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Socio-Economic Objective : Emerging Defence Technologies
Field of Research : Biological Adaptation
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    ARC Future Fellowships - Grant ID: FT180100491

    Funder
    Australian Research Council
    Funding Amount
    $712,800.00
    Summary
    Animal camouflage patterns. This project aims to understand whether animal camouflage patterns can produce the illusion of 3D form. By using the latest techniques in 3D computer imaging, vision science and animal behaviour, this work addresses the previously untested but fundamental theory on 3D camouflage patterns. The development of theory on the ecology and evolution of animal patterning will enhance our understanding of the processes that maintain biological diversity. This research is expec .... Animal camouflage patterns. This project aims to understand whether animal camouflage patterns can produce the illusion of 3D form. By using the latest techniques in 3D computer imaging, vision science and animal behaviour, this work addresses the previously untested but fundamental theory on 3D camouflage patterns. The development of theory on the ecology and evolution of animal patterning will enhance our understanding of the processes that maintain biological diversity. This research is expected to have broad impact across multiple disciplines and will inform novel military defence strategies and contribute to emerging bio-inspired technologies.
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    Funded Activity

    Discovery Projects - Grant ID: DP180100220

    Funder
    Australian Research Council
    Funding Amount
    $306,832.00
    Summary
    Understanding evolution in natural systems using robotic models. This project aims to build biologically-inspired robotic and computational systems, and then modify these in ways which are either not possible, or have not yet occurred in natural systems. A comparison of these two systems will then allow a quantitative understanding of how well optimised biological structures are and where the limitations to optimisation lie. Expected outcomes include advancing the understanding of evolutionary p .... Understanding evolution in natural systems using robotic models. This project aims to build biologically-inspired robotic and computational systems, and then modify these in ways which are either not possible, or have not yet occurred in natural systems. A comparison of these two systems will then allow a quantitative understanding of how well optimised biological structures are and where the limitations to optimisation lie. Expected outcomes include advancing the understanding of evolutionary processes, and will provide significant benefits, such as aiding the manufacture of efficient autonomous robots.
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