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.
Found 7 matching student topics
Displaying 1–7 of 7 results
UAV navigation in GPS denied environments
This PhD project aims to develop a framework for unmanned aerial vehicles (UAV), which optimally balances localisation, mapping and other objectives in order to solve sequential decision tasks under map and pose uncertainty. This project expects to generate new knowledge in UAV navigation using an innovative approach by combining simultaneous localisation and mapping algorithms with partially observable markov decision processes. The project’s expected outcomes will enable UAVs to solve multiple objectives under map and pose uncertainty in GPS-denied environments. This …
- Study level
- PhD
- Faculty
- Faculty of Engineering
- School
- School of Electrical Engineering and Robotics
Multi-UAV navigation in GPS denied environments
The aim of this research is to develop a framework for multiple Unmanned Aerial Vehicles (UAV), that balances information sharing, exploration, localization, mapping, and other planning objectives thus allowing a team of UAVs to navigate in complex environments in time critical situations. This project expects to generate new knowledge in UAV navigation using an innovative approach by combining Simultaneous Localization and Mapping (SLAM) algorithms with Partially Observable Markov Decision Processes (POMDP) and Deep Reinforcement learning. This should provide significant benefits, …
- Study level
- PhD, Vacation research experience scheme
- 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
Reimagining air travel passenger experience
Air travel is poised for systemic transformation due to the advent and implementation of emerging technologies. For example, electric vertical take-off and landing aircraft have the potential to deliver sustainable, efficient, and fast, short-range mobility in urban environments. Advances in fuel and propulsion systems, such as those used in hydrogen electric aircraft, could have broader impact, delivering aspirations of zero carbon aviation.Given the nascent qualities of such technology advances, it is unclear how they will affect passenger experience. Currently, air …
- Study level
- PhD
- Faculty
- Faculty of Creative Industries, Education and Social Justice
- School
- School of Design
- Research centre(s)
-
Design Lab
Basic aircraft collision risk modelling and visualisation
Aircraft collision risk modelling is complex yet key to ensuring safe air transport (both crewed and uncrewed aircraft). Different collision risk models are better suited to different airspace environments which means model comparison and evaluation is an important research problem. This project takes a deeper look into a specific collision risk modelling approach: gas models.
- Study level
- Honours, Vacation research experience scheme
- Faculty
- Faculty of Engineering
- School
- School of Electrical Engineering and Robotics
- Research centre(s)
- Centre for Robotics
Deep learning for next-generation visual place recognition: sequence matching in robotic navigation
Are you interested in contributing to the advancement of robotics and navigation systems? In this VRES project, you will explore the cutting-edge field of visual place recognition (VPR).In both human and robotic navigation, understanding our location is essential for various tasks, such as obtaining resources, commuting, and socialising. The future of robots and augmented reality devices depends on reliable localisation systems. VPR is a critical aspect of robotics that allows for navigation and decision-making without relying on satellite systems, which …
- Study level
- Vacation research experience scheme
- Faculty
- Faculty of Engineering
- School
- School of Electrical Engineering and Robotics
- Research centre(s)
- Centre for Robotics
Semantic based onboard UAV navigation
In recent years the field of robotic navigation has increasingly harnessed semantic information in order to facilitate the planning and execution of robotic tasks. The use of semantic information focuses on employing representations more understandable by humans to accomplish tasks with robustness against environmental change, limiting memory requirements and improving scalability. Contemporary computer vision algorithms extracting semantic information have continuously improved their performance on benchmark datasets, however, most computations are expensive, limiting their use for robotic platforms constrained by size, …
- Study level
- PhD
- Faculty
- Faculty of Engineering
- School
- School of Electrical Engineering and Robotics
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