There is nothing particularly new about robotics in industry. Robots have been operating on shopfloors for decades now. What is new, however, is the ability of those robots to work alongside and interact with human workers.
For many years, industrial robots meant large-scale production robots operating in isolation, safely caged off to prevent any accidents. Today, however, with advances in technology and the ability to scale robotics down both in terms of size and cost, it has become common to see smaller robots forming an inherent part of production lines.
The rise of these collaborative robots (cobots) has been so rapid that it is estimated that by 2025 cobots will comprise 34% of total robot sales. Much of this growth is anticipated to occur from those SME companies who, operating in High-Mix/Low-Volume (HMLV) production environments, realise the flexibility and productivity-boosting potential of collaborative robot technology.
Much of this potential lies in cobots’ ability to perform repetitive, monotonous or error-prone tasks - freeing-up time for an operator to devote to more complex, creative and value-adding tasks. According to Peter McCullough, product manager at Doosan Robotics: “Although cobots operate at lower speeds and payloads than industrial robots, their (relative) low cost, inherent safety and flexibility, easy integration and operation and ‘collaborative’ nature means (application-dependent of course) that they can deliver significant productivity improvements and a fast return on investment…The capability and acceptance of cobots is clearly increasing, and as countries emerge from coronavirus lockdowns and work restrictions, it is likely that adoption and use of the technology will grow exponentially.”
Barry Weller, product manager at Mitsubishi Electric, says: “Cobots are ideal when machines need to handle and hold parts while humans work on them. The ergonomics of a cobot arm are very different to that of a human; reach and repeatability are better, as is holding still for long periods. In this situation it can make a task far more comfortable for a human to complete, using robot assistance. This not only improves the working environment but is also a benefit for quality and productivity.”
Another factor in the increasing popularity of cobots is the fact that innovation comes not just from system manufacturers, but also from accessory, software and end-of-arm tooling suppliers has widened their appeal and application potential.
Widely acknowledged as a pioneer in this field is Universal Robots (UR), which developed the world’s first commercially viable cobot as far back as 2008. Today, UR has more than 37,000 cobots on the job around the world.
This was largely achieved by the development of the UR robot’s force and safety control features, which ensure that if the robot collides with a person it automatically stops operating so it doesn’t cause bodily harm. These features have eliminated the need for safety guarding in the vast majority of installed UR robot applications and established the company as a trailblazer for the collaborative robot concept.
As well as this belief that safety is simply the cost of entry to the cobot market, UR’s frontrunner position has been maintained by constantly raising the bar for what the term ‘collaborative’ really entails. By this, it means that the label not only means humans can collaborate directly with robots but also addresses ease of use and implementation – fundamentally, that a robot is not truly collaborative if it’s not affordable and easy to work with.
UR’s most recent raising of the bar has come in the form of the UR16e cobot, which boasts a 16kg payload capability. UR16e combines the high payload with a reach of 900mm and pose repeatability of +/-0.05 mm making it ideal for automating tasks such as heavy-duty material handling, heavy-part handling and machine tending.
“At Universal Robots we continue to push the boundaries of what’s possible with collaborative automation,” says Jürgen von Hollen, President of Universal Robots. “Today, we’re making it easier than ever for every manufacturer to capitalize on the power of automation by bringing a cobot to market that is built to do more as it delivers more payload than our other cobots.”
Like with UR’s other e-Series cobots; UR3e, UR5e and UR10e, the UR16e includes built-in force sensing, 17 configurable safety functions, including customisable stopping time and stopping distance, and an intuitive programming flow.
Another leap in terms of payload and capability comes in the form of the Yaskawa Motoman HC20DT robot, the latest example of Yaskawa’s expanding range of Motoman Smart Series robotic solutions that are helping users to meet the rapidly
changing demands and adaptation of new manufacturing practices.
The Motoman HC20DT is a six-axis robot which combines the powerful capabilities of handling payloads up to 20kg, the flexibility of a reach of up to 1700mm with the highest levels of safety. This represents ‘game-changing’ cobot potential for applications such as automated palletising which have until now been limited by the payload capacity and working envelopes of other typically available robots. Depending on the application it can be switched between safe / collaborative mode in phases of man-robot interaction and returning to high industrial speed when the absence of the operator is detected by additional safety devices.
Operator safety is assured thanks to features such as power and force limit technology that stops the robot in case of contact with an operator while the robot arm geometry is designed to avoid finger pinch points. Also, the robot arm can be guided by an operator and robot positions and gripper operation can be registered via ‘Teach’ and ‘Tool’ buttons. These features also contribute to time saving during programming and where the application requires additional protective measures, such as safety fences, these can be added in line with risk assessments.
Unlike traditional and more complex robot execution which typically requires significant upfront investment in training, the Smart Series technology provides simple, intuitive programming and operation methods for operators.
Among the other important features are a fully industrial robot controller, the YRC1000 and YRC1000 micro, safety by design with smooth rounded edges, internal cable routing, a functional safety unit and safe force / torque sensors for all six axes.
Clearly the future of cobots lies in increasing their presence in the SME sector. Naturally, this pushes factors of cost and ease-of-use to the forefront. This was the key principle for the founders of Automata in their development of the Eva robot.
Launched lasy year and claimed to be the first-ever desktop robot for industrial use. Eva is designed to be lightweight, user-friendly and accessible, while maintaining industrial quality performance and costs just £4,990.
Weighing 9.5kg, with a footprint of 160mm² and a reach of 600mm, it includes an on-board controller in its base and comes with a free subscription to Automata’s Choreograph software. It has no external control devices as Choreograph can be accessed through any web browser and is programmed via two buttons integrated on the robot arm.
Suryansh Chandra and Mostafa ElSayed, co-founded Automata in 2015 after discovering the limitations of conventional robots.
So, the pair set out to develop their own robot that was affordable to companies that don’t have the budgets of vehicle manufacturers, for example. The second requirement was that it had to be quick to set up and not need the bulky mountings. Four years – and many iterations – later, Eva is finally ready. The reason for this long gestation period? Taking on the “gatekeepers of robotics” and creating their own gearbox, the ‘Automata Drive’.
ElSayed explains: “We knew that if we had to make a dent in the robotics market we were going to have to tackle a gearbox. There’s only two companies in the world that make them [harmonic gear drives], one based in Germany the other in Japan, they control the price.”
More than that, he continues, once a designer commits to a specific gear drive they are tied into suppliers of other components like motors, brakes and electronics.
“The Automata Drive is central to our robot.” Says ElSayed. “Its patent protected technology is very similar to a harmonic drive and gives about 80% of the performance for around 20% of the cost. But, it’s purpose built, it doesn’t need to perform all kinds of use cases. It’s all about manufacturing tolerances, that’s what helps bring the price down, not the price of the components.”
Programming Eva’s movements is simply done by pressing one of the two buttons which releases the brakes and allows operators to lead it to a ‘waypoint’ where a command is to be carried out. Clicking the second button sets the waypoint, a process called ‘back driving’. This movement is transmitted to the operator’s device, running Choreograph on a browser, and saves those points.
“If I want to locate an object on this table I can simply drag the robot there,” Chandra explains. “This is something that would have taken much longer, much more measurement and much more CAD skills previously.”
Editing the movements on Choreograph is also simple. Waypoints can be edited graphically on the screen of the device and those waypoints can be dragged and dropped into a timeline, similar to video editing software, in the order the robot needs to move.
Given that they are likely to become ever more common, what is the next stage of development for cobots? Almost certainly greater levels of sophistication will emerge. One suggested possibility is reinforcement learning, a form of machine learning where a computer learns to complete a task by having repeated interaction with a dynamic environment. Through an iterative trial-and-error approach, the machine explores the environment. This exploration generates data, which is used by the machine to determine the best course of action to complete its job. This happens without human intervention and without having to programme the machine to perform a specific task.
Reinforcement learning differs from supervised machine learning in that in the latter, algorithms are built using data sets that contain the correct answer to a given problem. In reinforcement learning there is no answer – the machine has to find one by trying different courses of action and eventually selecting the one that gives the most reward with the least effort.
Neil Ballinger, head of EMEA sales at EU Automation explains: “Reinforcement learning algorithms encourage a machine to act in a similar way, interacting with a dynamic environment – for example a factory floor with several production lines – until it finds the most convenient way of proceeding.”
In industrial manufacturing, reinforcement learning is used in processes where complex decision-making skills are required, especially where machines need to cope with changes in dynamic environments.
Says Ballinger: “For example, a cobot can be trained to find the best path to avoid interferences, such as objects or the limbs of human workers, while continuing to perform its task. This would be simple for a human, but for machines it is an incredibly complex process that requires a careful analysis of an unpredictable environment. If successful, the cobot will be more productive, because it won’t need to stop to avoid impact.”
Reinforcement learning can also be used to streamline production, an approach used by researchers at the Industrial AI Lab at Hitachi America. The researchers designed a virtual shop floor as a bidimensional matrix and used reinforcement learning algorithms to repeatedly interact with this virtual environment. By doing this, they were able to determine the best set up to increase productivity and reduce delays in servicing their customers.
