Status : Declined
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  • Funded Activity

    Discovery Early Career Researcher Award - Grant ID: DE180101595

    Funder
    Australian Research Council
    Funding Amount
    $364,446.00
    Summary
    Knowledge-embedded motion planning for smart construction machinery. This project aims to develop a novel sensory feedback-based planning approach for construction machinery to optimise site execution effectiveness. The project will investigate current motion planning approaches which are feasible as planning tools but fail to be implemented at construction sites due to uncertainties of actual operations. The expected outcome will be a practical planning approach validated through field tests an .... Knowledge-embedded motion planning for smart construction machinery. This project aims to develop a novel sensory feedback-based planning approach for construction machinery to optimise site execution effectiveness. The project will investigate current motion planning approaches which are feasible as planning tools but fail to be implemented at construction sites due to uncertainties of actual operations. The expected outcome will be a practical planning approach validated through field tests and help solve feasibility problems in handling deviations between plans and on-site executions.
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