Robotics for zero-tillage agriculture. This project will develop small agricultural robots to increase broad-acre crop production and reduce environmental impact. These robots will have advanced navigation capability, will cooperate to cover large areas and resupply themselves, while causing less soil damage and applying herbicide more intelligently.
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.
Discovery Early Career Researcher Award - Grant ID: DE120100995
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Visual navigation for sunny summer days and stormy winter nights. This project will develop innovative techniques for camera-based navigation that recognise locations under a wide range of environmental conditions caused by day-night cycles, weather and seasonal change. These techniques will enable the widespread use of cheap and lightweight cameras in robot and personal navigation systems.
Learning Robotic Navigation and Interaction from Object-based Semantic Maps. Our project aims to develop new learning algorithms that enable robots to perform high-complexity tasks that are currently impossible. Compared to existing methods that rely on low-level sensor data, we aim to achieve this by learning from a high-level graph representation of the environment that captures semantics, affordances, and geometry. The outcome would be robots capable of using human instructions to efficiently ....Learning Robotic Navigation and Interaction from Object-based Semantic Maps. Our project aims to develop new learning algorithms that enable robots to perform high-complexity tasks that are currently impossible. Compared to existing methods that rely on low-level sensor data, we aim to achieve this by learning from a high-level graph representation of the environment that captures semantics, affordances, and geometry. The outcome would be robots capable of using human instructions to efficiently learn complex interaction and navigation behaviours that transfer to unseen environments. Our research should benefit new applications in domains of economic and societal importance that are currently too complex, unsafe, and uncertain for robot assistants, such as aged care, advanced manufacturing and domestic robotics.Read moreRead less
Australian Laureate Fellowships - Grant ID: FL210100156
Funder
Australian Research Council
Funding Amount
$2,716,041.00
Summary
Re-Evolving Nature’s Best Positioning Systems for People and Their Machines. The aim is to develop next-generation positioning capabilities that reduce Australia’s increasingly risky strategic reliance on vulnerable GPS satellites owned by other countries, and that enable transformation of Australia’s most important sectors through enhanced automation and robotics. Our approach re-evolves, re-engineers, and re-combines the best performing and best understood components of nature’s best positioni ....Re-Evolving Nature’s Best Positioning Systems for People and Their Machines. The aim is to develop next-generation positioning capabilities that reduce Australia’s increasingly risky strategic reliance on vulnerable GPS satellites owned by other countries, and that enable transformation of Australia’s most important sectors through enhanced automation and robotics. Our approach re-evolves, re-engineers, and re-combines the best performing and best understood components of nature’s best positioning systems with new technological advances in sensing and computation. The expected outcomes are high-performance positioning systems that improve the competitiveness of Australia’s leading industries and provide the positioning reliability required by the defence sector to keep Australia secure.Read moreRead less
Minimising the inappropriate and unnecessary hospital admissions of frail older people. The health system will continue to experience massive pressures in both fiscal and human resource terms. Older patients present with multiple, complex conditions and tend to be admitted because clinicians often do not have the time to explore other options. This project will develop and evaluate a unique and robust model for minimising inappropriate hospital admissions through rapid assessment of suitability ....Minimising the inappropriate and unnecessary hospital admissions of frail older people. The health system will continue to experience massive pressures in both fiscal and human resource terms. Older patients present with multiple, complex conditions and tend to be admitted because clinicians often do not have the time to explore other options. This project will develop and evaluate a unique and robust model for minimising inappropriate hospital admissions through rapid assessment of suitability for home care and complete referral information for safety and quality. Read moreRead less
Intelligent pattern recognition of water end uses enabling recommendations. This project aims to develop a hybrid machine learning method for autonomously disaggregating high- and low-resolution water flow data received from smart meters into discrete end-use events, and a customised recommender system for efficient resource demand management. Project novelty and significance relates to this coupling and autonomous disaggregation of datasets from advanced sensors, enabling more efficient utility ....Intelligent pattern recognition of water end uses enabling recommendations. This project aims to develop a hybrid machine learning method for autonomously disaggregating high- and low-resolution water flow data received from smart meters into discrete end-use events, and a customised recommender system for efficient resource demand management. Project novelty and significance relates to this coupling and autonomous disaggregation of datasets from advanced sensors, enabling more efficient utility services delivery and lower customer utility bills. Project benefits include enabling utilities to better manage and plan resources in the information age, while empowering customers with real-time water end-use data and behaviour changing consumption recommendations.Read moreRead less
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
The role of strong duality in computer vision. This project aims to undertake research in the fields of computer vision and optimization that will have a significant impact on the design of numerical algorithms for solving a wide range of problems in Computer Vision, Virtual Reality and Robotic Navigation. This project will advance understanding of a broad class of problems related to how computers interpret images. An expected outcome is the generation of novel mathematical theory and numerical ....The role of strong duality in computer vision. This project aims to undertake research in the fields of computer vision and optimization that will have a significant impact on the design of numerical algorithms for solving a wide range of problems in Computer Vision, Virtual Reality and Robotic Navigation. This project will advance understanding of a broad class of problems related to how computers interpret images. An expected outcome is the generation of novel mathematical theory and numerical algorithms capable of fundamentally changing the way problems relevant to a wide range of vision-related applications are solved. This should offer Australia a strong competitive advantage as a leader in scientific innovation in the areas of Computer Vision, Virtual Reality and Robotics and Autonomous Systems.Read moreRead less
Assuring dependability of complex adaptive multi-agent systems using time bands. As the complexity of computer-based systems rapidly increases, we need new methods for assuring their correct behaviour. This project will provide a means of relating behaviour at different timescales, enabling us to understand how the long-term behaviour of a system results from the short-term interactions between its components.