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Field of Research : Computer-Human Interaction
Research Topic : Intelligence
Australian State/Territory : ACT
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  • Funded Activity

    Discovery Projects - Grant ID: DP0451859

    Funder
    Australian Research Council
    Funding Amount
    $280,000.00
    Summary
    Autonomous Functions for Smart Cars. The aim of this project is to develop autonomous functions for smart cars, such as lane departure warning, driver fatigue warning, and automatic lane following. Every year 70,000 people are killed in road accidents, 95% of which can be attributed to driver error. The potential outcomes of this project therefore significant. Many of the theoretical methods required for this project have been developed by our group. However, further theoretical refinements fo .... Autonomous Functions for Smart Cars. The aim of this project is to develop autonomous functions for smart cars, such as lane departure warning, driver fatigue warning, and automatic lane following. Every year 70,000 people are killed in road accidents, 95% of which can be attributed to driver error. The potential outcomes of this project therefore significant. Many of the theoretical methods required for this project have been developed by our group. However, further theoretical refinements followed by experimental verification is necessary. For smart cars to be accepted, the systems must be demonstrated to be reliable and to operate in a wide range of conditions.
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    Funded Activity

    Linkage Projects - Grant ID: LP140100995

    Funder
    Australian Research Council
    Funding Amount
    $275,000.00
    Summary
    Computational Intelligence for Complex Structured Data. This project aims to use computational intelligence techniques to reliably learn adaptive natural human pointing and gestures to control an interface on a pseudo-3D display. Highly complex data with interconnections between elements is hard to visualise on screens. Most current tools are operated using point/click/drag on 2D screens. The physical technology to capture appropriate human behaviours exists already, but not the adaptive learnin .... Computational Intelligence for Complex Structured Data. This project aims to use computational intelligence techniques to reliably learn adaptive natural human pointing and gestures to control an interface on a pseudo-3D display. Highly complex data with interconnections between elements is hard to visualise on screens. Most current tools are operated using point/click/drag on 2D screens. The physical technology to capture appropriate human behaviours exists already, but not the adaptive learning of the syntax and semantics of individual gestures and actions, nor the multi-gesture information fusion required for understanding, which could significantly enhance efficiency, for example, in sorting through named entities in an investigation. All of this is done naturally by most human beings, using biological neural networks.
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    Funded Activity

    Linkage Projects - Grant ID: LP0347232

    Funder
    Australian Research Council
    Funding Amount
    $195,000.00
    Summary
    Robotics for the Real World: A Museum Tourguide Robot. This project will develop a tour guide robot for deployment into a real-world situation: providing tours at the Questacon museum in Canberra. Previously developed tour guide robots have all been limited in nature, similar to one-off laboratory experiments. This project aims to develop a world first: a truly robust and autonomous mobile robot that is continuously in service. This is a vital area for the future of robotics and has potential .... Robotics for the Real World: A Museum Tourguide Robot. This project will develop a tour guide robot for deployment into a real-world situation: providing tours at the Questacon museum in Canberra. Previously developed tour guide robots have all been limited in nature, similar to one-off laboratory experiments. This project aims to develop a world first: a truly robust and autonomous mobile robot that is continuously in service. This is a vital area for the future of robotics and has potential for spin-offs. The project will also develop necessary research results in the areas of mapping of dynamic environments, demonstrable safety, human-robot interaction, robot robustness and reliability, and Internet-based teleoperation.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP190102919

    Funder
    Australian Research Council
    Funding Amount
    $390,000.00
    Summary
    Adaptive modelling of human responses in complex interaction. This project aims to combine strengths of human cognition and evolutionary computing to efficiently solve problems which neither can do alone. The project will develop techniques combining advanced non-intrusive sensor measures of behaviour and emotional reaction in interaction tasks to enable high level computer support for human goal seeking, in complex data and design environments. This project will allow non-expert users to use to .... Adaptive modelling of human responses in complex interaction. This project aims to combine strengths of human cognition and evolutionary computing to efficiently solve problems which neither can do alone. The project will develop techniques combining advanced non-intrusive sensor measures of behaviour and emotional reaction in interaction tasks to enable high level computer support for human goal seeking, in complex data and design environments. This project will allow non-expert users to use tools normally requiring extensive training in settings where the user can 'see' when they get something they like but do not know how to instruct a computer system to show or do it. Applications of the project will include visualisation for bespoke manufacturing or for high dimensional data, generating abstract art, or improving teleconferencing systems.
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    Showing 1-4 of 4 Funded Activites

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