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Socio-Economic Objective : Emerging Defence Technologies
Research Topic : Copy Number Variations
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  • Funded Activity

    Discovery Early Career Researcher Award - Grant ID: DE120102388

    Funder
    Australian Research Council
    Funding Amount
    $375,000.00
    Summary
    From Bayesian filtering to smoothing and prediction for multiple object systems. This project will develop new and improved algorithms for tracking multiple targets, such as tanks, submarines or planes, using the state of the art in mathematical and computational design. These will enable more efficient and accurate technologies for defence related applications including intelligence, surveillance and reconnaissance.
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    Funded Activity

    Discovery Projects - Grant ID: DP120102343

    Funder
    Australian Research Council
    Funding Amount
    $105,000.00
    Summary
    Parameter estimation for multi-object systems. Parameter estimation in multi-object system is essential to the application of multi-object filtering to a wider range of practical problems with social and commercial benefits. This project develops the necessary parameter estimation techniques for complete 'plug-and-play' multi-object filtering solutions that facilitates widespread applications.
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    Funded Activity

    Discovery Projects - Grant ID: DP130104404

    Funder
    Australian Research Council
    Funding Amount
    $295,000.00
    Summary
    A stochastic geometric framework for Bayesian sensor array processing. This project develops a mathematical framework, and a new generation of techniques, for sensor array processing to address real-world problems with uncertainty in array parameters and number of signals. The outcomes will enhance the capability of sensors in many application areas including, radar, sonar, astronomy and wireless communications.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP200101303

    Funder
    Australian Research Council
    Funding Amount
    $360,000.00
    Summary
    Enabling the Internet of Things (IoT): structured networked control systems. Networked control systems are an emerging technology that combines control, communication and computation to deliver solutions for a range of manufacturing, safety-critical infrastructure, such as transport, defence and other Industrial Interent of Things (IIoT) applications. The current analysis and design approaches often take a ``monolithic" view of the system, which render them inadequate for addressing many importa .... Enabling the Internet of Things (IoT): structured networked control systems. Networked control systems are an emerging technology that combines control, communication and computation to deliver solutions for a range of manufacturing, safety-critical infrastructure, such as transport, defence and other Industrial Interent of Things (IIoT) applications. The current analysis and design approaches often take a ``monolithic" view of the system, which render them inadequate for addressing many important IIoT applications. This proposal will exploit specific features and structure of the plant, the communication network and the distributed computation to provide an analysis and design methodology which will deliver significant advances in control and optimised performance of IIoT with benefits to the economy and society.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP190100887

    Funder
    Australian Research Council
    Funding Amount
    $435,000.00
    Summary
    Cooperative control of networked systems with constraints. This project aims to address the challenge of networked systems in deploying teams of robotic agents. Control of the networked system is extremely difficult due to real world constraints imposed on each agent. This project will focus on motion constraints, equipment/capability constraints, and spatial constraints. In addition to theoretical advances, the wider scientific community will benefit directly, because the control algorithms dev .... Cooperative control of networked systems with constraints. This project aims to address the challenge of networked systems in deploying teams of robotic agents. Control of the networked system is extremely difficult due to real world constraints imposed on each agent. This project will focus on motion constraints, equipment/capability constraints, and spatial constraints. In addition to theoretical advances, the wider scientific community will benefit directly, because the control algorithms developed are expected to allow straightforward deployment of robotic teams. There are myriad applications for cooperative robotic agents, ranging from surveillance, to environmental monitoring using underwater and aerial drone formations – with an array of benefits and impacts including economic, commercial and societal. The results are intended to ensure and cement Australia’s front-line position in the current technological revolution known as “Industry 4.0”.
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    Funded Activity

    Discovery Projects - Grant ID: DP130103610

    Funder
    Australian Research Council
    Funding Amount
    $385,000.00
    Summary
    Information consensus and coordination of multiagent systems. Revolutions in information and communication technologies create a complex 'network of everything'. This project will develop advanced control techniques for such networks, to make the nation's power systems safer, to fly formations of unmanned airborne vehicles, and to extract key information from networks of environmental monitoring sensors.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP210102600

    Funder
    Australian Research Council
    Funding Amount
    $493,000.00
    Summary
    When stabilization and optimization meet: a codesign approach. The next generation of engineered systems need to perform complex tasks with precision, and be robust, resilient and adaptive to their environment enabled by the confluence of control, optimization, learning and computation Understanding the interplay between robust stability and optimization is key to this endeavor. Many techniques, such as model predictive control and reinforcement learning, rely on an intricate interplay between .... When stabilization and optimization meet: a codesign approach. The next generation of engineered systems need to perform complex tasks with precision, and be robust, resilient and adaptive to their environment enabled by the confluence of control, optimization, learning and computation Understanding the interplay between robust stability and optimization is key to this endeavor. Many techniques, such as model predictive control and reinforcement learning, rely on an intricate interplay between an optimization-based control algorithm and an optimization routine used to calculate the control law. This project aims to develop a general design framework for stability, suboptimality and robustness of such algorithms, that can be used in range of novel applications, such as driverless cars and drones.
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    Funded Activity

    Discovery Early Career Researcher Award - Grant ID: DE120102873

    Funder
    Australian Research Council
    Funding Amount
    $375,000.00
    Summary
    Securing networked control and estimation systems and safeguarding critical infrastructure. The purpose of this project is to reduce the likelihood of success, and the severity of impact, of a cyber-attack against networked control and estimation systems operating within critical infrastructure. The outcome will be a suite of algorithms, tools and design considerations for networked, industrial, control systems that satisfy this purpose.
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    Funded Activity

    Discovery Projects - Grant ID: DP110100538

    Funder
    Australian Research Council
    Funding Amount
    $600,000.00
    Summary
    Spatially distributed complex multiagent systems. This project will develop design methodologies for two related classes of technological systems: wireless sensor networks (in particular mobile sensor networks) and formations of mobile robotic agents. These technologies find application today in defence, and will probably become pervasive in the civilian sector.
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    Showing 1-9 of 9 Funded Activites

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