On-line structural integrity assessment of advanced composite airframe with senor network. The project addresses frontier technologies that lead to solutions to one of the critical key issues forming the Australian community - online integrity/safety assessment of structures or asset including aircraft, ships, buildings and bridges. The community benefits significantly if potential disaster due to occurrence of damage associated with those structures can be prevented - the ultimate aim of resear ....On-line structural integrity assessment of advanced composite airframe with senor network. The project addresses frontier technologies that lead to solutions to one of the critical key issues forming the Australian community - online integrity/safety assessment of structures or asset including aircraft, ships, buildings and bridges. The community benefits significantly if potential disaster due to occurrence of damage associated with those structures can be prevented - the ultimate aim of researchers for decades. It is imperative that Australian industries remain technologically ahead of international competitors. Outcomes of the project will lead to novel technologies for real-time structural health monitoring and integrity assessment, bringing significant improvement in operation safety and driving down maintenance cost.Read moreRead less
Enabling secure and competitive air cargo systems. This research will make a valuable contribution towards raising security levels in Australia. Methodologies and tools that enable rapid modelling, analysis and ongoing decision making support will enable the Australian air cargo industry to efficiently implement emerging screening technologies, whilst remaining competitive.
Improved efficiency in air cargo facilities and distribution hubs will help maintain and improve productivity and reduce ....Enabling secure and competitive air cargo systems. This research will make a valuable contribution towards raising security levels in Australia. Methodologies and tools that enable rapid modelling, analysis and ongoing decision making support will enable the Australian air cargo industry to efficiently implement emerging screening technologies, whilst remaining competitive.
Improved efficiency in air cargo facilities and distribution hubs will help maintain and improve productivity and reduce time to market, despite increased security screening and rising fuel prices placing greater cost overheads on logistics networks.
This research will have international application and create valuable high technology export for Australia.Read moreRead less
Inferring driver behaviours, intent and risk in complex traffic scenarios. This project intends to develop methods to evaluate risk during driving. The next generation of vehicles will be fitted with sophisticated perception and egocentric information. This will be combined with inter-vehicle communication enabling cooperative safety, used in conjunction with intelligent infrastructure. This technology is expected to be mandated in the United States starting from 2017. This project plans to deve ....Inferring driver behaviours, intent and risk in complex traffic scenarios. This project intends to develop methods to evaluate risk during driving. The next generation of vehicles will be fitted with sophisticated perception and egocentric information. This will be combined with inter-vehicle communication enabling cooperative safety, used in conjunction with intelligent infrastructure. This technology is expected to be mandated in the United States starting from 2017. This project plans to develop unsupervised learning algorithms to infer high-level driver behaviours, intent and contextual information to automatically evaluate levels of risk under complex driving scenarios. It plans to validate the results using naturalistic driving datasets taken in large-scale deployments around the world. This innovation may improve automotive safety and facilitate the deployment of autonomous vehicles.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE160100007
Funder
Australian Research Council
Funding Amount
$303,000.00
Summary
The Future of Urban Routing and Navigation. This project aims to develop new efficient techniques for mixed-initiative routing in large transportation networks. Current state-of-the-art techniques for real-world journey planning take user requirements as input and generate a few proposed journeys as output. However, the most useful decision-support systems are mixed-initiative: the Information Technology (IT) system and user work together to find the best decisions. In the context of journey pla ....The Future of Urban Routing and Navigation. This project aims to develop new efficient techniques for mixed-initiative routing in large transportation networks. Current state-of-the-art techniques for real-world journey planning take user requirements as input and generate a few proposed journeys as output. However, the most useful decision-support systems are mixed-initiative: the Information Technology (IT) system and user work together to find the best decisions. In the context of journey planning, interaction with the user is needed to find the best combination of private, public and active transportation; understand trade-offs between cost, starting time, journey time, convenience and reliability; and react to delays and disruptions. This project aims to develop dynamic decision-support systems that will help travellers reach their destinations cheaper, faster and more conveniently.Read moreRead less
Learning from Uncertain and Missing Labelling in Relational Data. Perceptual models for unstructured environments require complex modelling, usually specified in an ad-hoc manner. This project will substantially increase the range of robotic applications by learning more complex spatial statistical models for perception in challenging environments. Robots will be able to improve their perception capabilities with minimal human supervision.
Mining is one of the major components of the Australian ....Learning from Uncertain and Missing Labelling in Relational Data. Perceptual models for unstructured environments require complex modelling, usually specified in an ad-hoc manner. This project will substantially increase the range of robotic applications by learning more complex spatial statistical models for perception in challenging environments. Robots will be able to improve their perception capabilities with minimal human supervision.
Mining is one of the major components of the Australian economy. This project will improve mining automation and contribute to a more efficient industry, capable to compete internationally in the new globalisation context. Efficient extraction will also reduce the human impact and will be a significant factor for an environmentally sustainable development. Read moreRead less
Behaviour Bootstrapping for Ad Hoc, Heterogeneous Robot Swarms. This project aims to develop algorithms to permit groups of robots to evolve coordinated, collective, swarm behaviours. Groups of robots will be conceptualised as developmental swarm organisms with an initially limited set of behaviours, but equipped with structures and processes to permit them to evolve new behaviours. This project expects to deliver the next generation of computational intelligence technologies to enable humans to ....Behaviour Bootstrapping for Ad Hoc, Heterogeneous Robot Swarms. This project aims to develop algorithms to permit groups of robots to evolve coordinated, collective, swarm behaviours. Groups of robots will be conceptualised as developmental swarm organisms with an initially limited set of behaviours, but equipped with structures and processes to permit them to evolve new behaviours. This project expects to deliver the next generation of computational intelligence technologies to enable humans to harness large groups of robots for new kinds of transport and inspection tasks in smart cities, smart farming and defence. The expected outcomes of the project include new software frameworks for distributed developmental learning, extending developmental robotics to evolutionary robot swarms. Read moreRead less
Genetic Algorithms for Open-Cut Mine Scheduling. Open-cut mining depends heavily on long-term scheduling. This project will apply a novel artificial intelligence method, genetic algorithms, to mine scheduling. The aim is to create an improved scheduler as a drop-in replacement for today's methods, which generally assume perfect knowledge of the ore body and future prices and costs. This project will optimize schedules that cope with uncertainties, by searching the possible scenarios to automa ....Genetic Algorithms for Open-Cut Mine Scheduling. Open-cut mining depends heavily on long-term scheduling. This project will apply a novel artificial intelligence method, genetic algorithms, to mine scheduling. The aim is to create an improved scheduler as a drop-in replacement for today's methods, which generally assume perfect knowledge of the ore body and future prices and costs. This project will optimize schedules that cope with uncertainties, by searching the possible scenarios to automatically find the best options for different future contingencies. This will produce flexible schedules, to maintain mine viability and job security despite unpredictable economic fluctuations. About 40% of Australia's exports come from mining, so this proposal will benefit the nation's economy, and make secure mining jobs in rural and regional areas.Read moreRead less
Defense against adversarial attacks on deep learning in computer vision. Computer vision applications rely heavily on deep learning, which is highly vulnerable to being fooled by adding subtle perturbations to object/image textures that are imperceptible to humans. This project aims to develop defense mechanisms to detect and remove adversarial patterns from the input images. The project expects to advance knowledge in understanding the vulnerabilities of deep learning, and to design deep learni ....Defense against adversarial attacks on deep learning in computer vision. Computer vision applications rely heavily on deep learning, which is highly vulnerable to being fooled by adding subtle perturbations to object/image textures that are imperceptible to humans. This project aims to develop defense mechanisms to detect and remove adversarial patterns from the input images. The project expects to advance knowledge in understanding the vulnerabilities of deep learning, and to design deep learning architectures that are inherently robust. The outcomes of this project will increase the security and reliability of computer vision by detecting, reporting and nullifying such attacks and will benefit the general public and industry on many fronts.Read moreRead less
Evolutionary Design for Ore Processing Plants. This project will investigate the use of evolutionary algorithms (EAs) in the design of ore processing plants. Ore processing is a major activity in the Australian mining industry, and a significant source of export dollars. Prior work has demonstrated that EAs can out-perform previous manual and automated design techniques for individual processing units. This project will apply EAs to the design of whole flowsheets containing arbitrary combination ....Evolutionary Design for Ore Processing Plants. This project will investigate the use of evolutionary algorithms (EAs) in the design of ore processing plants. Ore processing is a major activity in the Australian mining industry, and a significant source of export dollars. Prior work has demonstrated that EAs can out-perform previous manual and automated design techniques for individual processing units. This project will apply EAs to the design of whole flowsheets containing arbitrary combinations of different types of units. The complexity of typical flowsheet layouts will require new algorithms to discover improved designs in practical time, so parallel hardware, and new parallel EAs, will be utilised.
Read moreRead less
Temporal and spatial Bayesian network modelling for improved fog forecasting. This project aims to improve the accuracy of fog forecasting by explicitly modelling the spatial and temporal uncertainties surrounding fog formation. It is expected weather forecast services will adopt our approach to improve their predictions of fog, which will in turn help transport companies save costs, cut emissions and improve safety.