Student topics

Unmanned Traffic Management (UTM) describes a set of systems, services and procedures that will be developed to manage drone (unmanned aircraft systems/unmanned aerial vehicle/remotely piloted aircraft) operations in and around our cities. From surveillance tasks and package delivery through to passenger transport, UTM will be essentially in ensuring safe and efficient use of our airspace. Essentially, UTM is a new air traffic control system for drones with high levels of automation and advanced decision making and control. This research aims …

Study level

PhD

Faculty

Faculty of Engineering

School

School of Electrical Engineering and Robotics

Stable correspondence-free image-based visual servoing is a challenging and important problem.In classical image-based visual controllers, explicit feature correspondence (matching) to some desired arrangement (configuration) is required before a control input is obtained. Instead, this project will investigate variable feature correspondence and robust feature selection to simultaneously solve visual servoing problem, removing any feature tracking requirement or additional image processing.Also involving Prof Jason Ford.Example of recent past work

Study level

PhD

Faculty

Faculty of Engineering

School

School of Electrical Engineering and Robotics

Managing multiple robotic systems simultaneously poses many challenges around coordination and control. This is particularly true in environments where there's a lack of accurate localisation, sensing uncertainty and limited communications, yet there is an overarching mission objective or series of tasks that need to be completed.In this project, you will explore and develop approaches around multi-robot swarming and coordinated formation control for dynamic process monitoring, target tracking and coordinated mapping. There will be a particular focus on underwater and surface …

Study level

PhD

Faculty

Faculty of Engineering

School

School of Electrical Engineering and Robotics

Control of connected vehicle platoons can ensure the swift movement of traffic through a city by sharing vehicles' states and desired actuation. This networked control design can alleviate traffic jams, reduce vehicle emissions, and reduce fuel usage through improved aerodynamics. Model Predictive Control algorithms are a natural solution to address constraints arising from both communications and system dynamics. A key challenge is to design distributed control algorithms that are robust to disturbances in the environment and to stochastic information from …

Study level

PhD

Faculty

Faculty of Engineering

School

School of Electrical Engineering and Robotics

Many critical infrastructure systems are operated using networked feedback control. These systems crucially use wireless networks to transmit sensor and actuation signals. Unfortunately, wireless technology (sensors, actuators and communications) is unreliable and increasingly vulnerable to cyberattacks. This causes performance degradation, loss of stability, system failure and, at worst, leads to deaths and disasters. Therefore, mitigating the effects of attack algorithms on Cyberphysical Systems (CPSs) is of utmost importance.A distinguishing aspect, when compared to attacks on classical information systems, is that …

Study level

PhD

Faculty

Faculty of Engineering

School

School of Electrical Engineering and Robotics

Cyberphysical systems (CPS) integrate sensors, communication networks, controllers, dynamic processes and actuators. CPS play an increasingly important role in modern society, in areas such as energy, transportation, manufacturing, healthcare. Due to the interplay between control systems, communications and computations, the design of CPS requires novel approaches, which bridge disciplinary boundaries.This PhD project will develop engineering science and methods for the analysis and design of CPS operating in closed loop. Your research will bring together elements of control systems engineering, as …

Study level

PhD

Faculty

Faculty of Engineering

School

School of Electrical Engineering and Robotics

Estimating the motion of a landing deck, and controlling the descent of a drone under severe weather events is a challenging task. We have developed a simulation environment to test control and prediction algorithms that could allow a drone to safely land on a ship. This PhD program involves the investigation of innovative predictive control approaches closely linked with predictors that provide T secs ahead the future position of the landing deck.

Study level

PhD

Faculty

Faculty of Engineering

School

School of Electrical Engineering and Robotics

AI that is pre-programmed is limited in its tasks and human bias. Learning systems offer richer decision-making behaviors where collaborative projects have led to the following three systems that require integration:A symbolic learning system that can continually learn Boolean classification problems as they are presented to it. But this needs to be extended to real-valued, noisy and uncertain classification problems.A lateralized system that can consider an input at the constituent level and the holistic level simultaneously, which enables flexible and …

Study level

PhD

Faculty

Faculty of Engineering

School

School of Electrical Engineering and Robotics

In today’s highly dynamic markets, companies seek to increase customer trust to gain a competitive advantage based on aspects such as customer engagement, retention, advocacy, and pricing. However, while a large body of trust research exists, little is known regarding the operative return on trust.The project explores these trust economics to quantify the impact of trust gains to guide organisations and utilise their resources more effectively. In this context, trust-related key performance indicators have to be identified to explore their …

Study level

PhD, Master of Philosophy

Faculty

Faculty of Business and Law

School

School of Accountancy

Research centre(s)

Centre for Future Enterprise

Complex manufacturing environments characterised by high value and high product mix manufacturing processes pose challenges to Human-Robot Collaboration (HRC). Allowing people to see what robots are ‘thinking’ will allow workers to efficiently collaborate with co-located robotic partners. A tighter integration of work routines requires improved approaches to support awareness in human-robotic co-working spaces. There is a need for solutions that also let people see what the robot is intending to do so that they can also efficiently adjust their actions …

Study level

PhD

Faculty

Faculty of Creative Industries, Education and Social Justice

School

School of Design

Research centre(s)

Design Lab

Effective models of place-based funding remain conceptually unresolved.  Place-based, collective impact initiatives are increasingly recognised for creating long-term systems change, yet the role of philanthropy in supporting, advocating for and catalysing change is underexplored.I am interested in supervising research into conceptual models of philanthropic funding for place-based initiatives, to explain and clarify the elements and characteristics of successful, long-term relationships between philanthropic funders and place-based, community-led initiatives in regional and urban Australian communities.

Study level

PhD, Master of Philosophy

Faculty

Faculty of Business and Law

School

School of Accountancy

Research centre(s)

Australian Centre for Philanthropy and Nonprofit Studies

Identify the specific competencies and skills that leaders need to effectively lead AI adoption initiatives in organisations. Research can focus on areas such as data literacy, AI literacy, critical thinking, decision-making, and the ability to manage and interpret AI-driven insights. Develop frameworks for assessing and developing these competencies in leaders.

Study level

PhD, Master of Philosophy, Honours

Faculty

Faculty of Science

School

School of Information Systems

Research centre(s)

Centre for Behavioural Economics, Society and Technology