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 30 matching student topics

Displaying 25–30 of 30 results

Degradation-conscious charging of lithium-ion batteries

The adoption of electric vehicles and grid storage systems by the present day consumers has been phenomenal. The most critical issue with the lithium-ion (Li-ion) battery is how to manage its degradation.Understanding battery degradation mechanisms and the development of charging strategies to optimally manage battery degradation is very important. There are a number of important issues that need to be addressed carefully, such as thermo-electrochemical modelling of large battery packs and fast charging protocols.

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

Dynamic wireless transfer systems

There's a growing interest by many governments and industry sectors on dynamic wireless power transfer systems for electric vehicle charging. This means there's increased research intensity in this domain. However, there are numerous important issues that need to be addressed carefully, such as:load estimationsensorless vehicle position estimationrobust controlimproved power converter topologies.

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

Increasing resilience of robotic systems through quickest change detection technology

Future robotics systems are likely to benefit from having an ability to self-diagnose self-failure or the presence of anomalous situations (so that they can switch to fallback or fail-safe modes). Example situations include subtle sensor or actuator failure and cyber security or physical intruder detection.Such low signal-to-noise anomaly detection or self-diagnose problems can be understood using powerful mathematical and statistical tools which QCR has a rich history of advancing through collaboration with industry partners and publication in premium international venues.

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

Semantic SLAM for robotic scene understanding, geometric-semantic representations for infrastructure monitoring and maintenance

Making a robot understand what it sees is one of the most fascinating goals in our current research. To this end, we develop novel methods for Semantic Mapping and Semantic SLAM by combining object detection with simultaneous localisation and mapping (SLAM) techniques.We work on novel approaches to SLAM that create semantically meaningful maps by combining geometric and semantic information. Such semantically enriched maps will help robots understand our complex world and will ultimately increase the range and sophistication of interactions …

Study level
PhD
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

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