Cybersecurity ethics training simulations for values-based decision-making. This Project will investigate ways to train reflective ethical decision making in cybersecurity management through the design of interactive social simulations. The Project will advance understanding and management of human factors in cybersecurity breaches and the field of serious game design for cybersecurity training by using new techniques for building artificially intelligent virtual agents, drawing on interdiscipli ....Cybersecurity ethics training simulations for values-based decision-making. This Project will investigate ways to train reflective ethical decision making in cybersecurity management through the design of interactive social simulations. The Project will advance understanding and management of human factors in cybersecurity breaches and the field of serious game design for cybersecurity training by using new techniques for building artificially intelligent virtual agents, drawing on interdisciplinary expertise in ethics, artificial intelligence and serious game design. Expected outcomes of the Project include a new framework and technologies for cybersecurity training. This should provide significant benefits through deeper understanding of the ethical impact of new cybertechnologies and training solutions.Read moreRead less
Advancing Human–robot Interaction with Augmented Reality. This research aims to advance emerging human-robot interaction (HRI) methods, creating novel and innovative, human-in-the-loop communication, collaboration, and teaching methods. The project expects to support the creation of new applications for the growing wave of assistive robotic platforms emerging in the market and de-risk the integration of collaborative robotics into industrial production. Expected outcomes include methods and tool ....Advancing Human–robot Interaction with Augmented Reality. This research aims to advance emerging human-robot interaction (HRI) methods, creating novel and innovative, human-in-the-loop communication, collaboration, and teaching methods. The project expects to support the creation of new applications for the growing wave of assistive robotic platforms emerging in the market and de-risk the integration of collaborative robotics into industrial production. Expected outcomes include methods and tools developed to allow smart leveraging of the different capacities of humans and robots. This should provide significant benefits allowing manufacturers to capitalize on the high skill level of Australian workers and bring more complex high-value manufactured products to market. Read moreRead less
Real-time signal processing and distributed robotic telescope networking for co-detection of gravitational waves and their optical counterparts. An international collaboration of scientists will employ a global network of telescopes and detectors to search for ripples in space-time. The project will use novel computational tools to study exotic phenomena in the distant Universe.
Lifelong robotic navigation using visual perception. Service robots are becoming a major part of our working and personal environments, in much the same way as personal computers already have. This project will develop new methods of practical and useful robot navigation that will enable Australia's industries and services to remain internationally competitive.
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
Explanation in artificial intelligence: a human-centred approach. This project aims to produce validated methods for creating human-centred explanations of decisions made by artificial intelligence (AI). Trial deployment of AI devices has resulted in the requirement for explanations of how AI makes decisions, where developed AI systems gave insufficient consideration of how decision logic would be explained to people. This project positions 'explainable AI' within the intersection of human-compu ....Explanation in artificial intelligence: a human-centred approach. This project aims to produce validated methods for creating human-centred explanations of decisions made by artificial intelligence (AI). Trial deployment of AI devices has resulted in the requirement for explanations of how AI makes decisions, where developed AI systems gave insufficient consideration of how decision logic would be explained to people. This project positions 'explainable AI' within the intersection of human-computer interaction, computer science and cognitive psychology. The expected outcomes of this project are new methods, models and algorithms for explaining different types of AI models to people. This project should result in improved understanding and trust of decisions made by AI systems, mitigating some societal concerns about AI-based decision making.Read moreRead less
Foundations of human-agent collaboration: situation-relevant information sharing. As automated systems become more sophisticated in their capabilities, the design of effective interaction with human operators becomes more demanding. Outcomes from this project will support the development of human-automation teams that can coordinate and collaborate in fast changing task environments.
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
ARC Centre of Excellence for Robotic Vision. Robots are vital to Australia's future prosperity in the face of high relative wages, low or decreasing productivity, and impending labour shortages. However the work and workplaces of our most important industries are unstructured and changeable and current robots are challenged by their inability to quickly, safely and reliably "see" and "understand" what is around them. The Centre's research will create the fundamental science and technologies th ....ARC Centre of Excellence for Robotic Vision. Robots are vital to Australia's future prosperity in the face of high relative wages, low or decreasing productivity, and impending labour shortages. However the work and workplaces of our most important industries are unstructured and changeable and current robots are challenged by their inability to quickly, safely and reliably "see" and "understand" what is around them. The Centre's research will create the fundamental science and technologies that will allow robots to see as we do, and overcome the last barrier to the ubiquitous deployment of robots into society for the benefit of all.Read moreRead less
Brain Robot Interface for Physical Human Robot Collaboration. This project aims to discover new knowledge of cognitive conflict and develop models and algorithms that enable intuitive physical human-robot collaboration to jointly conduct laborious tasks in complex, unstructured environments. It proposes to build on responses in the human brain when a robot does not operate in a way the human expects. Conflict models and prediction method are planned using advanced machine learning algorithms. Th ....Brain Robot Interface for Physical Human Robot Collaboration. This project aims to discover new knowledge of cognitive conflict and develop models and algorithms that enable intuitive physical human-robot collaboration to jointly conduct laborious tasks in complex, unstructured environments. It proposes to build on responses in the human brain when a robot does not operate in a way the human expects. Conflict models and prediction method are planned using advanced machine learning algorithms. The model and algorithms are intended to be integrated into an innovative brain-robot interface for field testing in a real-world industrial task. Translation of the outcomes to industry is expected to produce substantial economic and societal benefits through improved productivity and safety.Read moreRead less