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Australian State/Territory : WA
Australian State/Territory : VIC
Research Topic : Intelligent Robotics
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  • Funded Activity

    Linkage Infrastructure, Equipment And Facilities - Grant ID: LE160100090

    Funder
    Australian Research Council
    Funding Amount
    $250,000.00
    Summary
    Computational infrastructure for developing deep machine learning models. Computational infrastructure for developing deep machine learning models: The computational infrastructure for developing deep machine learning models aims to enable new developments in machine learning of deep neural network models by providing the specialised computing necessary to train and evaluate the networks. In the last three years, deep networks have smashed previous performance ceilings for tasks such as object .... Computational infrastructure for developing deep machine learning models. Computational infrastructure for developing deep machine learning models: The computational infrastructure for developing deep machine learning models aims to enable new developments in machine learning of deep neural network models by providing the specialised computing necessary to train and evaluate the networks. In the last three years, deep networks have smashed previous performance ceilings for tasks such as object recognition in images, speech recognition and automatic translation, bringing the prospect of machine intelligence closer than ever. Modern machine learning techniques have had huge impact in the last decade in fields such as robotics, computer vision and data analytics. The facility would enable Australian researchers to develop, learn and apply deep networks to problems of national importance in robotic vision and big data analytics.
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    Funded Activity

    Linkage Projects - Grant ID: LP160100662

    Funder
    Australian Research Council
    Funding Amount
    $285,000.00
    Summary
    Visual intelligence for safe vehicle operation in industrial environment. Visual intelligence for safe vehicle operation in industrial environment. This project aims to develop safety devices for loosely constrained environments with public access, building on visual-based collision avoidance technology in controlled industrial settings. Increasing productivity in industrial workplaces creates a need for faster industrial vehicles. At fruit and vegetable markets and construction sites, forklift .... Visual intelligence for safe vehicle operation in industrial environment. Visual intelligence for safe vehicle operation in industrial environment. This project aims to develop safety devices for loosely constrained environments with public access, building on visual-based collision avoidance technology in controlled industrial settings. Increasing productivity in industrial workplaces creates a need for faster industrial vehicles. At fruit and vegetable markets and construction sites, forklift drivers, crane operators and crews are under pressure to move faster. The need for higher speed and the enormous human and financial cost of unsafe operations create opportunities for the deployment of intelligent safety devices. The expected outcomes of this project are safer public industrial environments, reductions in work related injuries, injury compensation costs and associated societal burdens.
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    Funded Activity

    Linkage Projects - Grant ID: LP130100521

    Funder
    Australian Research Council
    Funding Amount
    $252,000.00
    Summary
    Intelligent collision avoidance system for mobile industrial platforms. This project will develop a collision prevention system for mobile industrial platforms that enhances existing artificial vision perception systems to mimic human eye capabilities. The outcomes of this project will result in significant reductions in work related injuries, injury compensation costs and associated societal burdens.
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    Active Funded Activity

    Linkage Projects - Grant ID: LP180101109

    Funder
    Australian Research Council
    Funding Amount
    $427,000.00
    Summary
    Controlling coastlines while generating power. The Project aims to produce strategies for protecting coasts from storms using farms of wave-energy machines, which also generate electricity. Increasing lengths of coast need protection as the climate changes, but conventional barriers create permanent environmental impacts and are a sunk cost usually borne by the taxpayer. The Project expects to derive a strategy for the setting of each machine in the farm, so that they collectively absorb or refl .... Controlling coastlines while generating power. The Project aims to produce strategies for protecting coasts from storms using farms of wave-energy machines, which also generate electricity. Increasing lengths of coast need protection as the climate changes, but conventional barriers create permanent environmental impacts and are a sunk cost usually borne by the taxpayer. The Project expects to derive a strategy for the setting of each machine in the farm, so that they collectively absorb or reflect damaging waves under severe conditions. Under normal conditions, enough wave energy to sustain environmental processes would pass through. Sales of electricity would help to pay back the capital cost. Outcomes would include reduced coastal-erosion costs and a low-intermittency energy supply.
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    Active Funded Activity

    Industrial Transformation Training Centres - Grant ID: IC190100017

    Funder
    Australian Research Council
    Funding Amount
    $3,703,664.00
    Summary
    ARC Training Centre for Integrated Operations for Complex Resources. This Training Centre aims to increase value in mining through clever applications of ‘lean processing’ and train the next generation of scientists and engineers in advanced sensors and data analytics in complex resources; knowledge priorities for the mining industry. Sensor information will be linked to the resource’s in-place knowledge to enable data analytics of all embedded knowledge. Processing can then be tuned to resource .... ARC Training Centre for Integrated Operations for Complex Resources. This Training Centre aims to increase value in mining through clever applications of ‘lean processing’ and train the next generation of scientists and engineers in advanced sensors and data analytics in complex resources; knowledge priorities for the mining industry. Sensor information will be linked to the resource’s in-place knowledge to enable data analytics of all embedded knowledge. Processing can then be tuned to resource attributes, maximising value ‘on the fly’. Benefits will include increasing certainty on product quality and maximising throughput and recovery. Outcomes will include new tools to rapidly model geological and geometallurgical uncertainty with sensor inputs, to track the resource to product and enhance interpretation.
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