Accelerated Finite-time Learning and Control in Cyber-Physical Systems. Efficient learning and control in cyber-physical systems such as smart grids and robotic systems are very important for achieving economic and social benefits. This project aims to establish a breakthrough accelerated finite-time dynamics theory and technology to assist in delivering efficient learning and control. Expected outcomes include new distributed accelerated finite-time dynamics based learning and control algorithm ....Accelerated Finite-time Learning and Control in Cyber-Physical Systems. Efficient learning and control in cyber-physical systems such as smart grids and robotic systems are very important for achieving economic and social benefits. This project aims to establish a breakthrough accelerated finite-time dynamics theory and technology to assist in delivering efficient learning and control. Expected outcomes include new distributed accelerated finite-time dynamics based learning and control algorithms and tools for optimal operations in cyber-physical systems. This should provide significant benefits including a practical technology for industry applications in smart grids and robotic systems, and training of the next generation engineers in this technology for Australia.Read moreRead less
Industrial Transformation Research Hubs - Grant ID: IH230100013
Funder
Australian Research Council
Funding Amount
$5,000,000.00
Summary
ARC Research Hub for Future Digital Manufacturing. This Hub aims to grow and accelerate Australian digital manufacturing (DM) transformation by devising novel DM technology and commercialisation/adoption pathways. The Hub expects to transform industry by developing novel AI and IoT-powered DM technology that provides for dramatic improvement in manufacturing productivity, resilience and competitiveness. Expected outcomes include novel DM technology for digitally representing, predicting, and imp ....ARC Research Hub for Future Digital Manufacturing. This Hub aims to grow and accelerate Australian digital manufacturing (DM) transformation by devising novel DM technology and commercialisation/adoption pathways. The Hub expects to transform industry by developing novel AI and IoT-powered DM technology that provides for dramatic improvement in manufacturing productivity, resilience and competitiveness. Expected outcomes include novel DM technology for digitally representing, predicting, and improving production and its outcomes via an open platform that supports reusing industry co-created DM solutions. Through supporting advanced manufacturing priorities and Industry 4.0, the Hub should provide significant benefits by increasing Australian manufacturing productivity and resilience by 30%.Read moreRead less
Home helper robots: Understanding our future lives with human-like AI. This fellowship aims to understand and plan for the social effects of embedding ‘cute’ home helper robots into people’s everyday lives. The project is expected to generate new knowledge and resources to understand and respond to the emerging opportunities and risks associated with home helper robots, including their ability to support household tasks, and to provide child and aged care and companionship. Expected outcomes inc ....Home helper robots: Understanding our future lives with human-like AI. This fellowship aims to understand and plan for the social effects of embedding ‘cute’ home helper robots into people’s everyday lives. The project is expected to generate new knowledge and resources to understand and respond to the emerging opportunities and risks associated with home helper robots, including their ability to support household tasks, and to provide child and aged care and companionship. Expected outcomes include an improved understanding of anthropomorphised robots in everyday life and innovation in home helper robot theory and imaginaries. This should provide benefits such as informing robot design and policy to improve social outcomes, consumer protections and human-robot relationships.Read moreRead less