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Australian State/Territory : NSW
Field of Research : Sensory Systems
Research Topic : Intelligent Robotics
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  • Funded Activity

    ARC Centres Of Excellence - Grant ID: CE0561903

    Funder
    Australian Research Council
    Funding Amount
    $16,250,000.00
    Summary
    ARC Centre of Excellence - Vision Science. This Centre will generate important new knowledge of the performance, logic and stability of vision and visual behaviour. This knowledge will help reduce the burden of vision impairment in Australia, increasing productivity, promoting healthy ageing and reducing the community costs of visual impairment (ca. $9.85 billion in 2004). The knowledge produced will also make possible world-class innovations in robotics, leading to novel automated vision system .... ARC Centre of Excellence - Vision Science. This Centre will generate important new knowledge of the performance, logic and stability of vision and visual behaviour. This knowledge will help reduce the burden of vision impairment in Australia, increasing productivity, promoting healthy ageing and reducing the community costs of visual impairment (ca. $9.85 billion in 2004). The knowledge produced will also make possible world-class innovations in robotics, leading to novel automated vision systems with applications in industry and national security. Other knowledge will develop novel diagnostic technologies, for application in health delivery.
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    Funded Activity

    ARC Future Fellowships - Grant ID: FT130100858

    Funder
    Australian Research Council
    Funding Amount
    $668,566.00
    Summary
    Real-time friction sensing, feedback and control for dexterous prosthetic and robotic manipulation. Prosthetic and robotic hands demonstrate poor dexterity during object manipulation, often dropping objects. Humans rarely allow objects to slip because we can sense when an object is slippery and adjust our grip. Exceptionally little research has been directed at replicating this ability to sense friction. This project aims to enable artificial hands to estimate frictional properties while graspin .... Real-time friction sensing, feedback and control for dexterous prosthetic and robotic manipulation. Prosthetic and robotic hands demonstrate poor dexterity during object manipulation, often dropping objects. Humans rarely allow objects to slip because we can sense when an object is slippery and adjust our grip. Exceptionally little research has been directed at replicating this ability to sense friction. This project aims to enable artificial hands to estimate frictional properties while grasping an object. Non-invasive methods to feed back this frictional information to an amputee will also be investigated. Finally, the friction-sensing system will be used to improve robotic gripper control. The outcomes of this research will significantly advance the fields of prosthetics, telesurgery, and service and manufacturing robotics.
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    Funded Activity

    Discovery Projects - Grant ID: DP140100896

    Funder
    Australian Research Council
    Funding Amount
    $430,000.00
    Summary
    Biologically-inspired detection, pursuit and interception of moving objects by unmanned aircraft systems. Although it is well known that aggressive honeybees are very effective at detecting, pursuing and intercepting moving targets, this behaviour has never been studied quantitatively. This project will use high-speed video cinematography to investigate this behaviour, to develop visual algorithms for the detection of moving targets, and to create dynamical models of the mechanisms that control .... Biologically-inspired detection, pursuit and interception of moving objects by unmanned aircraft systems. Although it is well known that aggressive honeybees are very effective at detecting, pursuing and intercepting moving targets, this behaviour has never been studied quantitatively. This project will use high-speed video cinematography to investigate this behaviour, to develop visual algorithms for the detection of moving targets, and to create dynamical models of the mechanisms that control pursuit. The resulting algorithms will be incorporated into unmanned aerial vehicles for detecting, monitoring and tracking other objects in the sky, and their performance will be evaluated. The results will provide a better understanding of the biological basis of pursuit behaviour, as well as lead to novel technologies for aerial surveillance and safety.
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    Funded Activity

    Linkage Projects - Grant ID: LP130100483

    Funder
    Australian Research Council
    Funding Amount
    $652,374.00
    Summary
    Strategies for mid-air collision avoidance in aircraft: lessons from bird flight. Birds seldom collide with each other and other objects, despite the high speeds at which they fly in complex environments. This project will examine how birds sense and avoid impending collisions, and will use these results to design novel strategies for the detection and avoidance of aircraft mid-air collisions.
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    Showing 1-4 of 4 Funded Activites

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