Fault detection and identification in nonlinear complex systems. Complex systems usually comprise a large number of inter-dependent subsystems linked together to perform a certain task. Examples of such systems are power systems, irrigation systems, air traffic control systems, to name a few. Such systems are subject to component failure or malfunction. Total failure can cause an unacceptable financial losses and/or danger to personnel. It is therefore extremely essential, from economic and safe ....Fault detection and identification in nonlinear complex systems. Complex systems usually comprise a large number of inter-dependent subsystems linked together to perform a certain task. Examples of such systems are power systems, irrigation systems, air traffic control systems, to name a few. Such systems are subject to component failure or malfunction. Total failure can cause an unacceptable financial losses and/or danger to personnel. It is therefore extremely essential, from economic and safety view points, that a way be found to ensure reliable and viable operation of complex plants. A first step in achieving this goal is to detect faults on-line and in real-time when they occur and identify their location and characteristics, which is the aim of this project.Read moreRead less
Context-aware verification and validation framework for autonomous driving. This project aims to enhance the reliability and safety of emerging self-driving vehicles, through a framework that supports the validation and verification of autonomous driving systems. This project expects to generate new knowledge in areas of software engineering, intelligent transport, and machine learning, using a multi-disciplinary research combining expertise from various fields. Expected outcomes of this project ....Context-aware verification and validation framework for autonomous driving. This project aims to enhance the reliability and safety of emerging self-driving vehicles, through a framework that supports the validation and verification of autonomous driving systems. This project expects to generate new knowledge in areas of software engineering, intelligent transport, and machine learning, using a multi-disciplinary research combining expertise from various fields. Expected outcomes of this project are a family of new context-aware techniques to verify and validate complex behaviours in autonomous driving. This should provide significant benefits, such as safe autonomous driving systems and the improved journey experience and security for road users.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE150101365
Funder
Australian Research Council
Funding Amount
$360,000.00
Summary
In-person tele-presence through hybrid camera networks. This project aims to develop novel theories and algorithms for live capturing of accurate dense 3D models of moving subjects based on hybrid camera networks. The latter consist of a mix of static external red, green, blue plus depth (RGB-D) cameras and a dynamic head-mounted regular camera. The scientific novelties will be dense, non-rigid, and collaborative structure-from-motion theories that maximise the exploitation of such hybrid inform ....In-person tele-presence through hybrid camera networks. This project aims to develop novel theories and algorithms for live capturing of accurate dense 3D models of moving subjects based on hybrid camera networks. The latter consist of a mix of static external red, green, blue plus depth (RGB-D) cameras and a dynamic head-mounted regular camera. The scientific novelties will be dense, non-rigid, and collaborative structure-from-motion theories that maximise the exploitation of such hybrid information, for instance by utilising exact head-pose information. The outcome is a working prototype producing live full-body animations, thus leveraging new applications in the Information Technology industry. Highly strategically relevant examples are given by 3D tele-presence, enhanced tele-operation, robotics, and intelligent transportation systems.Read moreRead less
Estimation of Complex Networked Dynamic Systems. An essential part of science and engineering is the development of mathematical models to describe how observed quantities relate to one another. For example, such models have proven to be extremely powerful in predicting the value of financial instruments, in providing high performance control of robots, and in detecting faults or changes in petrochemical processing plants. Constructing these models based on measurements from the system itself is ....Estimation of Complex Networked Dynamic Systems. An essential part of science and engineering is the development of mathematical models to describe how observed quantities relate to one another. For example, such models have proven to be extremely powerful in predicting the value of financial instruments, in providing high performance control of robots, and in detecting faults or changes in petrochemical processing plants. Constructing these models based on measurements from the system itself is known as system identification. This project is directed at developing new system identification methods for situations that, on the one hand, have previously been considered unsolvable, and on the other, are acknowledged as being of high practical interest.Read moreRead less
Feedback entropy in dynamical systems. This project aims to use the fundamental concept of entropy to help evaluate the decision-making effort in a variety of feedback control systems in science and engineering. This understanding will help develop smarter technologies and algorithms in areas such as manufacturing, vehicular technology and automated irrigation.
Nonstochastic information flows in networked dynamical systems. Feedback control is a crucial element of manufacturing, vehicular and energy systems, and is needed to guarantee hard performance bounds in safety- and mission-critical environments. When these control systems are implemented over communication networks, the amount of information flowing through them becomes a critical determinant of performance. However, the nonprobabilistic control objectives make standard information theory inapp ....Nonstochastic information flows in networked dynamical systems. Feedback control is a crucial element of manufacturing, vehicular and energy systems, and is needed to guarantee hard performance bounds in safety- and mission-critical environments. When these control systems are implemented over communication networks, the amount of information flowing through them becomes a critical determinant of performance. However, the nonprobabilistic control objectives make standard information theory inapplicable. This project aims to develop a novel, nonstochastic theory of information in order to analyse and design networked dynamical systems that obey worst-case performance limits. This will yield robust, probability-free algorithms for distributed control, filtering and causality inference.Read moreRead less
A hybrid system framework for robust model predictive control. This project will produce new analysis and design tools to develop novel hybrid model predictive control systems with guaranteed stability, robustness and fault tolerance. We foresee major benefits for Australia by enhancing its scientific reputation and by promoting safety, efficiency and technological innovation in industries and services.
Efficient computational methods for worst-case analysis and optimal control of nonlinear dynamical systems. Natural and technological systems can exhibit extremely complicated behaviour in worst-case scenarios. This project will develop efficient mathematical and computational tools that will enable this behaviour to be understood and controlled.
Exploiting the Symmetry of Spatial Awareness for 21st Century Automation. This project aims to enable autonomous robotic systems to operate more robustly and more reliably in the complex, cluttered and dynamic environments found in real-world applications. Applying the latest understanding of symmetry in non-linear systems and control provides tools that can be used to develop new design methodologies for spatial awareness algorithms. The outcomes of this project should increase Australia's ca ....Exploiting the Symmetry of Spatial Awareness for 21st Century Automation. This project aims to enable autonomous robotic systems to operate more robustly and more reliably in the complex, cluttered and dynamic environments found in real-world applications. Applying the latest understanding of symmetry in non-linear systems and control provides tools that can be used to develop new design methodologies for spatial awareness algorithms. The outcomes of this project should increase Australia's capacity in high-tech systems and deliver world best open source code for spatial awareness problems to enable the next generation of automation in Australia.Read moreRead less
Integrated high-performance control of aerial robots in dynamic environments. The outcomes of this project will enable novice pilots to safely operate aerial robots in dangerous and dynamic environments through novel intuitive user interfaces and advanced control algorithms. The project will contribute strongly to Australia's presence in the emerging world market of unmanned aerial vehicles.