Discovery Early Career Researcher Award - Grant ID: DE210100858
Funder
Australian Research Council
Funding Amount
$344,896.00
Summary
Human-Centred Robot Training. This project aims to address the challenge of effectively enabling novice users to train robots on complex tasks using instructional methods and gamification. With the recent advances of AI research, robots have now better cognitive and functional skills, research in robot training also now allows them to learn interactively from human. Since these robots are expected to provide assistance in different domains including education and healthcare, it is crucial to eff ....Human-Centred Robot Training. This project aims to address the challenge of effectively enabling novice users to train robots on complex tasks using instructional methods and gamification. With the recent advances of AI research, robots have now better cognitive and functional skills, research in robot training also now allows them to learn interactively from human. Since these robots are expected to provide assistance in different domains including education and healthcare, it is crucial to effectively engage human in robot’s instruction. Expected outcomes include new methods for trainers to assess robot learning, and to improve their engagement and feedback. This should provide significant human-robot interaction benefits for accessibility of learning robots.Read moreRead less
Self-organised communication as a foundation of large, complex societies. This Project aims to investigate how evolution has shaped the self-organisation of robust communication networks that emerge in large animal collectives from the actions of individuals following only simple, local rules. It expects to generate new knowledge into the fundamental principles guiding the self-organisation of networks that can sustain a complex society. Empirical work with ant colonies will inform the construct ....Self-organised communication as a foundation of large, complex societies. This Project aims to investigate how evolution has shaped the self-organisation of robust communication networks that emerge in large animal collectives from the actions of individuals following only simple, local rules. It expects to generate new knowledge into the fundamental principles guiding the self-organisation of networks that can sustain a complex society. Empirical work with ant colonies will inform the construction of simulation models to push the investigation beyond experimental limits. The Project should significantly advance our understanding of how communication networks enable the development of large societies, and thus of how to better manage autonomous man-made networks, most importantly the Internet-of-Things.Read moreRead less
Integrated Planning for Uncertainty-Centric Pilot Assistance Systems. This project aims to deliver a novel pilot assistance system to improve the viability, speed and safety of Helicopter Emergency Medical Services (HEMS) and Search and Rescue (SAR) missions. It will advance fundamental algorithms for probabilistic planning in partially observable scenarios to form the core technology of a pilot assistance system that accounts the various types of uncertainty faced by pilots in a typical HEMS/S ....Integrated Planning for Uncertainty-Centric Pilot Assistance Systems. This project aims to deliver a novel pilot assistance system to improve the viability, speed and safety of Helicopter Emergency Medical Services (HEMS) and Search and Rescue (SAR) missions. It will advance fundamental algorithms for probabilistic planning in partially observable scenarios to form the core technology of a pilot assistance system that accounts the various types of uncertainty faced by pilots in a typical HEMS/SAR missions. It will exploit recent advances in Partially Observable Markov Decision Processes (POMDPs) to recommend robust, safe, and pilot-aware mission and manoeuvring strategies to make HEMS/SAR operations safer for helicopter crews, and more effective for those in need of the service.Read moreRead less
Self-supervised feature learning for rapid processing of marine imagery. Fast and reliable quantitative estimates of marine environmental health are needed for scientific studies, design and management of protected areas, and regulatory compliance of industrial activity in the ocean. Australia is collecting seafloor images at increasing rates but expert annotations are not keeping up, meaning that typical machine learning approaches struggle. This project will develop self-supervised techniques ....Self-supervised feature learning for rapid processing of marine imagery. Fast and reliable quantitative estimates of marine environmental health are needed for scientific studies, design and management of protected areas, and regulatory compliance of industrial activity in the ocean. Australia is collecting seafloor images at increasing rates but expert annotations are not keeping up, meaning that typical machine learning approaches struggle. This project will develop self-supervised techniques that use large amounts of unlabeled data to enhance performance. Our design takes advantage of additional information available for marine imagery such as geolocation and remote sensing context. We will explore how these representations can guide additional sampling and improve performance in classification tasks.Read moreRead less
Muscle-based Signals for Responsive Physically-Assistive Robotics. This project aims to develop a physically assistive robot for industrial use that interprets signals from the human user’s muscles during a physical activity and responds with appropriate assistance. This is significant because the robot must accommodate the complexity of movement required in industrial settings and adapt to variabilities in muscle activation signals among users that also change in time. The expected research out ....Muscle-based Signals for Responsive Physically-Assistive Robotics. This project aims to develop a physically assistive robot for industrial use that interprets signals from the human user’s muscles during a physical activity and responds with appropriate assistance. This is significant because the robot must accommodate the complexity of movement required in industrial settings and adapt to variabilities in muscle activation signals among users that also change in time. The expected research outcome is an intuitive, assistive robot worn by the human workforce that enhances their productivity and longevity, improves working conditions, lowers production costs, and increases workforce resilience. The robot’s capabilities will be demonstrated in this project through the challenging activity of sheep shearing.Read moreRead less
Industrial Transformation Training Centres - Grant ID: IC200100001
Funder
Australian Research Council
Funding Amount
$4,879,415.00
Summary
ARC Training Centre for Collaborative Robotics in Advanced Manufacturing. The Centre aims to build the human and technical capability Australia needs to underpin our global competitiveness in advanced manufacturing. The Centre will unite manufacturing businesses, including SMEs, and universities to develop collaborative robotics applications which combine the strengths of humans and robots in shared work environments. The Centre will train researchers, engineers, technologists and manufacturing ....ARC Training Centre for Collaborative Robotics in Advanced Manufacturing. The Centre aims to build the human and technical capability Australia needs to underpin our global competitiveness in advanced manufacturing. The Centre will unite manufacturing businesses, including SMEs, and universities to develop collaborative robotics applications which combine the strengths of humans and robots in shared work environments. The Centre will train researchers, engineers, technologists and manufacturing leaders with the expertise industry needs to boost safety, quality assurance, production efficiency, and workforce readiness. The intended outcome is to support Australian manufacturers to shift toward higher-potential markets, compete globally and attract and retain a digitally-capable workforce for the future.Read moreRead less
Context-aware verification and validation framework for autonomous driving. This project aims to enhance the reliability and safety of emerging self-driving vehicles, through a framework that supports the validation and verification of autonomous driving systems. This project expects to generate new knowledge in areas of software engineering, intelligent transport, and machine learning, using a multi-disciplinary research combining expertise from various fields. Expected outcomes of this project ....Context-aware verification and validation framework for autonomous driving. This project aims to enhance the reliability and safety of emerging self-driving vehicles, through a framework that supports the validation and verification of autonomous driving systems. This project expects to generate new knowledge in areas of software engineering, intelligent transport, and machine learning, using a multi-disciplinary research combining expertise from various fields. Expected outcomes of this project are a family of new context-aware techniques to verify and validate complex behaviours in autonomous driving. This should provide significant benefits, such as safe autonomous driving systems and the improved journey experience and security for road users.Read moreRead less
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
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.Read moreRead less