QUT offers a diverse range of student topics for Honours, Masters and PhD study. Search to find a topic that interests you or propose your own research topic to a prospective QUT supervisor. You may also ask a prospective supervisor to help you identify or refine a research topic.

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Found 45 matching student topics

Displaying 25–36 of 45 results

Robotic intention visualisation

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

The dark side of robotic process automation

Pandemics such as COVID 19 have forced organisations to pursue hyper-automation to maintain operational sustainability. Many organisations are keen to adopt Robotic Process Automation (RPA) to dramatically improve operational efficiency. However, evidence to date highlighted various associated challenges associated with adoption of RPA in organisations.Furthermore, recent surveys by consultant organisations found a high RPA project fail rate and their inability to meet the expected return on investment.

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Information Systems
Research centre(s)
Centre for Future Enterprise

Investigating Australian consumer perspectives on smart home products

Technological advancements such as information and communication technologies, artificial intelligence, internet-of-things, robotics, and the increasing popularity of the smart city and smart living movements during the last couple of decades have created and intensified a boom of the smart home industry. At present, digital technology applications uptake in homes has become common and increasingly changed people’s lifestyles. Smart home technology provides a suite of independently and remotely controlled software and hardware connected to a network to deliver smart living. Smart …

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Engineering
School
School of Architecture and Built Environment

Robotic maintenance of equipment

Think about the problem of maintaining equipment at remote work sites.  How can robotic technology help human maintenance staff to work more safely and productively?

Study level
PhD
Faculty
Faculty of Engineering
School
School of Electrical Engineering and Robotics

Robot learning for navigation, interaction, and complex tasks

How can robots best learn to navigate in challenging environments and execute complex tasks, such as tidying up an apartment or assist humans in their everyday domestic chores?Often, hand-written architectures are based on complicated state machines that become intractable to design and maintain with growing task complexity. I am interested in developing learning-based approaches that are effective and efficient and scale better to complicated tasks.Especially learning based on semantic information (such as extracted by the research in semantic SLAM above), …

Study level
PhD
Faculty
Faculty of Engineering
School
School of Electrical Engineering and Robotics

Very high-speed dynamic motion planning for arm robots

Robot manipulator arms are increasingly used for logistics applications.  These typically require robots to run at the limits of their performance: motor torque and motor velocity.  Added challenges include significant payloads (if we are schlepping heavy parcels) with apriori unknown mass, the possibility of boxes detaching from the gripper under high acceleration, and fixed obstacles in the workspace.  How can we determine the limits to performance, quickly identify the payload mass, then plan the fastest path to get from A to B.

Study level
PhD
Faculty
Faculty of Engineering
School
School of Electrical Engineering and Robotics

Robust feature selection and correspondence for visual control of robots

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

SLAM inside the human body: camera tracking and 3D reconstruction for medical procedures

Minimally invasive surgery and endoscopic interventions rely heavily on the clinician’s ability to understand and navigate complex internal anatomy using only a narrow and often restrictive field of view. Having access to an accurate and dynamic 3D reconstruction of the endoscopic scene, together with reliable camera pose estimation can significantly improve spatial awareness and navigation during procedures. The generated map can be used alongside the device’s estimated location to help clinicians better orient themselves within the patient, and it also …

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Engineering
School
School of Electrical Engineering and Robotics

From digital design to human-robot collaborative masonry construction

This project addresses Queensland's critical housing shortage by exploring the productivity benefits of human-robot collaboration (HRC) in masonry construction. The research is conducted within the Building 4.0 CRC framework and leverages advanced facilities at QUT alongside industry partners such as Brickworks and the ARM Hub.By integrating collaborative robots (cobots), augmented reality (AR), parametric design tools (e.g. Grasshopper 3D), and AI algorithms, we aim to develop innovative workflows that enhance construction efficiency and material performance through the use of novel binders.

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Engineering
School
School of Architecture and Built Environment
Research centre(s)
QUT Resilience Centre

Augmented reality (AR) applications for robotic scene understanding

Augmented reality (AR), or mixed reality, has become a mature technology with many possible practical applications in manufacturing, retail, navigation and entertainment.We're interested in using AR to support human-robot interaction. In this project, you'll investigate how a human can use AR to better understand how a robot perceives the world and to understand the robot's intentions.

Study level
Honours
Faculty
Faculty of Engineering
School
School of Electrical Engineering and Robotics

Perception-to-action for collision avoidance using robotic boats

Much like driving cars on our roads, there are rules around driving maritime systems (boats) on waterways regarding where you can drive and how to avoid and behave in potential collision situations.In this project, you'll explore and develop state-of-the-art perception and decision support solutions to allow robotic surface vessels (robot boats) to safely travel complex waterways in and around other human-driven vessels. This will involve diving deep into vision and laser-based sensor processing and fusion algorithms, as well as robust …

Study level
PhD
Faculty
Faculty of Engineering
School
School of Electrical Engineering and Robotics

High-speed robotic waste separation

Sorting waste or recyclables is an important but unpleasant job, currently done by specialised machinery and humans for the hard bits.  What are the core challenges that could be done by "robots that see". This is a challenging problem in perception, dynamic path planning and control.

Study level
PhD
Faculty
Faculty of Engineering
School
School of Electrical Engineering and Robotics

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