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New PhD Researcher, Justin Botha

Let’s introduce Justin Botha, our newest team member. Justin is a PhD researcher at QUT (Queensland University of Technology), actively involved in the Human-Robot-Interaction program and the Interactive (and Collaborative) Robot Programming using Language project.

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. We are pleased to welcome Justin to the team and anticipate his valuable contributions. Join us in welcoming Justin aboard!

Welcome Justin!

PhD Project Introductions

Collaboration and sharing of information are vital for the success of our Centre. To support this, we ask our PhD Researchers to give a brief introduction to their projects within the initial 6 months.

During our latest seminar, QUT (Queensland University of Technology)‘s Phuong Anh TranJasper Vermeulen and Yuan Liu provided an outline of their projects’ objectives, methodology, and anticipated outcomes.

As they continue their research, we’ll keep you posted on their progress. Meanwhile, you can learn more about their research updates HERE.

ARTICLE: Cobots in manufacturing: Good for skill shortages and much more.

Written by Research Program Co-Lead Professor Greg Hearn and PhD Candidate Nisar Ahmed Channa both from the Human Robot Workforce research program in the Centre.  

In this era of rapidly evolving technology landscape, almost every industry sector needs to keep pace with technological advancements to prosper and remain competitive. However, many companies struggle to develop or even adopt innovations in technologies, processes, or business models. COVID-19 is one recent example where manufacturing companies found it extremely challenging to generate an innovative response to address labor shortages caused by lockdowns and movement restrictions across many countries. As a result, many production units of large as well as small to medium manufacturing companies shut down for significant time periods. This negatively affected global supply chains in many other sectors because manufacturing industries provide input in the form of usable goods and services to many other industries. Soon after the global economic crises, the manufacturing companies were facing issues like increasing production costs caused by unavailability of raw material and increased labour costs. Covid-19 pandemic further fuelled these issues due to disruptions in global supply chains and restricted movement of human workers. Even after the pandemic, various countries are still facing issues like increased labour costs, and shortages of skilled labour. Resultantly, companies are now investing huge financial resources to future proof their manufacturing potential and reduce input and increase output.

One of the innovative solutions to these labor and skills shortages on which academics and industry experts are working is the adoption of collaborative robots (Cobots) in manufacturing. A Cobot is a special kind of robot, with context awareness, which can safely share a workspace with other Cobots or with human operators. Recent research suggests that Cobots can be used as alternatives to skilled human workers and thus can supplement the shortage of workers across the industries. For instance, to cope with labour shortages caused by pandemic and to meet increased demand, manufacturing companies in North America spent around 2 billion USD in 2021 to acquire 40,000 robots[i],[ii],[iii]. Similarly, rising labour costs, and an aging workforce, has led to an increase in the demand for Cobots in the automobile sectors of Europe and the Asia–Pacific region iii.

Some labour economists believe that the introduction of technologies like artificial intelligence (AI) and robots increases production and efficiency in manufacturing through the displacement of jobs traditionally being performed by human workers. However, under certain conditions, these technologies can create new jobs and upskill other jobs across the ecosystem of the related suppliers and services providers.

In line with the priorities for Australian manufacturing formulated by the Australian Advanced Manufacturing Growth Centre[iv], we argue Cobots could be “creatively productive” for Australian manufacturing not only because of their potential to reduce production cost efficiencies but also to enhance value differentiation, and potentially open up new revenue segments including through export[v]. Efficiencies can be achieved through optimisation of human-robot workflow design; accelerating workforce acceptance of robotic driven process efficiencies; reducing human errors in automation documentation; and by reducing downtime through enhanced work safety.  Value differentiation can be achieved by integration of Cobots in product design for rapid prototyping; by developing autonomous systems of quality assurance and better data analytics as value adding services; by improving capabilities for just-in-time and mass customisation products in existing markets; and by upskilling the manufacturing workforce for innovation leadership which in itself is a value differentiator. The fact that Cobots are designed to work alongside and close to people to perform their jobs and responsibilities can help companies to integrate and digitalise their business operations without compromising on lacking human aspects of the job. In many respects, Cobots are the hardware equivalent of augmented intelligence, rather than replacing people with autonomous equivalents. Cobots can supplement and improve human skills with super-strength, accuracy, and data capabilities, allowing them to perform more and add more value to the production process and to final product itself. It aids in creating strategic business value and improves efficiency, resulting in better, quicker delivery of products to customers in market.

[i] North American companies send in the robots, even as productivity slumps | Reuters

[ii] Robots marched on in 2021, with record orders by North American firms | Reuters

[iii] Rise of The Cobots in Automotive Manufacturing | GEP

[iv] https://www.amgc.org.au/our-purpose/about-advanced-manufacturing/

[v] Microsoft Word – Hearn et al ACRA Final Submission.docx (linklings.net)

ARTICLE: Can we Unlock the Potential of Collaborative Robots?

Written by Dr Marc Carmichael and Louis Fernandez from the Australian Cobotics Centre.

Collaborative robots, or cobots for short, have gained significant attention in recent years due to their potential to work in close proximity and collaboration with humans. However, despite their name, there seems to be a lack of actual collaboration between humans and cobots in many, if not most, industrial settings.

The Australian Cobotics Centre aims to transform the Australian manufacturing industry through the deployment of collaborative robots, and in a recent webinar we discussed how significant benefits may be possible if more sophisticated forms of collaboration between humans and cobots can be practically achieved.

In this article we discuss this, starting with the basics of cobots, exploring the untapped potential of cobot-human collaboration, and how we hope to develop new ways of enabling humans and cobots to collaborate.

Defining Cobots and Industrial Robots:

Before we talk about the untapped potential of cobot-human collaboration, let’s start by understanding the basic differences between cobots and regular industrial robot arms.

Industrial robot arms are normally big, heavy machines you might see in factories or other environments that have repetitive and predictable jobs. Industrial robots are great at lifting heavy things quickly and accurately. However, this is also what makes them dangerous around people, so they need to be kept away from them.

On the other hand, cobots are much smaller and lighter. They also have technology that lets them ‘feel’ their surroundings. These functionalities allow them to work alongside humans. On top of that, they’re easier to program than industrial robots. This allows them to be quickly put to work on different tasks and makes them good for flexible jobs.

The Current State of Cobot Collaboration:

Even though cobots are capable of working beside people, they don’t very often really work with people. Feedback from experts and users, as well as research literature, have observed that cobots are being used more like traditional industrial robots. For example, cobots are often used in pick and place or palletising jobs. These applications look much like how industrial robots work, except cobots don’t need the protective cage around them. This raises the question: “Are we really using cobots to their full potential?”

Don’t get me wrong, using cobots as cageless industrial robots has great advantages. Not needing a cage means you have more space on your shop floor for other equipment, and you spend less time during the installation process. In addition, cobots are generally easier and faster to program compared to industrial robots. For example, cobots can be programmed by physically grabbing and moving their arm to show them where to go. This easy form of programming allows cobots to be easily set up and deployed, a benefit for small businesses getting into automation. Plus, cobots are getting better, with some having more reach and strength to handle different jobs. As they improve, we might see cobots and robots becoming harder to tell apart, and using cobots like cageless industrial robots might become common.

However, using cobots like industrial robots doesn’t make the most of what they can do. We should explore the challenges and opportunities of making cobot-human collaboration better.

Defining Levels of Human-Robot Collaboration:

Before we continue, it is important to define collaboration in the context of cobots. What collaboration means depends on the discipline, and terms are often used inconsistently or interchangeably. A classification that is becoming increasingly common, and which we personally like, is the following:

Level 0: Cell – this is the traditional approach used in industrial robots where humans are isolated from the robot, often by physical caging or fences.

Level 1: Co-existence – the human and cobot share the workspace, but work together on a task in a sequential fashion. For example, a cobot performs a packing task, with a human only entering the workspace to restock items. Sensors such as a safety area scanner are used to slow/stop the cobot when someone is in the vicinity.

Level 2: Co-operation – the human and cobot operate in shared space, with the worker guiding or influencing cobot operation via inputs (e.g. force, speech, gesture, etc). Cobot may adapt its motion based on human measurements.

Level 3: Collaboration – the human and cobot cooperate on joint task. Cobot learns and adapts by observing humans, to achieve a dynamic and supportive collaboration. Human and cobot are responsive to each other in a mutually beneficial manner, where both parties actively contribute to the task at hand.

Although it is sometimes difficult to define, these definitions can help distinguish different levels of interaction and collaboration between cobots and humans.

Exploring the Potential Gains and Barriers to Collaboration:

We would consider most cobot use cases to be Level 1 collaboration, where other than the cobot adapting its pre-programmed routine based on the presence of a human, there is next-to-no real collaboration between the two. To rephrase the previous question that we raised: “what are we missing out on by not going after Level 2 and Level 3 collaboration?”

There are some interesting and compelling proof-of-concepts by robotics researchers that demonstrate the potential to be achieved, See Further Reading for some examples. One study estimated a potential reduction in task completion time of up to 20%, suggesting significant benefits in productivity can be unlocked. Unfortunately, there are relatively few examples of high-level collaboration that have made their way to practical use.

In our program (Human-Robot Interaction) at the Australian Cobotics Centre, our goal is to increase the scope of genuine collaboration. Our efforts are focused on novel interaction approaches using multi-sensory interfaces, gesture control devices and augmented reality which can reduce training costs, enable rapid prototyping, and make robots safer and easy to use in production tasks.

It is our belief that addressing these challenges will lead to new methodologies for enabling rich and beneficial forms of human-robot collaboration. Combined with the work of our colleagues at the Australian Cobotics Centre whose programs are addressing technical, social, and organizational challenges, we are looking forward to sharing the outcomes we achieve and are excited about the future of cobotics.

Further reading:

Michaelis, J. E., Siebert-Evenstone, A., Shaffer, D. W., & Mutlu, B. (2020). Collaborative or simply uncaged? understanding human-cobot interactions in automation. Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. https://doi.org/10.1145/3313831.3376547

Guertler, M., Tomidei, L., Sick, N., Carmichael, M., Paul, G., Wambsganss, A., Hernandez Moreno, V., & Hussain, S. (2023). When is a robot a cobot? moving beyond manufacturing and arm-based cobot manipulators. Proceedings of the Design Society, 3, 3889-3898. https://doi.org/10.1017/pds.2023.390

Kopp, T., Baumgartner, M., & Kinkel, S. (2020). Success factors for introducing industrial human-robot interaction in practice: an empirically driven framework. The International Journal of Advanced Manufacturing Technology, 112(3-4), 685-704. https://doi.org/10.1007/s00170-020-06398-0

Male, J. and Martinez-Hernandez, U. (2021). Collaborative architecture for human-robot assembly tasks using multimodal sensors. 2021 20th International Conference on Advanced Robotics (ICAR). https://doi.org/10.1109/icar53236.2021.9659382

Carmichael, M. G., Aldini, S., Khonasty, R., Tran, A., Reeks, C., Liu, D., … & Dissanayake, G. (2019). The ANBOT: an intelligent robotic co-worker for industrial abrasive blasting. 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). https://doi.org/10.1109/iros40897.2019.8967993

Zhuang, Z., Ben-Shabat, Y., Zhang, J., Gould, S., & Mahony, R. (2022). Goferbot: a visual guided human-robot collaborative assembly system. 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). https://doi.org/10.1109/iros47612.2022.9981122

PhD Project Introductions

Cooperation and sharing of information are vital for the success of our Center. To support this, we ask our PhD Researchers to give a brief introduction to their projects within the initial 6 months.

During our latest seminar, Akash Hettiarachchi and Louis Fernandez provided an outline of their projects’ objectives, methodology, and anticipated outcomes.

As they continue their research, we’ll keep you posted on their progress. Meanwhile, you can learn more about their research updates HERE.

          

New PhD Researcher, Eleonora Zodo

Let’s introduce Eleonora Zodo, our newest team member. Eleonora is a PhD researcher at QUT (Queensland University of Technology), actively involved in the Human-Robot Interaction program.

This program focuses on critical aspects of human interaction with robotic systems, including mutual awareness, visualising robotic intentions, and developing rapid collaborative robotic solutions. The program is built on understanding collaborative work patterns and specific task domains and aims to create practical Human-Robot Collaboration (HRC) solutions and support industry adoption.

Eleonora’s research project centers on establishing safe and efficient #HumanRobotcollaboration. The work has practical implications, from manufacturing to operating theaters, and involves partners like Cook Medical and Stryker.

We are pleased to welcome Eleonora to the team and anticipate her valuable contributions. Join us in welcoming Eleonora aboard!

Welcome Eleonora!

Meet our E.P.I.C. Researcher, Jagannatha Pyaraka

Jagannatha Pyaraka is a PhD researcher based at Swinburne and his project is part of the Biomimic Cobots Program at the Australian Cobotics Centre.

He is excited to work in the field of Robotics/Automation that serves and inspires society in leading a simple and better quality of life.

We interviewed Jagannatha recently to find out more about why he does what he does.

  • Tell us a bit about yourself and your research with the Centre?

I finished my Bachelor of Engineering (Electrical and Electronics) degree from GITAM University in 2018 and master’s in professional engineering (Robotics and Mechatronics) in 2021 from Swinburne University of Technology. Following the undergraduate degree, I worked as a Senior QA Automation Engineer at NTT DATA Services. Now I am pursuing my PhD in field of robotics.

My research under ACC is centered on developing a learning framework for cobots through biomimicry digital twinning. I am pioneering a learning from demonstration methodology for collaborative robots using digital twin technology. This project addresses several critical challenges: enabling robots to adapt to varied operational conditions for a given task, facilitating their learning of diverse tasks in a manner analogous to human learning, and significantly reducing the necessity for human intervention in the robot’s learning process. I am confident that the advancements from this research will pave the way for more intuitive robot-human interactions, enabling robots to understand tasks more holistically and perform them as instinctively as humans.

  • Why did you decide to be a part of the Australian Cobotics Centre?

As a postgraduate, my decision to become a part of the Australian Cobotics Centre is fuelled by the extraordinary prospects it offers. The Centre’s vision to revolutionize the Australian manufacturing industry through collaborative robotics resonates deeply with my desire to contribute to impactful change. The opportunity to enhance manufacturing efficiency, and prioritize safety aligns perfectly with my aspirations for a meaningful and dynamic career.

The Centre’s commitment to cutting-edge research and innovation is particularly enticing. Being at the forefront of technological advancements in collaborative robotics would not only allow me to engage with groundbreaking ideas but also give me the chance to be part of a transformative movement. The interdisciplinary approach embraced by the Centre is equally appealing, as it would enable me to explore diverse fields, fostering a versatile skill set that’s crucial in today’s ever-evolving landscape.

The prospect of industry collaboration is another significant factor in my decision. The Centre’s connections with industry partners and its dedication to training researchers and engineers with practical skills means I would be well-prepared to transition seamlessly into the workforce. Moreover, the people-centric and inclusive environment the Centre promotes assures me of a supportive community where I can grow both personally and professionally. Overall, ACC offers a unique chance to merge my academic pursuits with real-world impact, making it an inspiring destination to embark on my journey toward a fulfilling career.

  • What project are you most proud of throughout your career and why?

During my final semester, I undertook an internship at a company that exposed me to a real-world challenge in the realm of autonomous vehicles. To address this issue, I meticulously designed and built an Arduino-based data logger capable of capturing serial data communication between two subsystems. My contribution encompassed both hardware and software elements, resulting in a robust end-to-end system. The finalized product was a turnkey solution that industry professionals could seamlessly utilize for similar scenarios.

  • What do you hope the long-term impact of your work will be?

The goal of my work is to make robots work more like humans. By improving how they learn and interact, we hope to make human-robot teamwork smoother. In the long run, this means robots could do tasks just as naturally as humans, changing the way we work together in many fields.

  • Aside from your research, what topic could you give an hour-long presentation on with little to no preparation?

Autonomous systems in Everyday Life

ARTICLE: Human-Robot Collaboration through Augmented Reality

Written by Dr Alan Burden, Postdoctoral Research Fellow from the Australian Cobotics Centre.

In previous articles, we delved into socio-technical systems (STS) and highlighted the importance of spatial design in shared human-robot environments. As we continue this exploration, this article will focus on technologies that show immense potential in improving the harmony between humans and cobotic systems. Our spotlight will be on augmented reality (AR), a technology poised to make human-cobot interactions more intuitive, efficient, and enjoyable. 

AR is a part of the ‘reality technologies’, often grouped under the umbrella term of extended reality (XR), which also includes virtual reality (VR) and mixed reality (MR). These technologies merge the physical and digital worlds, creating innovative environments where humans and machines interact. AR stands out because it doesn’t replace our reality, as with VR, but instead enhances our existing environment by overlaying digital information.   

AR enhances our perception of the physical world by overlaying images, sounds, or other data, onto our physical environment. In cobotics, AR could serve as a communication bridge between humans and robots, facilitating a more intuitive and efficient collaboration. For example, AR can visually guide a human worker in a manufacturing plant, showing them how to operate a machine or assemble a product with the help of a robot. Similarly, AR could provide surgeons with real-time data during a robotic assistant procedure in a healthcare setting. AR offers opportunities to improve the efficiency of the task at hand and enhance the safety and effectiveness of human-robot collaboration. 

The potential of AR extends beyond communication. It also plays a crucial role in spatial design for shared human-robot spaces. AR can help visualise the optimal arrangement of a workspace, considering the movement patterns and tasks of both humans and robots, which could lead to safer, more efficient, and intuitive shared spaces. For example, in a warehouse, AR can help design a layout that minimises the risk of accidents between human workers and autonomous robots. By visualising the robots’ paths and highlighting potential danger zones, AR can contribute to a safer and more productive environment. 

However, the integration of AR into cobotics is not without challenges. Technical limitations, such as AR devices’ accuracy and reliability, can affect AR applications’ effectiveness. User acceptance is another critical factor. While AR can make human-robot collaboration more intuitive, users must adapt to a new way of working and interacting with technology. Ethical considerations, such as privacy and data security, must also be addressed. 

Despite these challenges, AR presents exciting opportunities for the future of cobotics and STS. It can make human-robot collaboration more accessible and user-friendly, opening new possibilities for automation in various industries. Moreover, as AR technology evolves, we can expect even more innovative applications that will further enhance human-robot collaboration. 

AR is a powerful tool that can significantly enhance human-robot collaboration in STS. By improving communication and contributing to the design of safer and more efficient shared spaces, AR can help us harness the full potential of cobotics. As we navigate the intersection of humans and technology, embracing tools like AR will be crucial in creating a harmonious and efficient future for human-robot collaboration. The journey towards this future is filled with challenges and exciting opportunities. As we continue to explore and innovate, we can look forward to a world where humans and robots work together seamlessly, each enhancing the capabilities of the other. 

TAFE Queensland Explores QUT Centre for Robotics’ Industry Collaborations

Yesterday, TAFE Queensland’s representatives visited the QUT Centre for Robotics (QCR) at the Queensland University of Technology’s Gardens Point campus for an informative tour. Led by QCR PhD researcher Somayeh Hussaini, the delegation, including Shawn O’Sullivan, Mark Robertson, and Richard Auld, got a glimpse of the center’s ongoing industry collaborations and its impact on research.

The tour focused on showcasing the joint projects between QCR and various industries, highlighting the practical applications and benefits of their research efforts. The Australian Cobotics Centre PhD researchers, Jacqueline Greentree, Nisar Ahmed Channa, and Jagannatha Pyaraka, along with Postdoctoral Research Fellow Dr. Melinda Laundon, also participated in the tour, offering their expertise and insights.

        

In a recent webinar, Dr. Melinda Laundon and Shawn O’Sullivan engaged in a discussion on how education and training systems can support a digitally-enabled workforce in the Australian manufacturing sector. The seminar emphasised the importance of preparing graduates with relevant skills to meet the demands of emerging technologies in the industry. Additionally, they shared the latest research findings from the Australian Cobotics Centre Human-Robot Workforce Program, led by Dr. Melinda Laundon, Professor Paula McDonald, and Jacqueline Greentree.

Watch the webinar via the link – (2) Supporting the digitally-enabled manufacturing workforce: the role of education and training systems – YouTube

Congratulations to our PhD researcher, Jagannatha Pyaraka

Congratulations to our PhD researcher from Swinburne University of TechnologyJagannatha Charjee Pyaraka who passed his confirmation of candidature this week!

The COC Panel was chaired by A/Prof Chris McCarthy with Dr Michelle Dunn and Dr Andrew Ang as other panel members.
Jagan’s supervisors (A/Prof Mats Isaksson, Dr John McCormick & Dr Fouad (Fred) Sukkar) were also in attendance.

More information about his project can be found on our website: https://lnkd.in/g8ckp8bQ.