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 655 matching student topics

Displaying 121–132 of 655 results

Understanding and designing for digital self-care

The aim of this project is to better understand self-care practices with digital technologies amongst young adults and to explore opportunities for digital technology design.Self-care is a process of purposeful engagement in practices that promote holistic health and well-being of the self. Holistic health implies overall health and this encompasses more than just physical health but also includes mental, emotional and even spiritual health of a person. For some people, cooking can be a form of self-care to eat healthily …

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Computer Science

Ubiquitous visual positioning devices

Everything that moves is defined and limited by its ability to navigate the world in which it exists. Knowing where you are located in the world is a key navigational capability for people, animals, and both autonomous and human-operated platforms ranging from self-driving cars to aircraft.But accurate and trustworthy positional knowledge has widespread potential implications beyond navigation: it can, for example, allow life-and-death decisions in defence and in tracking the spread of global pandemics. Both the potential of and problems …

Study level
Honours
Faculty
Faculty of Engineering
School
School of Electrical Engineering and Robotics
Research centre(s)
Centre for Robotics

Human robotic interaction prototyping toolkit

Design relies on prototyping methods to help envisage future design concepts and elicit feedback from potential users. A key challenge the design of human-robot interaction (HRI) with collaborative robots is the current lack of prototyping tools, techniques, and materials. Without good prototyping tools, it is difficult to move beyond existing solutions and develop new ways of interacting with robots that make them more accessible and easier for people to use.This project will develop a robot collaboration prototyping toolkit that combines …

Study level
PhD
Faculty
Faculty of Creative Industries, Education and Social Justice
School
School of Design
Research centre(s)

Design Lab

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
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

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

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

Implicit representations for place recognition and robot localisation

This project will develop a novel localization pipeline based on implicit map representations. Unlike traditional approaches that use explicit representations like point clouds or voxel grids, the map in our project is represented implicitly in the weights of neural networks such as Neural Radiance Fields (NeRF). You will get a chance to develop a new class of localization algorithms that work directly on the implicit representation, bypassing the costly rendering step from implicit to explicit representation. The designed algorithms will …

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

Space robotics: Scene understanding for Lunar/Mars Rover

The QUT Centre for Robotics is working with the Australian Space Agency on the newly established Australian space program, in which robots will play a key role. There are multiple PhD projects available to work on different aspect of developing a new Lunar Rover (and later Mars Rover) and in particular its intelligence and autonomy. Future rovers will not only need to conduct exploration and science missions as famous rovers such as NASA's Curiosity or Perseverance are doing right now …

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

Safe autonomous driving through dense vegetation via advanced perception

One of the remaining challenges to achieve off-road autonomous navigation for mobile robots is the accurate evaluation of vegetated environments, to determine where a robot can safely drive through. To achieve this, robots may use extra sensory modalities compared to humans, such as RADARs that can penetrate through vegetation and see behind it what is not visible to the naked eye. Another option is to physically interact with the environment to 'clear the way'.

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

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

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