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.
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
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
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.
Multi-resolution spatial query processing. The cost of spatial query processing is directly related to spatial data complexity and accuracy. While spatial data is often stored in a database with the highest level of detail available, not all applications require the same level of detail. Recognising the difficulties of multiple representations of spatial data, in this project we propose to use multi-resolution data structures as a new foundation for efficient, application-dependent, on-demand de ....Multi-resolution spatial query processing. The cost of spatial query processing is directly related to spatial data complexity and accuracy. While spatial data is often stored in a database with the highest level of detail available, not all applications require the same level of detail. Recognising the difficulties of multiple representations of spatial data, in this project we propose to use multi-resolution data structures as a new foundation for efficient, application-dependent, on-demand derivation of data at different resolution levels. The systematic approach adopted in this project has the potential to deliver performance improvement that previous algorithm-level-only research cannot match.Read moreRead less
Brain-based sensor fusion for navigating robots. This project uses new findings in neuroscience to create robots that can self-determine which of their sensors will best help them learn to navigate in an environment. This technology enables robot systems to be flexibly deployed without prior calibration for wide ranging applications in environments from office buildings to outdoor ecosystems.
Human Cues for Robot Navigation. The world has many navigational cues for the benefit of humans: sign posts, maps and the wealth of information on the internet. Yet, to date, robotic navigation has made little use of this abundant symbolic information as a resource. This project will develop a robot navigation system that can navigate using information beyond the robot's range sensors by incorporating knowledge gained by reading room labels, following human route directions or interpreting maps ....Human Cues for Robot Navigation. The world has many navigational cues for the benefit of humans: sign posts, maps and the wealth of information on the internet. Yet, to date, robotic navigation has made little use of this abundant symbolic information as a resource. This project will develop a robot navigation system that can navigate using information beyond the robot's range sensors by incorporating knowledge gained by reading room labels, following human route directions or interpreting maps found on the web. This project will demonstrate the robot's navigation ability by comparing its performance with a human as it learns to find its way around campus by asking for directions, reading signs and maps, and searching the internet for clues.Read moreRead less
Human interaction with context-aware computing systems. Context-aware systems can provide seamless support of IT applications in a variety of technologies and therefore can improve: (i) work performance and adoption of IT in many industries; and (ii) the quality of life through better support for health services, education, and everyday tasks. Currently proposed solutions for context-aware systems fail to deliver systems which are usable for non-IT professionals. The proposed project will show h ....Human interaction with context-aware computing systems. Context-aware systems can provide seamless support of IT applications in a variety of technologies and therefore can improve: (i) work performance and adoption of IT in many industries; and (ii) the quality of life through better support for health services, education, and everyday tasks. Currently proposed solutions for context-aware systems fail to deliver systems which are usable for non-IT professionals. The proposed project will show how to design context-aware systems that are usable and whose autonomic decisions can be trusted. Additional benefits include increased scientific competitiveness of Australia, strengthened collaboration with international research institutions, and high quality graduates (PhDs, Masters, Honours).Read moreRead less
Automated benthic understanding with multimodal observations. This project aims to deliver cost-effective techniques to explore and monitor marine environments. The project will develop novel methods for classification of large extent, multimodality seafloor surveys consisting of high-resolution visual 3D gigamosaics made of tens of thousands of images coregistered with broad-scale, lower resolution remote sensing data. This knowledge is essential for designing cost-effective, scalable systems t ....Automated benthic understanding with multimodal observations. This project aims to deliver cost-effective techniques to explore and monitor marine environments. The project will develop novel methods for classification of large extent, multimodality seafloor surveys consisting of high-resolution visual 3D gigamosaics made of tens of thousands of images coregistered with broad-scale, lower resolution remote sensing data. This knowledge is essential for designing cost-effective, scalable systems to explore, map and monitor Australia's marine environments. At a broader level, the approach and the techniques developed in this project have the potential to have applications in other areas such as terrestrial and intertidal ecology, extending positive impacts beyond benthic environments.Read moreRead less
An Empirically Derived Experimentally Validated Framework for Interactions in Information Environments. This project will investigate and design ways of interacting with the information infrastructure that maintain natural social interactions, take advantage of physical space and utilise our extensive human abilities to recognise and manipulate physical objects.
Expected outcomes include:
? a theoretical framework that describes the range of possible interactions that mediate information b ....An Empirically Derived Experimentally Validated Framework for Interactions in Information Environments. This project will investigate and design ways of interacting with the information infrastructure that maintain natural social interactions, take advantage of physical space and utilise our extensive human abilities to recognise and manipulate physical objects.
Expected outcomes include:
? a theoretical framework that describes the range of possible interactions that mediate information between the physical and virtual worlds.
? a prototype instrumented information environment that demonstrates and validates naturalistic information transactions identified in the framework.
This research is highly innovative in its field. It will use an iterative cycle of video observation, interaction analysis, user-centred device design, deployment and evaluation.
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