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 43 matching student topics
Displaying 25–36 of 43 results
Designing smart visual technologies with people with intellectual disability
This area of research is seeking to understand how the meaning of images can be computed and used in the design of intelligent interfaces which can be used by and support people with cognitive disability (intellectual disability, dementia, brain injury), in their homes, their daily lives, or their work.The visual interactions of interest to this research may be embedded in a variety of technologies, including:assistive technologies (e.g. AAC)assistive robots (social robots and humanoid robots)conversational technologies (e.g. voice assistants)tangible technologies (e.g. …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
From digital design to human-robot collaborative masonry construction
This project addresses Queensland's critical housing shortage by exploring the productivity benefits of human-robot collaboration (HRC) in masonry construction. The research is conducted within the Building 4.0 CRC framework and leverages advanced facilities at QUT alongside industry partners such as Brickworks and the ARM Hub.By integrating collaborative robots (cobots), augmented reality (AR), parametric design tools (e.g. Grasshopper 3D), and AI algorithms, we aim to develop innovative workflows that enhance construction efficiency and material performance through the use of novel binders.
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Engineering
- School
- School of Architecture and Built Environment
- Research centre(s)
- QUT Resilience Centre
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
SLAM inside the human body: camera tracking and 3D reconstruction for medical procedures
Minimally invasive surgery and endoscopic interventions rely heavily on the clinician’s ability to understand and navigate complex internal anatomy using only a narrow and often restrictive field of view. Having access to an accurate and dynamic 3D reconstruction of the endoscopic scene, together with reliable camera pose estimation can significantly improve spatial awareness and navigation during procedures. The generated map can be used alongside the device’s estimated location to help clinicians better orient themselves within the patient, and it also …
- Study level
- PhD, Master of Philosophy, Honours
- 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
Human-Robot Collaboration
Study the dynamics and challenges of human-robot collaboration in the context of RPA and Business Process Automation. Explore ways to design collaborative interfaces, communication protocols, and decision-making frameworks that enable seamless interactions between human workers and automation robots (RPA), leading to efficient and effective task completion.
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Information Systems
- Research centre(s)
-
Centre for Behavioural Economics, Society and Technology
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
Cobot contact tasks through multi-sensory deep learning
Contact tasks like grinding, polishing and assembly require a robot to physically interact with both rigid and flexible objects. Current methods relying on force control have difficulty achieving consistent finishing results and lack robustness in dealing with non-linear dynamics inherent in how the material is handled. This project will take a new approach that detects and diagnoses the dynamical process through deep learning fusion of multi-sensory data, including force/tactile, visual, thermal, sound, and acoustic emission; and generate corrective process parameters …
- 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
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
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
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
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