Industrial Transformation Research Hubs - Grant ID: IH210100030
Funder
Australian Research Council
Funding Amount
$5,000,000.00
Summary
ARC Research Hub in Intelligent Robotic Systems for Real-Time Asset Management. This hub aims to transform the way assets and infrastructure are managed by developing new capabilities for intelligent robotic systems for inspection, monitoring, and maintenance. The hub expects to generate new knowledge in robotics and associated fields including sensing, planning, data processing, and machine learning using interdisciplinary approaches and tight collaboration between academia and industry. The ex ....ARC Research Hub in Intelligent Robotic Systems for Real-Time Asset Management. This hub aims to transform the way assets and infrastructure are managed by developing new capabilities for intelligent robotic systems for inspection, monitoring, and maintenance. The hub expects to generate new knowledge in robotics and associated fields including sensing, planning, data processing, and machine learning using interdisciplinary approaches and tight collaboration between academia and industry. The expected outcomes are robots with the ability to autonomously collect data for integration into a digital twin that provides a real-time representation of the true state of a physical asset. The benefits include both improved asset management and establishing Australia as a leading manufacturer of advanced robotic systems.Read moreRead less
Control and Optimization of Distributed Multiagent Formations. The project aims to develop a conceptual framework and algorithms for handling multi-vehicle formation control. Formations of unmanned airborne vehicles are currently used by defence forces and swarms of micro-vehicles are beginning to find increasing use in defence and for civilian emergency response, largely for surveillance purposes. Vehicles must cooperate to achieve a global formation objective, while respecting constraints on s ....Control and Optimization of Distributed Multiagent Formations. The project aims to develop a conceptual framework and algorithms for handling multi-vehicle formation control. Formations of unmanned airborne vehicles are currently used by defence forces and swarms of micro-vehicles are beginning to find increasing use in defence and for civilian emergency response, largely for surveillance purposes. Vehicles must cooperate to achieve a global formation objective, while respecting constraints on sensors, energy, and general mechanical limitations. The project aims to resolve the challenges of deciding what a single vehicle should observe, what and to where it should communicate, and how it should move in relation to what it sees. The conceptual framework developed may also be relevant in guiding future defence acquisitions and civilian applications.Read moreRead less
A networked robotic telescope array for coincident detection of transient phenomena in the optical, gravitational wave, neutrino and radio spectra. An international collaboration of scientists will employ a global network of rapid response robotic telescopes and detectors to study exotic transient phenomena in the early Universe. Potential spin-offs include the application of novel image analysis techniques for identifying and tracking dangerous space junk.
Optimal control of nonlinear delay systems: theory, algorithms, and applications. Time delays are present in many engineering systems, including robots, irrigation canals, and chemical reactors. This project aims to develop state-of-the-art techniques for controlling systems with time delays in an optimal manner.
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE120100051
Funder
Australian Research Council
Funding Amount
$150,000.00
Summary
A robotic telescope imaging system for rapid response spectroscopy of gamma ray bursts. This project will build and employ a rapid response optical spectrograph on the robotic Zadko Telescope, triggered by satellite and ground based observatories. The instruments will be used to probe the most energetic explosions in the universe and to test non-standard quantum and relativity theories using coincident multi-wavelength observations.
A geometric theory for modern optimisation problems in control and estimation. Linear-quadratic and spectral factorisation problems play a crucial role in system and control theory as well as many important application areas. The success of the project will represent a significant advancement of state-of-the-art in these broad areas.
Distributionally robust dynamic optimisation for nonlinear switched system. Biochemical production utilising fermentation processes evidences poor product repeatability. This project aims to control and optimise 1,3-propanediol production via microbial fermentation. 1,3-propanediol is an essential ingredient for many polymeric materials and is present in cosmetics, personal care and cleaning products. New theory and parallel algorithms will be developed for the control and optimisation of the mi ....Distributionally robust dynamic optimisation for nonlinear switched system. Biochemical production utilising fermentation processes evidences poor product repeatability. This project aims to control and optimise 1,3-propanediol production via microbial fermentation. 1,3-propanediol is an essential ingredient for many polymeric materials and is present in cosmetics, personal care and cleaning products. New theory and parallel algorithms will be developed for the control and optimisation of the microbial fermentation of 1,3-propanediol production, where the bacteria kinetic parameters are uncertain without full knowledge of the probability distribution. This theory will also be applicable to other fermentation processes. The project outcomes are expected to significantly improve the productivity of the biochemical engineering industry involving fermentation processes.Read moreRead less
Industrial Transformation Training Centres - Grant ID: IC190100017
Funder
Australian Research Council
Funding Amount
$3,703,664.00
Summary
ARC Training Centre for Integrated Operations for Complex Resources. This Training Centre aims to increase value in mining through clever applications of ‘lean processing’ and train the next generation of scientists and engineers in advanced sensors and data analytics in complex resources; knowledge priorities for the mining industry. Sensor information will be linked to the resource’s in-place knowledge to enable data analytics of all embedded knowledge. Processing can then be tuned to resource ....ARC Training Centre for Integrated Operations for Complex Resources. This Training Centre aims to increase value in mining through clever applications of ‘lean processing’ and train the next generation of scientists and engineers in advanced sensors and data analytics in complex resources; knowledge priorities for the mining industry. Sensor information will be linked to the resource’s in-place knowledge to enable data analytics of all embedded knowledge. Processing can then be tuned to resource attributes, maximising value ‘on the fly’. Benefits will include increasing certainty on product quality and maximising throughput and recovery. Outcomes will include new tools to rapidly model geological and geometallurgical uncertainty with sensor inputs, to track the resource to product and enhance interpretation.Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE210100184
Funder
Australian Research Council
Funding Amount
$183,437.00
Summary
Femtoliter Liquid Deposition Facility. This project aims to create a research capacity for direct printing of femtolitre volumes of functional liquids onto devices and surfaces. This project expects to enable the development of new sensing and electronic devices that require a novel fabrication step with delicate materials that cannot be deposited using existing processes. Expected outcomes include new chemical and biological sensors created through collaborative research between the partner in ....Femtoliter Liquid Deposition Facility. This project aims to create a research capacity for direct printing of femtolitre volumes of functional liquids onto devices and surfaces. This project expects to enable the development of new sensing and electronic devices that require a novel fabrication step with delicate materials that cannot be deposited using existing processes. Expected outcomes include new chemical and biological sensors created through collaborative research between the partner institutions and researchers. The benefits of this project should include the creation of a new rapid prototyping facility for Australian researchers, and the application of these capabilities for the development of new low-cost sensors for environmental gas sensing and glucose monitoring.Read moreRead less
Biomechanics Meets Robotics: Methods for Accurate and Fast Needle Targeting. This project intends to create a novel integrated framework for biomedical systems that can accurately target a needle. Accurate surgical targeting means less trauma and better patient outcomes. Needles are used in over half of all surgical procedures, but up to 38 per cent of these are affected by targeting errors. Achieving sub-millimetre accuracy is extremely difficult because inserting a needle displaces the tissue ....Biomechanics Meets Robotics: Methods for Accurate and Fast Needle Targeting. This project intends to create a novel integrated framework for biomedical systems that can accurately target a needle. Accurate surgical targeting means less trauma and better patient outcomes. Needles are used in over half of all surgical procedures, but up to 38 per cent of these are affected by targeting errors. Achieving sub-millimetre accuracy is extremely difficult because inserting a needle displaces the tissue and moves the target. How, then, can ultra-fine targeting be achieved? This project plans to integrate non-linear biomechanical models that predict tissue motion with accurate and principled motion control. It seeks to create new methods for surgical robots that will predict target motion and guide a needle to accurately intersect the target.Read moreRead less