Discovery Early Career Researcher Award - Grant ID: DE130100885
Funder
Australian Research Council
Funding Amount
$374,723.00
Summary
Aerial robots contacting objects in dynamic environments. This project will allow small unmanned aerial vehicles to touch objects to perform tasks and to fly confidently in complex and cluttered environments where contact with surroundings is inevitable. This will enable robots to perform critical tasks such as servicing power lines, bridges and other elevated infrastructure.
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.
ARC Centre of Excellence - Vision Science. This Centre will generate important new knowledge of the performance, logic and stability of vision and visual behaviour. This knowledge will help reduce the burden of vision impairment in Australia, increasing productivity, promoting healthy ageing and reducing the community costs of visual impairment (ca. $9.85 billion in 2004). The knowledge produced will also make possible world-class innovations in robotics, leading to novel automated vision system ....ARC Centre of Excellence - Vision Science. This Centre will generate important new knowledge of the performance, logic and stability of vision and visual behaviour. This knowledge will help reduce the burden of vision impairment in Australia, increasing productivity, promoting healthy ageing and reducing the community costs of visual impairment (ca. $9.85 billion in 2004). The knowledge produced will also make possible world-class innovations in robotics, leading to novel automated vision systems with applications in industry and national security. Other knowledge will develop novel diagnostic technologies, for application in health delivery.Read moreRead less
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.
Talking with Robots: Evolving Grounded Language for Embodied Agents. The coming personal robot revolution will be built on robots that have real-world intelligence, with an ability to understand and communicate about the world in the way we humans do. This project extends a previous ARC project, which developed robot-friendly languages for naming places in the world. This new project will develop the robots' abilities and language to understand a comprehensive range of real world objects, places ....Talking with Robots: Evolving Grounded Language for Embodied Agents. The coming personal robot revolution will be built on robots that have real-world intelligence, with an ability to understand and communicate about the world in the way we humans do. This project extends a previous ARC project, which developed robot-friendly languages for naming places in the world. This new project will develop the robots' abilities and language to understand a comprehensive range of real world objects, places, actions, attributes and relationships. This project represents a major advance for Australia in the new and fast growing personal robot industry.Read moreRead less
Enhancing Intelligent Robot Navigation with the Evolution of a Robot-Friendly Language. Personal robots are set to become as popular as personal computers. The key ingredient that has been missing is intelligence - not the kind of intelligence that plays chess, but the kind that allows robots to understand the world in the way that we humans do. This project represents a major advance in that kind of intelligence, giving robots the ability to understand the world and the ability to communicate a ....Enhancing Intelligent Robot Navigation with the Evolution of a Robot-Friendly Language. Personal robots are set to become as popular as personal computers. The key ingredient that has been missing is intelligence - not the kind of intelligence that plays chess, but the kind that allows robots to understand the world in the way that we humans do. This project represents a major advance in that kind of intelligence, giving robots the ability to understand the world and the ability to communicate about their experiences. Armed with this new technology, Australia will have a competitive edge in the new and fast growing personal robot industry.Read moreRead less
Robot Navigation From Nature: Simultaneous Localisation And Mapping Based On Hippocampal Models. This project will create a new method of robot control that allows a robot to learn a map of any area and then navigate using that map. The new method is based on ideas from recent models of rodent brains.
The resulting improvements in robot navigation offer immediate benefits to the emerging service robot industry. In addition, the act of reproducing a high-level brain function in a robot will inc ....Robot Navigation From Nature: Simultaneous Localisation And Mapping Based On Hippocampal Models. This project will create a new method of robot control that allows a robot to learn a map of any area and then navigate using that map. The new method is based on ideas from recent models of rodent brains.
The resulting improvements in robot navigation offer immediate benefits to the emerging service robot industry. In addition, the act of reproducing a high-level brain function in a robot will increase the understanding of memory and learning in mammals, including humans. Consequently, the outcomes of this research will benefit both robot designers and brain researchers.
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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
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.