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6 Reasons Why We Need a Prototyping Toolkit for Designing Human-Robot Collaboration

Written by Postdoctoral Research Fellow, Dr Stine S Johansen and PhD Researcher, James Dwyer

In this short article, we will share 6 benefits of having a prototyping toolkit for designing human-robot collaboration (HRC). We will lift the curtain on our planned activities to work towards this in Program 2 of the Australian Cobotics Centre.

What type of human-robot collaboration are we talking about?

The Australian Cobotics Centre focuses on cobots in manufacturing settings. In these settings, robots are most often big and locked away in cages for safety reasons. They are useful for highly defined and repeatable tasks that require strength. In contrast, cobots are typically smaller and allow for people to safely carry out a task by handing over items to the robot or even by physically handling the robot.

Cobots address an increasing need for more adaptable robotic systems for customised and bespoke products. These types of products still require people in the manufacturing line to accommodate changes from product to product.

So, what could a prototyping toolkit look like?

Imagine a toolbox with screwdrivers, a hammer, cutters, etc. Similar to that, we already have tools in our design toolbox that work at a generic level or are appropriated to suit particular problems. But a toolkit for prototyping human-robot collaboration is still left for us to investigate. In Program 2, James Dwyer (PhD student) will contribute to our knowledge about how different prototyping tools can facilitate design processes of HRC. The goal is to develop a practical and affordable toolkit that can be used to enable designers, engineers, and end-users to work together towards human-robot collaboration in manufacturing settings and beyond.

What are the benefits of having a prototyping toolkit?

Knowing how a cobot can fit into an existing or new manufacturing setting requires substantial research. What if we had a way to make that process easier and more efficient for designers and clients as well as more accommodating for the final end-users of the cobot? This is the broad aim of a HRC prototyping toolkit. Here are 6 concrete benefits that we aim to support through our work in Program 2.

1) Accessible end-user engagement

Manufacturers often lack the expertise to define how a cobot could be used. They are, however, experts in their respective domain. Domain knowledge is not always something that can be documented in written reports. It is also the tacit knowledge that workers build through years of experience. A prototyping toolkit can enable that knowledge to play a role very early in the design and development process by lowering the currently high technical barriers to understand how a robot works. In Program 2, we rely on principles from participatory design which is a design practice to produce tangible outcomes together with end-users.

2) Cost and time efficiency

Facilitating a cobot integration project can require substantial costs and time which makes it non-viable for some manufacturers. The hardware investments require committing to a particular setup, but there are risks associated with such investments if feasibility of the concept has not been investigated early on. Therefore, it will be beneficial to have prototyping tools to conduct such investigations without the necessity of actual hardware. Prototyping tools can furthermore allow for quick and cheap iterations. Subsequently, there is a need for tools that facilitate the transition from early concepts to implementation and testing.

3) Flexibility

Given the opportunity for cobots to assist in manufacturing of customised products, there is a high need for flexible solutions. Crucial to realising flexibility is the establishment of design processes that bridge the gap between early stage conceptual development and technical integration. For cobots to effectively contribute to customised production, they must follow a rich understanding of work practices, production methods, and customisation requirements entailed in the manufacturing. This understanding can be developed through iterative design and a holistic approach, covering all aspects from conceptualisation, prototyping, and implementation. This will ensure that the cobots are versatile, adaptable, and able to meet changing production needs.

4) Risk mitigation

Even though cobots are generally equipped with safety measures such as a safe stop button and sensors to detect and stop collisions with people, it is still possible to get hurt by a faulty cobot that has not been adapted to its environment. Prototyping tools allow us to mitigate this risk in two ways. First, it is possible to create virtual models of the environment and cobot, meaning that we can simulate tasks and clarify potential safety risks we might not otherwise have detected purely from prior experience and safety standards. This allows us to develop safety measures long before anyone gets hurt. Second, while engaging end-users in the design process has many benefits, people with non-technical backgrounds are not necessarily comfortable interacting with a robot – especially an unfinished robot solution. Therefore, prototyping tools can support our engagement with end-users by removing the potential fear of getting hurt.

5) Enhanced creativity

As design researchers, we often engage in generative ideation activities to address research questions. Prototypes enable us to see facets of an idea that were not previously obvious. This is sometimes referred to as ‘filtering’ (for further reading on this topic, see our list of references). It’s like putting on special glasses that highlight the specific qualities we want to explore further while still capturing the essence of the entire concept. In order to use prototypes as filters, it is necessary to have a holistic understanding of the context within which the cobot will operate and how that context can change with the introduction of the cobot. A prototyping toolkit can help give us different lenses to explore facets of the context in early prototypes, thereby becoming a creative extension for designers. This could include prototyping tools such as facilitating Wizard-of-Oz methods, video prototyping, or virtual simulations.

6) Facilitating internal communication

Prototyping is an activity that allows us to both internalise and externalise ideas. In other words, prototypes enable us to internally reflect on what works and what does not work as well as communicate ideas to team members, clients, or anyone interacting with them. Prototypes have always had that role in design research, but with the technical barriers to quick prototyping for human-robot collaboration, there is a need to identify new ways to facilitate this role of prototypes.

We look forward to sharing our progress throughout the next few years. Please reach to us for further discussion, questions, or other inquiries.

Further reading:

Lim, Y. K., Stolterman, E., & Tenenberg, J. (2008). The anatomy of prototypes: Prototypes as filters, prototypes as manifestations of design ideas. ACM Transactions on Computer-Human Interaction (TOCHI)15(2), 1-27.

Wensveen, S., & Matthews, B. (2014). Prototypes and prototyping in design research. In The routledge companion to design research (pp. 262-276). Routledge.

William Odom, Ron Wakkary, Youn-kyung Lim, Audrey Desjardins, Bart Hengeveld, and Richard Banks. 2016. From Research Prototype to Research Product. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems (CHI ’16). Association for Computing Machinery, New York, NY, USA, 2549–2561.

Gopika Ajaykumar. 2023. Supporting End-Users in Programming Collaborative Robots. In Companion of the 2023 ACM/IEEE International Conference on Human-Robot Interaction (HRI ’23). Association for Computing Machinery, New York, NY, USA, 736–738.

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.

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.

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.

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).

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).

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).