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 145 matching student topics
Displaying 25–36 of 145 results
Outdoor litter collection
Cleanup Australia day in 2019 collected 17,000 ute loads of rubbish from rivers, parks, beaches, roadways and bushland. Imagine a robot ground vehicle or boat that could identify litter, plan the motion of the robot so that it can pick up items in the right sequence so that it doesn't have to stop, while also navigating obstacles in the environment. 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
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
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
Drone ship landing under adverse sea condition
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
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
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
Continual learning system
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
Capture and reuse of phosphate nutrients
Nutrients such as ammonium and phosphate species are essential in agriculture. However, release of excessive amounts of nutrients to waterways may result in eutrophication which can lead to toxic algae blooms, killing of fish and destruction of the environment.Compounding this issue is the fact that phosphate rock sources are gradually being exhausted. Hence, finding a means to capture and reuse phosphate species from sources such as wastewater treatment plants is potentially attractive.Consequently, this project involves the development of new phosphate …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Engineering
- School
- School of Mechanical, Medical and Process Engineering
Understanding responsible deployment of computer vision for urban planning
Advances in artificial intelligence (AI) offer urban planning practice many novel prospects. By the responsive use of AI, planners can effectively analyse data, improve processes, increase efficiency, and prioritise human-centric aspects of planning to develop sustainable cities. Computer vision is one of the key areas where responsible AI is applied in urban planning to revolutionise the analysis and interpretation of visual data, like images and videos captured in cities to aid decision and plan making processes. While the potential impacts …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Engineering
- School
- School of Architecture and Built Environment
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