The UTS School of Mechanical and Mechatronic Engineering (MME) is seeking PhD and Masters students to work on a number of research projects at the Robotics Institute, Centre for Advanced Manufacturing and Centre for Audio, Acoustics and Vibration.
Find the right project for you
Search the list below to find a potential academic supervisor at the School of Mechanical and Mechatronic Engineering compatible with your area of interest.
To engage with your potential supervisor, please submit an expression of interest in their research project with the following:
- A brief email outlining your relevant areas of interest and experience in the project (1-3 sentences)
- Your CV (max 2 pages)
- Academic transcripts of all degrees (unofficial transcripts may be included)
For funding opportunities on specific postgraduate projects, please directly liaise with the principal supervisor listed on the project description after submitting your expression of interest.
Research projects on offer
Robotics Institute
Project Titles/Themes
- Sensing and Perception for Blockage Detection in Underground Broadband Pipes
- Dynamic Control of a 3 - legged robot
- Fast and reliable motion planning for 3-legged climbing robot
- Robot Decision Making through Behaviour Trees
- Multi-Robot Information Gathering with Hybrid Centralised-Decentralised Coordination
- Next-Generation Intelligent Robotic Mobility Aid for Vision Impaired People
Sensing and Perception for Blockage Detection in Underground Broadband Pipes
Supervisor
Professor Sarath Kodagoda
Industry Professor Ray Owen
MME Centre/Institute
Robotics Institute
School of Mechanical & Mechatronic Engineering
Degree Level
- Doctor of Philosophy
Project Description
Hidden beneath our urban landscapes, broadband networks serve as the digital backbone of modern connectivity, enabling communication essential for homes, businesses, and industries. Despite their resilience, these underground pipes that house network cables are susceptible to degradation and faults. Traditional methods that facilitate the detection of blockages remain outdated, inefficient, and often result in unnecessary excavation and costly remediation, causing delays and budget overruns.
Inspired by large-scale broadband infrastructure deployments by entities like NBN Co in Australia, BT Openreach in the United Kingdom, and Chorus in New Zealand, the project aims to produce robust, novel solutions that revolutionise blockage detection in small-diameter underground pipes.
The successful candidate will focus on analysing multimodal sensing technologies and their capability to assess the continuity and characteristics of broadband pipes. Analytical solutions and numerical studies will be validated by experimental data obtained from testbenches setup to imitate common pipe conditions and environments. The effects of various parameters such as, blockage type, ground material, pipe depth and length, environmental noise, and sensor array parameters will be investigated, as well as the potential for leveraging advanced signal processing, AI, and machine learning techniques.
This project would suit applicants that have a strong background in robotics, mechatronics, AI, and machine learning.
Open to domestic and international students
Duration: 3.5 years (flexible)
Closing Date: When filled
For more information contact Professor Sarath Kodagoda sarath.kodagoda@uts.edu.au or Industry Professor Ray Own ray.owen@uts.edu.au
Dynamic control of a 3-legged climbing robot
Supervisor
Dr. Felix Kong
MME Centre/Institute
Robotics Institute
School of Mechanical & Mechatronic Engineering
Degree Level
- Doctor of Philosophy
- Master of Engineering (Research)
Project Description
I am working with Mr Clyde Webster on a 3-legged climbing robot to do inspection and maintenance of structures like electrical towers, telecommunications infrastructure, and even in-orbit space structures. Our goal is to have efficient, dynamic motions like Boston Dynamics' Atlas, which will require (among other things) fast and accurate motion control. Check out our robot hardware.
We are primarily interested in locomotion at the moment - how to improve control when climbing. Currently we have a feedback controller that works, but doesn't plan ahead, making dynamic reaching motions difficult. While there are lots of interesting problems just in locomotion, we're also interested in eventually developing the control algorithm to perform manipulation using the "neck" of the robot. This will allow us to exert forces on the structure, with the aim of one day doing useful work like angle grinding, drilling, or replacing objects on the structure.
This project would suit graduating students with a background in optimal control, or optimization in other fields. Strong familiarity with basic mathematics (e.g., linear algebra, ordinary differential equations) and robot modelling (e.g. modelling of physical systems, robot manipulator kinematics) are required. MATLAB is required; familiarity with Python, C++, and ROS are nice-to-haves.
Open to domestic and international students
Duration: 3.5 years (flexible)
Closing Date: When filled
For more information contact Dr Felix Kong: felix.kong@uts.edu.au
Fast and reliable motion planning for 3-legged climbing robot
Supervisor
Dr Felix Kong
MME Centre/Institute
Robotics Institute
School of Mechanical & Mechatronic Engineering
Degree Level
- Doctor of Philosophy
- Master of Engineering (Research)
Project Description
I am working with Mr Clyde Webster on a 3-legged climbing robot to do inspection and maintenance of structures like electrical towers, telecommunications infrastructure, and even in-orbit space structures. Our goal is to have efficient, dynamic motions like Boston Dynamics' Atlas, which will require (among other things) fast and accurate motion control. Check out our robot hardware.
This project is focused on motion planning - what leg do we move next, and where/how should we place its foot? And after we decide that, how should the body and each joint move to achieve that foot placement? At the moment, we're interested in the problem of locomotion, i.e., of climbing up/around/into/through the structure. Perhaps later in the project, we're interested in the motion planning problem for manipulation - how should the robot position itself if it wants to drill a hole, or angle grind the surface of a beam? On top of this all, we're looking for fast algorithms that can run onboard, without requiring the robot to "stop and think" before moving.
This project would suit graduating students with a background in optimization and/or dynamic programming. Strong familiarity with basic mathematics (e.g., linear algebra, ordinary differential equations) and robot modeling (e.g. dynamic modeling of multi-body systems, robot manipulator kinematics) are required. MATLAB is required; familiarity with Python, C++, and ROS are nice-to-haves.
Open to domestic and international students
Duration: 3.5 years (flexible)
Closing Date: When filled
For more information contact Dr Felix Kong: felix.kong@uts.edu.au
Robot Decision Making through Behaviour Trees
Supervisor
Dr Graeme Best
MME Centre/Institute
Robotics Institute
Degree Level
- Doctor of Philosophy
- Master of Engineering (Research)
Project Description
Robots performing complex missions are often required to switch between high-level behaviours, such as "explore", "pick up object", and "return home". A key challenge is determining how to autonomously switch between these behaviours to satisfy the objectives of a mission. The behaviour tree architecture has emerged as a convenient data structure for encoding this decision making. This project will involve making behaviour trees even more useful for real robotic systems.
There is broad scope to take this project in many possible directions, for example: encoding multi-robot communication through behaviour trees; simulation-based learning of behaviour tree structures; encoding logical policies as behaviour trees for improved interpretability; and deploying behaviour trees on physical robots.
This project would suit students with a strong background in Computer Science (particularly algorithms and data structures) and an interest in Robotics and Software Development.
Open to domestic and international students
Duration: flexible
Closing Date: When filled
For more information contact Dr Graeme Best: Graeme.Best@uts.edu.au
Multi-Robot Information Gathering with Hybrid Centralised-Decentralised Coordination
Supervisor
Dr Graeme Best
MME Centre/Institute
Robotics Institute
Degree Level
- Doctor of Philosophy
- Master of Engineering (Research)
Project Description
Robots working in outdoor environments are often tasked to gather information about the environment, such as by building a map, finding objects of interest, or studying how an environment evolves over time. Robots need to plan their motion to obtain high-value observations of the environment. Ideally, this is performed as a multi-robot system, where robots need to coordinate their actions to maximise the collective performance of the team.
There is broad scope to take this project in many possible directions. One idea is to study how robots can gracefully switch between centralised coordination (a common decision maker) and decentralised coordination (each robot plans for itself) as the communication network evolves. Related directions include developing: data representations for multi-robot communication; coalition formation algorithms; decentralised coordination algorithms for complex tasks; and deploying these ideas on physical multi-robot systems.
This project would suit students with a strong background in Computer Science (particularly algorithms and data structures) and an interest in Robotics and Software Development.
Open to domestic and international students
Duration: flexible
Closing Date: When filled
For more information contact Dr Graeme Best: Graeme.Best@uts.edu.au
Next-Generation Intelligent Robotic Mobility Aid for Vision Impaired People
Supervisor
Professor Sarath Kodagoda
Co-supervisors
Dr Marc Carmichael
Dr Karthick Thiyagarajan
MME Centre/Institute
Robotics Institute
Degree Level
- Doctor of Philosophy
Project Description
More than 253 million people worldwide are blind or have low vision, with over 575,000 in Australia. This research aims to develop the world's first functional robotic guide with advanced robotic sensing, navigation, control, machine learning-based decision making and user interfaces. Funded by the Australian Government and Guide Dogs Australia, several PhD positions are available. Together, the projects will generate novel theoretical breakthroughs, produce feasible prototypes, and provide new research that will transform the lives of visually impaired people.
A SPOT robot dog from Boston Dynamics will be used as the primary development and testing platform (https://www.bostondynamics.com/products/spot). Several PhD positions are available. PhD 1 will research real-time object classifications and semantic mapping in dynamic environments through a deep learning framework targeted at guide dog applications. PhD 2 will research robot navigation and obstacle avoidance framework incorporating dynamic objects and learned user behaviours. PhD 3 will research designing multimodal user interfaces for the robotic guide dog application.
This project would suit students with a background in robotics, mechatronics or related fields. Beneficial is experience in: object classification, semantic mapping, deep learning, robot navigation and obstacle avoidance, human-robot interaction, programming (especially python, C++, ROS).
Open to domestic and international students
Duration: flexible
Closing Date: When filled
For more information contact Prof Sarath Kodagoda: Sarath.Kodagoda@uts.edu.au
Centre for Advanced Manufacturing
Project Titles/Themes
- Industrial decarbonisation: Scope 3 advanced modelling for small- and medium-sized enterprises
- Cyber-physical production system approach for industrial decarbonisation
- Manufacturing System simulation for Life Cycle Assessment
- Hydrogen Storage and Transportation: Next-generation Energy Solution
- Advanced Systems Engineering for Australian SMEs
Industrial decarbonisation: Scope 3 advanced modelling for small- and medium-sized enterprises
Supervisor
Associate Professor Andrea Trianni
MME Centre/Institute
Centre for Advanced Manufacturing
Degree Level:
- Doctor of Philosophy
Project Description
Identifying and controlling the source of carbon emissions is crucial for manufacturing industry as part of their decarbonisation journey. Whilst Scope 1 and 2 are more easily attributable to a company, as a measure of its either direct or indirect GHG emissions, Scope 3 are rather difficult to measure, since they refer as the result of upstream and downstream activities from assets not directly controlled or owned by the company. However, such emissions, also often known as value chain emissions, represent the majority of an industry’s total GHG emissions. Whilst some preliminary examples of Scope 3 modelling are coming up, there is a large research gap in this area, particularly for smaller and less structured organisations. Hence, the project aims at developing innovative methodology to measure, account and benchmark Scope 3 emissions in industry, with particular emphasis on manufacturing small- and medium-sized enterprises, also exploring the potential from industry 4.0 solutions to reduce such emissions and improve industrial sustainability.
This project would suit industrial engineers with advanced skills in modelling and energy
Open to domestic and international students
Duration: 3.5 years
Closing Date: When filled
For more information, contact A/Prof Andrea Trianni: andrea.trianni@uts.edu.au
Cyber-physical production system approach for industrial decarbonisation
Supervisor
Associate Professor Andrea Trianni
MME Centre/Institute
Centre for Advanced Manufacturing
Degree Level:
- Doctor of Philosophy
Project Description
Planning and operating industrial processes should focus on crucial aspects for industrial decarbonisation such as energy and resource efficiency. For this reason, a specific simulation of the energy and resource flow could contribute to industry decarbonisation by providing a parametric digital twin of a physical production system. Such simulation could be integrated into the CPS for the simulation of real scenarios, thus allowing industrial decision-makers to better understand, control and optimise the production processes. The project aims at developing such decision-making tools to support industries in their decarbonisation journey and implement them in relevant industrial case studies.
This project would suit industrial engineers with advanced skills in modelling and energy efficiency as well as a particular interest around advanced manufacturing and industrial sustainability.
Open to domestic and international students
Duration: 3.5 years – 4 years
Closing Date: When filled
For more information, contact A/Prof Andrea Trianni: andrea.trianni@uts.edu.au
Manufacturing System simulation for Life Cycle Assessment
Supervisor
Associate Professor Andrea Trianni
MME Centre/Institute
Centre for Advanced Manufacturing
Degree Level:
- Doctor of Philosophy
Project Description
Combining environmental assessment (up to a full-scale deployment of LCA) and simulation has been already done in literature. However, the potential interactions between some crucial elements in manufacturing systems has not been investigated in detail. On the one hand, such connection would become quite relevant considering recent ISO 14001 deployment, which entails a life cycle approach, and overcome to some extent some crucial shortcomings of LCA (among others, a static approach). On the other hand, a more thorough knowledge of the impacts and the specific activities would support decision-making and, ultimately, contribute to mapping, controlling, and reducing Scope 1 emissions in industry. Starting from the above, the research project aims at developing and applying innovative methodologies for manufacturing system simulation combined with Life Cycle Assessment so to provide dynamic information for decision-makers on the impact of time-dependent manufacturing processes.
This project would suit industrial engineers with advanced skills in modelling and energy efficiency as well as a particular interest around advanced manufacturing and industrial sustainability.
Open to domestic and international students
Duration: 3 years
Closing Date: When filled
For more information, contact A/Prof Andrea Trianni: andrea.trianni@uts.edu.au
Supervisor
Dr Saidul Islam
MME Centre/Institute
Centre for Advanced Manufacturing
Degree Level:
- Doctor of Philosophy
Hydrogen Storage and Transportation: Next-generation Energy Solution
Project Description
Hydrogen is an important energy carrier, as it can be used to generate electricity via fuel cells, or combusted in internal combustion engines. To store hydrogen efficiently, it needs to be compressed or liquefied. However, compressing hydrogen to high pressures (e.g. 700 bar) can require large amounts of energy. Hydrogen can be transported in compressed or liquefied form via pipelines, trucks, or ships. However, transportation of compressed or liquefied hydrogen can be challenging due to the high pressures or low temperatures required. One potential solution to the hydrogen storage and transportation challenge is to develop solid-state hydrogen storage technologies. However, solid-state storage technologies are still in the early stages of development and require more research and development to become commercially viable. Therefore, this project aims to develop a cutting-edge method for hydrogen storage and transportation.
This project would suit students with advanced CAD and modelling skills. Advanced SolidWorks skill is mandatory for this project.
Open to domestic students
Duration: 3 - 3.5 years
Closing Date: When filled
For more information, contact Dr Saidul Islam: MohammadSaidul.Islam@uts.edu.au
Advanced Systems Engineering for Australian SMEs
Supervisor
Dr Matthias Guertler
MME Centre/Institute
Centre for Advanced Manufacturing
School of Mechanical & Mechatronic Engineering
Degree Level:
- Doctor of Philosophy
Project Description
Systems engineering allows for the systematic and successful development and deployment of complex multidisciplinary systems/products, taking into account the requirements and stakeholder needs from across the entire system lifecycle, such as recycling. Aside from building a deep problem understanding and systematically splitting a complex problem into more tangible parts, it supports a coordinated collaboration of interdisciplinary teams. This is particularly important for aviation and space systems as well as autonomous and IoT systems, ranging from robotics to manufacturing systems. Along with being a core approach at NASA for decades, it has therefore been used by various industries like automotive and aerospace around the world. However, systems engineering processes and tools can be perceived as complicated and rigid, especially by small and medium-sized enterprises (SMEs). Limited personnel and financial resources can be a challenge for building systems engineering skills and implement its processes and tools. However, often, a full 100% suite of processes and tools might not be required. Instead, a reduced, flexible, and tailored approach would be sufficient.
The goal of this PhD project is to analyse the current state and need of Australian SMEs concerning product development support with a focus on systems engineering. Based on this, strategies and measures shall be developed of how to adjust and tailor systems engineering processes and tools for SMEs. Subsequently, these strategies and measures shall be applied and evaluated with selected SMEs.
This project would suit students who have experience in developing mechanical or mechatronic systems and like to deepen their expertise through learning – and enhancing – a powerful state-of-the-art product development approach.
Open to domestic and international students
Duration: 3.5 years (flexible)
Closing Date: When filled
For more information, contact Dr Matthias Guertler: matthias.guertler@uts.edu.au
Centre for Audio, Acoustics and Vibration
Project Titles/Themes
Design and Control of Microelectromechanical Systems for High-Performance Sensing Applications
Supervisor
Dr Michael Ruppert
MME Centre/Institute
Centre for Audio, Acoustics and Vibration
Centre for Advanced Manufacturing
School of Mechanical & Mechatronic Engineering
Degree Level:
- Doctor of Philosophy
Project Description
Microelectromechanical Systems (MEMS) have been identified as one of the most promising technologies of the 21st century. These precision micro mechatronic systems have the potential to revolutionize both industrial and consumer products by combining silicon-based microelectronics with micromachining technology. MEMS devices are fabricated using integrated circuit (IC) batch processing techniques and can range in size from a few micrometers to millimetres. The interdisciplinary nature of MEMS utilizes design, engineering and manufacturing expertise from a wide range of technical areas including integrated circuit fabrication technology, mechanical engineering, materials science, electrical engineering, control engineering, optics and instrumentation. MEMS devices can be found in a variety of systems ranging across automotive, medical, electronic, nanometrology, communication and defence applications.
Several PhD research topics are available in this area to develop novel versatile, high-performance microsensor platforms with an emphasis on nanometrology, that is, measurement techniques at the nanoscale level or down to the length scale of a single atom. A major challenge in this field is to develop new technology to meet the needs of next-generation advanced manufacturing such as of nanomaterials and semiconductors. Available PhD projects will include the computer aided design, finite element simulation, and fabrication of MEMS devices in combination with electronic read-out circuit design, instrumentation, and packaging. The successful PhD candidate is expected to develop an expert knowledge in microelectromechanical systems , low-noise analog instrumentation, controller implementations, and nanometrology with extensive laboratory experience.
This project would suit students with a strong background in mechanical design, modelling and simulation and / or electronic circuit design with a good understanding of system dynamics and control. The project would suit students with an interest in precision mechatronic systems and emerging challenges in micro- and nanotechnology.
Open to domestic and international students
Duration: 3.5 years
Closing Date: When filled
For more information, contact Dr Michael Ruppert: michael.ruppert@uts.edu.au