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New PhD Researcher, James Dwyer

Welcome to our newest PhD Researcher, James Dwyer based at QUT (Queensland University of Technology)! James is joining our Human Robot Interaction program and is supervised by Jared Donovan. His PhD project is entitled: “Human Robotic Interaction prototyping toolkit”.

Interaction 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 physical and simulated robotic systems to explore, develop and test new processes and work routines. The project will enable designers, engineers, and end-users to work together to improve the future of human-robotic interaction.

Read more about the program.

Robotic Vision Summer School: An Overview from our PhD Researchers

The Robotics Vision Summer School (RVSS) is an annual event that brings together researchers and students from all over the world to learn about the latest developments in vision-based control methods for robotics. The program features a series of lectures, tutorials, and hands-on projects designed to teach participants the fundamentals of robot vision, spatial awareness, and visual learning.

The program is an excellent opportunity for students to network with other researchers, learn from leading experts in the field, and gain valuable hands-on experience with cutting-edge technology.  Two of our PhD researchers, Jagannatha Pyaraka and Nadimul Haque attended the 2023 RVSS and shared some highlights from their experiences.

What were some of the topics covered during the Robotic Vision Summer School, and which were the most interesting to you?

Jagannatha: The most interesting topics was the vision & deep learning. Deep dive on “How the way we see is different from what a robot looks and perceives” and “how to train a robot to finish a task done from that vision” were very valuable.

Nadimul: RVSS covered mostly vision based control methods. There were segments on spatial awareness, visual learning, reinforcement learning, and robot vision. To me, I felt that robot vision that covered camera calibration, visual servoing were the most interesting topics because they were quite new to me. Visual learning was also very interesting because it covered a lot of theoretical and philosophical ideas regarding AI as well.

What were some of the hands-on activities or projects that you worked on during the summer school, and what did you learn from them?

Jagannatha: On day 2 we were given a RC car and brief about the outcome to be delivered by the end of week for a final competition. The task was to present an autonomous driving car that detects turns and steers accordingly completing a lap in shortest time possible. As I was completely new to deep learning, this kind of gave me a brief idea on robot data training, prediction and optimisation.

Nadimul: During the summer school, we had to do a project that involved controlling a robot with visual data. Although the problem itself was trivial, it highlighted the importance of spatial awareness and uncertainty modelling, rather than simply learning from raw visual data.

What were some of the highlights of the program for you?

Jagannatha:  Learning (Deep dive sessions*): One of the key highlights is the opportunity to learning from domain experts. Insight on latest advances in robotic vision, including techniques and technologies to improve robot perception and decision making.

Hands-on-experience: Allowing us to work on RC car has given an invaluable experience in terms of implementing our learning to real-world setting.

Networking: During breaks and other free time I was able to network with fellow researchers, field experts which helped me to build relations that can be beneficial in near future. I did discuss my research with them and got to know a list of important things to consider while solving my research problem.

Exposure to research: I was able to get good exposure and relate with common problems faced in current research. This was a good opportunity to learn about on-going projects and emerging trends.

Nadimul:  The highlights of the program are surely, the deep dive lectures given by Richard Hartey, Hanna Kurniawati and Miaomiao Liu. An hour and a half of their talks didn’t only comprise of their current and recent works, but showed a glimpse of their thought process, which I think is much, much more important for an HDR student to grasp. Of course, the lectures given by Peter Corke, Simon Lucey and others were also quite interesting. Being close to such influential people and hearing from them not only as tutors, but also as humans, was a great privilege.

What did you learn that you think will be most useful in your future work or studies?

Jagannatha: The lectures /deep dives on below topics are most useful for my future work are:

  • Deep learning – Various algorithms for decision making, pattern recognition, optimisation
  • Object recognition and tracking – Detecting and tracking important objects in given environment
  • Fusion of sensors
  • Spatial awareness
  • Human robot interaction – Better ways in which robots can communicate and interact with humans which helps in collaborative tasks

Nadimul: I think the biggest thing I learnt from RVSS is to take things step by step and find the time to sit back even in the busiest time, to think about whatever idea I might have in a broader perspective. The lectures, especially the deep dives helped me to gather my thoughts and ideas about my PhD project, which I think will shape my future works.

Apart from the amazing program, what else did you get up to?

Jagannatha: Almost all the evenings we had fun activities – which included networking with fellow researchers, bon-fire, going to the beach, game night, panel discussion – In which we were allowed to ask any questions to the experts such as their experience, thoughts about future developments, failures, and career advice.

Nadimul: RVSS hosted students from different universities, both from Australia and abroad. Most of them were more experienced, and in a more advanced stage in their PhDs (6-10 months in). It was a pleasure to talk and learn about their journeys, how they fixed their PhD topic and ideas etc. It was a great experience in meeting people from different cultures and backgrounds and learn from them as well.


ICRA 2023 – Accepted Papers from The Australian Cobotics Centre

Australian Cobotics Centre researchers have three papers accepted for publication at the upcoming International Conference on Robotics and Automation (ICRA) 2023 in London. ICRA is the IEEE Robotics and Automation Society’s flagship conference and the premier international forum for robotics researchers to present and discuss their work.

Postdoctoral Research Fellow, Dr Fouad Sukkar gave is a brief summary of two of the papers appearing at the conference mid this year.

Guided Learning from Demonstration for Robust Transferability”, by Fouad Sukkar, Victor Hernandez Moreno, Teresa Vidal-Calleja and Jochen Deuse, contributes to the idea of humans teaching robots how to carry out tasks in the real world. A common approach is to physically move the robot around and record its motions. However, this can be inconvenient if the robot is already busy doing work and even dangerous/ not possible in the case of large industrial arms. Ideally, we should be able to demonstrate the task more naturally using the original tool, such as a welder, without the physical robot present. This is where the proposed guided learning from demonstration (LFD) framework comes in handy. It visually displays regions in the workspace that the robot is capable of moving within to the demonstrator. That way the user can be confident that the robot will be able to execute the demonstrated task and avoid having to carry out repeated trial and error. To validate their method, a user study was carried out which involved users teaching a collaborative robot (cobot) how to carry out a welding task with obstacles in the environment. Results showed that with the visual guidance users were always able to achieve a successful execution of the task on the robot in comparison to only 44% of the time without it. While the framework is in a promising proof of concept state, the authors strongly believe this idea will be important for industry as they adopt more flexible methods for manufacturing. As for future work, they are currently working towards testing their framework in real world applications and exploring different guidance mediums such augmented reality and haptic feedback. A preprint for the paper can be found here:

“Optimal Workpiece Placement Based on Robot Reach, Manipulability and Joint Torques”, by Baris Balci, Jared Donovan and Peter Corke, looks at how to best place a workpiece for a robot to physically interact with. This is particularly important for cobots, such as the Universal Robot’s UR arms, which are designed to be safe around humans. Cobots are sensitive to external forces in order to be safe around people, however, this sensitivity complicates cobots’ physical interaction with objects for manufacturing purposes. The arm will deviate away from where you tell it to go due to the external forces that are required for the manufacturing processes. What the authors in the paper show is that depending on how you place a workpiece, it is possible to increase cobots’ physical interaction performance. They present a novel method for choosing this placement and demonstrate it works effectively in a simulated surface finishing application for a few different objects with interesting surface geometries.

New PhD Researcher, Munia Ahamed

Our Quality Assurance and Compliance research program has a new PhD Researcher, Munia Ahamed.

Munia is supervised by Lee Clemon and is based at UTS Tech Lab.

Her PhD project is entitled: “Human Factors in Cobot era to Support Quality Assurance and Reliability: An exploratory Multiple Case Study in Australian Manufacturing Industry.”

This Project will capture the inspection points, reliability, and interpreted information needed for monitoring collaborative robotic activity. This activity is captured both through the collaborative robots in the interaction, automation processes up and downstream as well as through additional sensors.

This Project will focus on the integration and documentation of this data for regulatory and quality assurance activities.

Find out more about Munia here: Munia Ahamed » Australian Cobotics Centre | ARC funded ITTC for Collaborative Robotics in Advanced Manufacturing

2023 Association of Industrial Relations Academics of Australia and New Zealand (AIRAANZ) Conference

On 8th February, Postdoctoral Research Fellow, Dr Melinda Laundon presented on Cobots at the Association of Industrial Relations Academics of Australia and New Zealand (AIRAANZ)AIRAANZ2023 conference hosted by James Cook University at Magnetic Island.

The theme of the conference is: ‘Labour and Value’ and Melinda’s abstract was entitled, “Cobots and decent work”

Read the full abstract here:


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Jobs Queensland and Australian Cobotics Centre Report Launch

On Tuesday 7th February, Jobs Queensland and the Australian Cobotics Centre officially launched their joint report, Advancing Manufacturing: Exploring the human element of the journey.

The report illustrates the opportunities and challenges faced by manufacturing organisations in Queensland as they progress toward Industry 4.0, with a focus on the people in the frontline of the change. The report also includes case studies of two organisations, Watkins Steel and our industry partner, B&R Enclosures. The research was completed by our research program leads, Dr Penny Williams, Prof Greg Hearn, research Associate, Dr Rio Rodrigues PhD and Postdoctoral Research Fellow, Dr Melinda Laundon.

The event was held at our Industry partner and key organisation in advancing Advanced Manufacturing in Queensland, ARM Hub (Advanced Robotics for Manufacturing) and included

Key takeaways included:

? Implementing new technology doesn’t work when people haven’t been involved in the development, design and implementation.
? Multidisciplinary working is vital to ensure holistic solutions that work across all aspects of the business.
? The skills workers are developing are transferrable and can be used across many different industries.
? For Australia to be globally competitive we need to embrace advanced manufacturing.

To learn more, access the reports here: Advancing Manufacturing Skills project | Jobs Queensland

New PhD Researcher – Fikre Gebremeskel

Welcome to our newest PhD Researcher, Fikre Gebremeskel based at UTS Tech Lab!

Fikre is joining our Designing Socio-Technical Robotic Systems program and is supervised by Matthias Guertler.

His PhD project is entitled: “Design Factors: Integrated Design of Collaborative Robots, Products, and Manufacturing Environment.”

The ultimate goal of this PhD project is to support companies in implementing collaborative robots (cobots). A key focus is on exploring socio-technical interdependencies between cobot, products to be manipulated, and the manufacturing workplaces. This will help to identify how products and workplaces affect the choice and design of a cobot, and how those need to be adjusted to best accommodate the new cobot.

We look forward to sharing the progress of Fikre’s research!

Read more about the program.