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Field of Research : Intelligent Robotics
Socio-Economic Objective : Combined operations
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  • Funded Activity

    Discovery Projects - Grant ID: DP0452416

    Funder
    Australian Research Council
    Funding Amount
    $201,000.00
    Summary
    Visual Tracking: Geometric Fitting and Filtering. One of the most elementary things that people and sighted animals do is to follow moving objects with their eyes. Movement is a cue to the importance and relevance of objects in a scene. Visually tracking objects allows the determination of important characteristics - distance to the object, shape of the object, likely behaviour of the object etc. Though systems have been built that can perform visual tracking: accuracy and reliability must be i .... Visual Tracking: Geometric Fitting and Filtering. One of the most elementary things that people and sighted animals do is to follow moving objects with their eyes. Movement is a cue to the importance and relevance of objects in a scene. Visually tracking objects allows the determination of important characteristics - distance to the object, shape of the object, likely behaviour of the object etc. Though systems have been built that can perform visual tracking: accuracy and reliability must be improved though a better understanding of the underlying processes. Applications include visual inspection (industrial automation), surveillance (civil and military), robot vision for scene understanding and navigation, multimedia production (automatic human motion capture for example), and human computer interfaces.
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    Funded Activity

    Discovery Projects - Grant ID: DP0881564

    Funder
    Australian Research Council
    Funding Amount
    $235,944.00
    Summary
    Learning from Uncertain and Missing Labelling in Relational Data. Perceptual models for unstructured environments require complex modelling, usually specified in an ad-hoc manner. This project will substantially increase the range of robotic applications by learning more complex spatial statistical models for perception in challenging environments. Robots will be able to improve their perception capabilities with minimal human supervision. Mining is one of the major components of the Australian .... Learning from Uncertain and Missing Labelling in Relational Data. Perceptual models for unstructured environments require complex modelling, usually specified in an ad-hoc manner. This project will substantially increase the range of robotic applications by learning more complex spatial statistical models for perception in challenging environments. Robots will be able to improve their perception capabilities with minimal human supervision. Mining is one of the major components of the Australian economy. This project will improve mining automation and contribute to a more efficient industry, capable to compete internationally in the new globalisation context. Efficient extraction will also reduce the human impact and will be a significant factor for an environmentally sustainable development.
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    Funded Activity

    Discovery Projects - Grant ID: DP0558468

    Funder
    Australian Research Council
    Funding Amount
    $235,000.00
    Summary
    Integrating human operators into large-scale sensor networks. Information awareness is critical in many applications of national importance: from bush fire fighting and defence to transportation and health care. These applications involve tasks in which timely delivery and fusion of heterogeneous information streams is of critical importance. They can all benefit from the use of robotic and embedded sensor networks considered in this project. Human operators, acting as users or supervisors, will .... Integrating human operators into large-scale sensor networks. Information awareness is critical in many applications of national importance: from bush fire fighting and defence to transportation and health care. These applications involve tasks in which timely delivery and fusion of heterogeneous information streams is of critical importance. They can all benefit from the use of robotic and embedded sensor networks considered in this project. Human operators, acting as users or supervisors, will remain at the centre of these systems. The technology and algorithms developed in this project will efficiently structure information exchange between humans and sensor networks. Establishing Australian leadership in this fast-evolving high-technology field will spur growth and job creation.
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    Funded Activity

    Federation Fellowships - Grant ID: FF0241328

    Funder
    Australian Research Council
    Funding Amount
    $1,417,500.00
    Summary
    Honeybee Vision and navigation, and applications to robotics. Anyone observing a honeybee find its way home effortlessly after collecting nectar would know that these insects are excellent navigators, despite their diminutive brains and relatively simple nervous systems. One aim of this proposal is to gain a better understanding of the mechanisms underling honeybee navigation. Another aim is to apply some of these findings to the development of novel, biologically inspired naviagtion systems for .... Honeybee Vision and navigation, and applications to robotics. Anyone observing a honeybee find its way home effortlessly after collecting nectar would know that these insects are excellent navigators, despite their diminutive brains and relatively simple nervous systems. One aim of this proposal is to gain a better understanding of the mechanisms underling honeybee navigation. Another aim is to apply some of these findings to the development of novel, biologically inspired naviagtion systems for aircraft. The findings should illuminate important principles of animal navigation. They should also advance Australia's technology in the area of unmanned aerial vehicles (UAVs), which will have important applications in national defence and security.
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    Showing 1-4 of 4 Funded Activites

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