Student topics

Complex manufacturing environments characterised by high value and high product mix manufacturing processes pose challenges to Human-Robot Collaboration (HRC). Allowing people to see what robots are ‘thinking’ will allow workers to efficiently collaborate with co-located robotic partners. A tighter integration of work routines requires improved approaches to support awareness in human-robotic co-working spaces. There is a need for solutions that also let people see what the robot is intending to do so that they can also efficiently adjust their actions …

Study level

PhD

Faculty

Faculty of Creative Industries, Education and Social Justice

School

School of Design

Research centre(s)

Design Lab

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

Microfluidic devices are increasingly relied upon to address the complexity of in-vitro disease models that are intended to mimic and provide insight into in-vivo processes and reactions to novel therapies and in turn, can become powerful companion diagnostic devices essential for predicting and individual patient’s reaction to a particular treatment. However, as these microfluidic devices become more and more prominent and necessary for addressing the drug screening and disease modeling needs of the industry, we have observed a lack in …

Study level

PhD, Master of Philosophy

Faculty

Faculty of Engineering

School

School of Mechanical, Medical and Process Engineering

Research centre(s)

Centre for Biomedical Technologies

Programming robots to carry out desired tasks is difficult and time-consuming. This PhD project focuses on collaborative and instructional dialogue agents to help human operators program robot tasks.In this collaborative scenario, a human operator converses with an AI agent to explain the steps that are to be performed, using high-level references and abstractions that make sense to the human, as opposed to simple verbal instructions corresponding to rudimentary robot movements. The AI agent must interpret the high-level instructions and translate …

Study level

PhD

School

School of Design

Research centre(s)

Design Lab

Accurately mapping large-scale infrastructure assets (power poles, bridges, buildings, whole suburbs and cities) is still exceptionally challenging for robots.The problem becomes even harder when we ask robots to map structures with intricate geometry or when the appearance or the structure of the environment changes over time, for example due to corrosion or construction activity.The problem difficulty is increased even more when sensor data from a range of different sensors (e.g. lidars and cameras, but also more specialised hardware such as …

Study level

PhD

Faculty

Faculty of Engineering

School

School of Electrical Engineering and Robotics

Research centre(s)

Centre for Robotics

Dr Scott Kiel-Chisholm is looking for PhD/MPhil candidates considering the legal dimensions from the development and adoption of neural interfaces. We are interested in looking for candidates looking at civil and criminal implications, comparative legal analysis and the legal and quasi-legal implications of neural interfaces for supra-legal institutions like the WTO and the EU. This topic is led by the QUT School of Law within the Datafication and Automation of Human Life research group.

Study level

PhD, Master of Philosophy, Honours

Faculty

Faculty of Business and Law

School

School of Law

Our research in the space of advanced quantitative medical imaging is investigating how to use ultrasound as a real time volumetric mapping tool of human tissues, to guide in a reliable and accurate way complex medical procedures1. We have developed several novel methods which make use of the most cutting-edge artificial intelligence technology2. For example, to show where the treatment target and the organs at risk are at all times during treatments in radiation therapy3, 4; or to inform robots …

Study level

PhD, Master of Philosophy

Faculty

Faculty of Health

School

School of Clinical Sciences

Research centre(s)

Centre for Biomedical Technologies

Re-localisation in robotics involves the process of determining a robot's current pose, consisting of its position and orientation. This can either be within a previously mapped and known environment (i.e. prior map) or relative to another robot in a multi-agent setup. Re-localisation is essential for enabling robots to perform tasks such as autonomous monitoring and exploration seamlessly, even when they encounter temporary challenges in precisely tracking their location in GPS-degraded environments. For instance, consider the 'wake-up' problem, where a robot …

Study level

PhD

School

School of Electrical Engineering and Robotics

Professor Belinda Bennett is interested in talking to students who wish to undertake research on legal issues related to technology, innovation and health, regulation of innovative health technologies, legal issues related to genomics, the use of artificial intelligence in health care, and the use of robotics in health care.

Study level

PhD, Master of Philosophy

Faculty

Faculty of Business and Law

School

School of Law

Research centre(s)

Australian Centre for Health Law Research

Think about the problem of maintaining equipment at remote work sites.  How can robotic technology help human maintenance staff to work more safely and productively?

Study level

PhD

Faculty

Faculty of Engineering

School

School of Electrical Engineering and Robotics

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

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