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 41 matching student topics
Displaying 25–36 of 41 results
Design of a soft force sensor for an endoscope
A challenge when using robotics tools in a medical setting like surgery and endoscopy is the lack of force feedback for the medical practitioner. Commonly used instruments and tools lack the ability to sense forces and therefore this information cannot be conveyed to the operator. By incorporating force sensing technology into these devices, medical professionals can obtain real-time feedback on the amount of pressure being applied to tissues and organs inside the body. This invaluable data enables them to navigate …
- Study level
- Vacation research experience scheme
- Faculty
- Faculty of Engineering
- School
- School of Electrical Engineering and Robotics
- Research centre(s)
- Centre for Robotics
A soft robotic manipulator for spinal surgery
The geriatric population in Australia (4.2 million 2020, ABS), is growing steadily with numbers expected to double in the coming years. Incidences of spinal disorders requiring surgical treatment are therefore predicted to increase, incurring an estimated lifetime cost of AUD 3.7 billion per case (The Treasury). Robotics, an increasingly important component of modern medicine, is well suited to address the minimally invasive surgical needs of treating the spine.This project proposes the use of a soft-robotic manipulator to carry out spinal …
- Study level
- PhD
- Faculty
- Faculty of Engineering
- School
- School of Electrical Engineering and Robotics
- Research centre(s)
- Centre for Robotics
Optimisation of piezoelectric materials for robotics applications
Piezoelectricity, which translates to “pressure electricity”, is the phenomenon in which certain materials convert mechanical energy to electrical energy, and vice versa. Such materials are common-place and are used in a variety of applications including sensor, actuator, and energy harvesting technologies. The capabilities of such piezoelectric materials have not yet been fully realised. We plan to use computational structural optimisation to design new piezoelectric materials and components that may contribute to novel sensing technologies for robotics applications. Essentially, robots need …
- Study level
- PhD, Master of Philosophy, Honours, Vacation research experience scheme
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
Sun-guided localisation: harnessing absolute direction for advanced visual place recognition in robotics
The significance of positioning and localisation systems in robotics is well-established. Visual place recognition (VPR) enables robots to localise themselves visually, facilitating navigation and decision-making without relying on satellite systems, which can be unavailable indoors and unreliable in densely built areas.This project aims to enhance the VPR process by incorporating supplementary information to simplify the place recognition problem. We will investigate the use of an additional network head that predicts the absolute direction of an image, potentially serving as supplementary …
- Study level
- Vacation research experience scheme
- Faculty
- Faculty of Engineering
- School
- School of Electrical Engineering and Robotics
- Research centre(s)
- Centre for 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
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
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
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
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
The insufficient informativeness of measurements in Bayesian detection problems
Shiryaev's Bayesian Quickest Change Detection (QCD) problem is to detect a change in the statistical problems of an observed process. This is an important signal processing problem with application in a diverse range of areas, including:automatic controlquality controlstatisticstarget detection.Recently a critical deficiency in Shiryaev's QCD problem has been identified to occur due to the insufficient informativeness of measurement in low signal-to-noise (SNR) to overcome geometric prior assumption on the change event.These deficiencies are due to the non-ergodic nature of the …
- Study level
- PhD
- Faculty
- Faculty of Engineering
- School
- School of Electrical Engineering and Robotics
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