Industrial Transformation Training Centres - Grant ID: IC200100001
Funder
Australian Research Council
Funding Amount
$4,879,415.00
Summary
ARC Training Centre for Collaborative Robotics in Advanced Manufacturing. The Centre aims to build the human and technical capability Australia needs to underpin our global competitiveness in advanced manufacturing. The Centre will unite manufacturing businesses, including SMEs, and universities to develop collaborative robotics applications which combine the strengths of humans and robots in shared work environments. The Centre will train researchers, engineers, technologists and manufacturing ....ARC Training Centre for Collaborative Robotics in Advanced Manufacturing. The Centre aims to build the human and technical capability Australia needs to underpin our global competitiveness in advanced manufacturing. The Centre will unite manufacturing businesses, including SMEs, and universities to develop collaborative robotics applications which combine the strengths of humans and robots in shared work environments. The Centre will train researchers, engineers, technologists and manufacturing leaders with the expertise industry needs to boost safety, quality assurance, production efficiency, and workforce readiness. The intended outcome is to support Australian manufacturers to shift toward higher-potential markets, compete globally and attract and retain a digitally-capable workforce for the future.Read moreRead less
Mechanical advantage: biomimetic artificial muscles for micro-machines. This project will develop better ways to operate miniature machines by copying the way that muscle operates in Nature. The outcome will be important for portable devices like digital cameras that need small, efficient motors. The artificial muscles developed in this project may also be used in medical prosthetics and more agile robots.
Disassembly Automation of End-of-Life Electric Vehicle Batteries. This project aims to develop an automated disassembly solution for End-of-Life (EOL) Electric Vehicle (EV) batteries, which is flexible and modular to handle the uncertainties associated with model changes, condition of the EOL battery packs as well as the projected volume growth. The outcome of this project will lead to a better separation of EV battery components and materials. This will allow recycling of EOL EV batteries with ....Disassembly Automation of End-of-Life Electric Vehicle Batteries. This project aims to develop an automated disassembly solution for End-of-Life (EOL) Electric Vehicle (EV) batteries, which is flexible and modular to handle the uncertainties associated with model changes, condition of the EOL battery packs as well as the projected volume growth. The outcome of this project will lead to a better separation of EV battery components and materials. This will allow recycling of EOL EV batteries with a higher material recovery efficiency and a lower cost due to the significantly reduced labor cost; hence substantially reduce the environmental footprint associated with EOL treatment of these batteries.Read moreRead less
Non-invasive and safe human-machine interface (HMI) systems . This project aims to establish novel non-invasive human-machine interface systems based on multi-modal sensing and machine learning to intuitively command and control robotic and autonomous systems safely interacting and cooperating with humans. This will be achieved by harnessing the synergies across design optimisation, multi-modal sensing, additive manufacturing, machine learning, and assistive and cooperative robotic devices. Expe ....Non-invasive and safe human-machine interface (HMI) systems . This project aims to establish novel non-invasive human-machine interface systems based on multi-modal sensing and machine learning to intuitively command and control robotic and autonomous systems safely interacting and cooperating with humans. This will be achieved by harnessing the synergies across design optimisation, multi-modal sensing, additive manufacturing, machine learning, and assistive and cooperative robotic devices. Expected outcomes are a novel human-machine interface methodology, a new multi-purpose wearable data glove, and function and application-specific machine learning methods for cutting-edge applications in assistive robotic devices such as a prosthetic hand, advanced manufacturing, construction and agriculture.Read moreRead less
Personalised assistive robotic systems: Optimised collaborative teaming . Robotic assistance for humans performing physical tasks provides significant benefits in various sectors from advanced manufacturing and defence through to rehabilitation, prosthetics and aged care. However, most robotic systems are designed with an average user in mind rather than tailored to the individual. This innovative project will focus on developing new techniques for adapting the interface between human and robot ....Personalised assistive robotic systems: Optimised collaborative teaming . Robotic assistance for humans performing physical tasks provides significant benefits in various sectors from advanced manufacturing and defence through to rehabilitation, prosthetics and aged care. However, most robotic systems are designed with an average user in mind rather than tailored to the individual. This innovative project will focus on developing new techniques for adapting the interface between human and robotic systems, leading to personalised physical interactions that outperform traditional approaches in achieving a shared performance goal even in unstructured environments. The tools developed will be demonstrated using state-of-the-art facilities, and will leverage the unique skill sets of the international project team.Read moreRead less
Learning deep resilient behaviour for uncertainty-aware autonomy. This research project aims to propose a novel framework for developing uncertainty-aware autonomous systems using deep learning. There are fundamental gaps in our knowledge of deep uncertainty quantification and its application for risk-aware decision making. Novel algorithms will be proposed to reliably generate deep uncertainty estimates with low computational overhead. These estimates will be then exploited by safety-critical s ....Learning deep resilient behaviour for uncertainty-aware autonomy. This research project aims to propose a novel framework for developing uncertainty-aware autonomous systems using deep learning. There are fundamental gaps in our knowledge of deep uncertainty quantification and its application for risk-aware decision making. Novel algorithms will be proposed to reliably generate deep uncertainty estimates with low computational overhead. These estimates will be then exploited by safety-critical systems such as autonomous robots to identify risky actions and avoid catastrophise. Developed algorithms will be implemented on an autonomous robotic system to make it averse to uncertainties. The outcomes will greatly increase reliable telerobotic applications in mining, manufacturing, defence, and health.Read moreRead less
A System Behavioral Approach to Big Data-driven Nonlinear Process Control. This project aims to develop a novel process control approach that utilises big process data to improve the cost-effectiveness of industrial processes. Existing monitoring systems in the industry have been collecting a tremendous amount of process operation data but little effort has been made to use the big process data to enhance process operations. Based on the system behavioural approach and dissipativity theory, inte ....A System Behavioral Approach to Big Data-driven Nonlinear Process Control. This project aims to develop a novel process control approach that utilises big process data to improve the cost-effectiveness of industrial processes. Existing monitoring systems in the industry have been collecting a tremendous amount of process operation data but little effort has been made to use the big process data to enhance process operations. Based on the system behavioural approach and dissipativity theory, integrated with machine learning techniques, this project expects to develop a novel framework for data-driven control using big process data. The outcomes are expected to benefit the Australian process industry, where many processes are controlled by inadequate logic controllers, by improving their operational efficiency.Read moreRead less
Distributed nonlinear control based on differential dissipativity. This project aims to investigate the process control methodologies crucial to smart manufacturing It aims to develop a distributed optimisation-based nonlinear control approach for plant-wide flexible manufacturing, which can achieve time-varying operational targets including production rates and product specifications to meet dynamic market demands. This includes a contraction-based nonlinear distributed control framework that e ....Distributed nonlinear control based on differential dissipativity. This project aims to investigate the process control methodologies crucial to smart manufacturing It aims to develop a distributed optimisation-based nonlinear control approach for plant-wide flexible manufacturing, which can achieve time-varying operational targets including production rates and product specifications to meet dynamic market demands. This includes a contraction-based nonlinear distributed control framework that ensures plant-wide stability at any feasible set-points or references and a distributed economic model predictive control approach that coordinates autonomous controllers to achieve plant-wide economic objectives in a self-organising manner. The outcomes of this project are expected to form a process control framework for next-generation smart plants.Read moreRead less
Exploration of lead free ferroelectric crystals for transducer applications. This project aims to investigate lead free crystals, which are expected to possess high piezoelectric properties for medical imaging and underwater acoustics, as an alternative to toxic lead-based ferroelectrics which have been dominantly used in ultrasound transducers. The project will have significant impact on development of new lead-free ferroelectric crystals with desirable properties. This will benefit Australian ....Exploration of lead free ferroelectric crystals for transducer applications. This project aims to investigate lead free crystals, which are expected to possess high piezoelectric properties for medical imaging and underwater acoustics, as an alternative to toxic lead-based ferroelectrics which have been dominantly used in ultrasound transducers. The project will have significant impact on development of new lead-free ferroelectric crystals with desirable properties. This will benefit Australian industry by providing knowledge and technology of crystal growth, enabling advanced ultrasound transducers for medical imaging and underwater acoustic applications.Read moreRead less
Breakthrough technologies in implantable bionics. This project aims to introduce revolutionary changes in implantable bionics via miniaturisation, automation and improved reliability and generating new knowledge by leveraging recent advances in laser processes. Expected outcomes include innovative hybrid thin-film/thick-film electrode arrays with more channels and charge-carrying capacity for neuromodulation; novel glass interfaces that facilitate deeply-miniaturised hermetic packages; and failu ....Breakthrough technologies in implantable bionics. This project aims to introduce revolutionary changes in implantable bionics via miniaturisation, automation and improved reliability and generating new knowledge by leveraging recent advances in laser processes. Expected outcomes include innovative hybrid thin-film/thick-film electrode arrays with more channels and charge-carrying capacity for neuromodulation; novel glass interfaces that facilitate deeply-miniaturised hermetic packages; and failure analysis to ensure study aims result in new processes that are as or more reliable than the current state-of-the-art. This work will create new and novel manufacturing processes, and trains the next generation of innovators equipped with the tools to advance implantable bionics into the future.Read moreRead less