Industrial Transformation Research Hubs - Grant ID: IH210100030
Funder
Australian Research Council
Funding Amount
$5,000,000.00
Summary
ARC Research Hub in Intelligent Robotic Systems for Real-Time Asset Management. This hub aims to transform the way assets and infrastructure are managed by developing new capabilities for intelligent robotic systems for inspection, monitoring, and maintenance. The hub expects to generate new knowledge in robotics and associated fields including sensing, planning, data processing, and machine learning using interdisciplinary approaches and tight collaboration between academia and industry. The ex ....ARC Research Hub in Intelligent Robotic Systems for Real-Time Asset Management. This hub aims to transform the way assets and infrastructure are managed by developing new capabilities for intelligent robotic systems for inspection, monitoring, and maintenance. The hub expects to generate new knowledge in robotics and associated fields including sensing, planning, data processing, and machine learning using interdisciplinary approaches and tight collaboration between academia and industry. The expected outcomes are robots with the ability to autonomously collect data for integration into a digital twin that provides a real-time representation of the true state of a physical asset. The benefits include both improved asset management and establishing Australia as a leading manufacturer of advanced robotic systems.Read moreRead less
Special Research Initiatives - Grant ID: SR0354908
Funder
Australian Research Council
Funding Amount
$10,000.00
Summary
The Insect-Plant Chemical Ecology Network (IPCEN). We bring together plant molecular biology, entomology and analytical chemistry to transform three leading fields of Australian research into an advanced science with far reaching capabilities in innovative research and applied outcomes. Expertise studying the biochemical pathways that produce specific plant compounds and expertise in insect recognition and response to these chemicals will be brought together. This will lead to new research outco ....The Insect-Plant Chemical Ecology Network (IPCEN). We bring together plant molecular biology, entomology and analytical chemistry to transform three leading fields of Australian research into an advanced science with far reaching capabilities in innovative research and applied outcomes. Expertise studying the biochemical pathways that produce specific plant compounds and expertise in insect recognition and response to these chemicals will be brought together. This will lead to new research outcomes and solutions to problems in agriculture, horticulture, forestry and protection of Australia's native flora. Researchers are struggling to create these links, constrained by disciplinary boundaries and geographical isolation. Key industries and researchers already support this proposal.Read moreRead less
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.Read moreRead less
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. Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE130100203
Funder
Australian Research Council
Funding Amount
$385,000.00
Summary
Autonomous benthic observing system. This project seeks to improve our ability to monitor marine habitats and characterise their variability by enhancing the Integrated Marine Observing system (IMOS) Autonomous Underwater Vehicle (AUV) Facility. The new AUV infrastructure will reduce operating costs, increase robustness of the sampling effort and insure continued operation for the next decade.