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
Using data mining methods to remove uncertainties in sensor data streams. This project will develop key techniques for removing uncertainties in sensor data streams and thus improve the monitoring quality of sensor networks. The expected outcomes will benefit Australia by enabling improved, lower-cost monitoring of natural resources and management of stock raising.
A data science framework for modelling disease patterns from medical images. A data science framework for modelling disease patterns from medical images. This project aims to extract models of disease patterns from medical imaging data, using deep learning, smart image processing, machine learning, and statistical modelling to quantify and model patterns conventional methods cannot detect. These disease models are expected to improve understanding of particular diseases and enable precision medi ....A data science framework for modelling disease patterns from medical images. A data science framework for modelling disease patterns from medical images. This project aims to extract models of disease patterns from medical imaging data, using deep learning, smart image processing, machine learning, and statistical modelling to quantify and model patterns conventional methods cannot detect. These disease models are expected to improve understanding of particular diseases and enable precision medicine, which recognises that there are important differences between individuals with a particular disease, and that when patients are separated into sub-populations with similar disease patterns, treatment can be tailored to these sub-populations.Read moreRead less
Manoeuvrable burrowing robots for underground search. It is very difficult to locate items that have been buried underground or to find out their condition without digging them up. There are a number of situations involving leaking underground chemical storage tanks, and pipelines together with improperly disposed of chemical containers where chemical leaks can pose dangers to the environment and human health. This project aims to develop a robotic system that can burrow through the ground and h ....Manoeuvrable burrowing robots for underground search. It is very difficult to locate items that have been buried underground or to find out their condition without digging them up. There are a number of situations involving leaking underground chemical storage tanks, and pipelines together with improperly disposed of chemical containers where chemical leaks can pose dangers to the environment and human health. This project aims to develop a robotic system that can burrow through the ground and home in on sources of leaking chemicals. Such a system could pinpoint the sources of leaks without requiring extensive excavations.Read moreRead less
Robust Intelligence: Rational Decision-Making under Risk and Uncertainty. This project seeks to bridge the gap between theory and practice with an innovative framework for rational decision-making under risk and uncertainty. Intelligent agents exercise profound and growing impact in business and society. However, significant problems arise in intelligent agent deployment as their theoretical underpinnings do not ensure rational decision-making in complex real-world settings. The project aims to ....Robust Intelligence: Rational Decision-Making under Risk and Uncertainty. This project seeks to bridge the gap between theory and practice with an innovative framework for rational decision-making under risk and uncertainty. Intelligent agents exercise profound and growing impact in business and society. However, significant problems arise in intelligent agent deployment as their theoretical underpinnings do not ensure rational decision-making in complex real-world settings. The project aims to open the door to transformational technologies that may drive new entrepreneurial opportunities in agent-based global services.Read moreRead less
Smart Information Processing for Roadside Fire Risk Assessment Using Computational Intelligence and Pattern Recognition. This project proposes a novel approach for identifying roadside fire risks using pattern recognition and computational intelligence techniques. The video data is collected over every state road in Queensland annually, and has the potential to provide a range of value-added products for safer roads. This project aims to develop new techniques for identification of roadside obje ....Smart Information Processing for Roadside Fire Risk Assessment Using Computational Intelligence and Pattern Recognition. This project proposes a novel approach for identifying roadside fire risks using pattern recognition and computational intelligence techniques. The video data is collected over every state road in Queensland annually, and has the potential to provide a range of value-added products for safer roads. This project aims to develop new techniques for identification of roadside objects so that the data can be automatically analysed allowing the estimation of fire risk factors. The final outcome intends to be techniques for segmentation and classification of roadside objects and estimation of fire risk factors.Read moreRead less
Model Checking Knowledge and Probability in Pursuit-Evasion Games. The research will produce software enabling modellers to better understand their models in applications including planning under uncertainty, information flow security and systems fault diagnosis. The application studied in this project is military search and rescue mission planning, resulting in greater confidence in mission success. The research is also relevant to emergency response and collision avoidance. The project will ....Model Checking Knowledge and Probability in Pursuit-Evasion Games. The research will produce software enabling modellers to better understand their models in applications including planning under uncertainty, information flow security and systems fault diagnosis. The application studied in this project is military search and rescue mission planning, resulting in greater confidence in mission success. The research is also relevant to emergency response and collision avoidance. The project will support retention of Australian intellectual property with potential for future commercialisation. It will foster linkages between Australian researchers and an international defence alliance partner. Outcomes will be available to Australian Defence through existing Defence research sharing arrangements.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE130100292
Funder
Australian Research Council
Funding Amount
$285,000.00
Summary
Towards a stronger proof system for combinatorial optimisation. Combinatorial optimisation problems such as staff rostering, vehicle routing or resource allocation are central to the efficiency of many businesses and industries. This project will improve optimisation technology by using the low-level structure of the problems to find better solutions. This will save time, money and reduce environmental impact.
Dynamic Scheduling and Stochastic Control for Sensor Networks. Sensor networks are rapidly becoming important in applications from environmental monitoring, navigation to border surveillance. However, due to bandwidth constraints, even very simple networks have proven to be very complex to properly control. It is now necessary to efficiently allocate the 'limited available bandwidth' to sensors in order to share the most valuable data over the network. Therefore, this project proposes new techn ....Dynamic Scheduling and Stochastic Control for Sensor Networks. Sensor networks are rapidly becoming important in applications from environmental monitoring, navigation to border surveillance. However, due to bandwidth constraints, even very simple networks have proven to be very complex to properly control. It is now necessary to efficiently allocate the 'limited available bandwidth' to sensors in order to share the most valuable data over the network. Therefore, this project proposes new techniques using concepts of dynamic sensor scheduling and stochastic control to provide computationally feasible and near optimal solutions to the limited and varying bandwidth problem. This work will greatly enhance the operational performance of distributed sensor networks.Read moreRead less
Accurate analysis of combinatorial problems: from the particular to the general. Combinatorial problems pervade all aspects of our social, environmental and economic life, but finding good solutions to these problems can take too much computer time. This project will develop new analysis tools that are effective at reducing this time, thus allowing for better solutions to be found.