THE ROBOT REPORT MARCH 2021

A Supplement to Design World - March 2021 www.therobotreport.com

How ActiNav

automated a challenging bin-picking task page 54

INSIDE: • ABB develops next-gen GoFa, SWIFTI cobots....................................................62 • Tactile sensing for feedback control, object classification .........................................68 • Q & A: Greg Smith, President, Teradyne Industrial Automation Group ........................72

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How ActiNav

automated a challenging bin-picking task Facing challenges due to labor shortages, Allied Moulded turned to Universal Robots’ ActiNav to automate an important bin-picking application.

Steve Crowe | Editor, The Robot Report

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THE ROBOT REPORT

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The Robot Report

Founded in 1958, Allied Moulded is a full-service molding operation manufacturing non-metallic electrical boxes and enclosures for residential, commercial and industrial markets. Facing significant challenges due to labor shortages, the Ohio-based company chose Universal Robots’ new ActiNav system to automate an important bin-picking application. The deployment enabled Allied Moulded to reduce overtime expenses, move existing workers to more ergonomic tasks and improve consistency in the production process.

Challenge Like many firms throughout Ohio’s manufacturing sector, Allied has faced challenges filling open positions due to difficult labor market conditions. At the same time, the company wanted to enhance the safety of its current staff by freeing them from repetitive, unergonomic bin-picking tasks. Quality improvement was also a motivating factor in the decision to explore automation “When looking for automation you look for repetitiveness. You have better control over your quality if you have more consistency with loading and unloading machines,” explained Tom Carlisle, manufacturing support department manager, Allied Moulded. “As far as keeping and retaining your employees, you want to remove some of the repetitiveness from their positions.”

Using manual labor on bin-picking applications produces inconsistent results, added manufacturing engineer technician, Nate Gilbert. “One of the biggest challenges with manual labor is they get tired and towards the end of the day, production would go down; whereas with a robot, you can always count on a consistent output.”

The COVID-19 pandemic added another layer of concern regarding the company’s manual labor force. “We could risk that dedicated staff at any moment would not be here for reasons beyond their control,” said Carlisle. “So we needed a way to keep those processes running.”

Additionally, Allied Moulded required a bin-picking solution with a small footprint, so that it could easily be incorporated into its existing facility.

ActiNav’s high-resolution sensor and CAD matching enable high accuracy picks. | Universal Robots

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The Robot Report

Inside ActiNav Universal Robots’ ActiNav autonomous bin-picking kit is an

Solution Allied Moulded has been tracking the development of bin-picking automation om its infancy, and has found significant limitations with traditional approaches, said Carlisle: “Most of your bin-picking systems were developed for forging operations, but they didn’t have the speed that we were looking for.”

When Allied first researched binpicking automation, the technology “just wasn’t where we needed it to be,” said Gilbert: “The guarding was too intrusive, and that was going to make it difficult when we needed to have an operator in that area. Floor space here at Allied is pretty limited already, and the thought of having to put up more guarding to accommodate a robot was one of the things that held us back initially; but with collaborative robots being safe around employees, we felt that was a great way to go.”

Allied Moulded’s interest in the potential of collaborative robots (cobots) increased following a trip to a nearby factory that had already successfully deployed cobots om Universal Robots (UR). A follow-up encounter with UR at a trade show eventually led to the deployment of UR’s ActiNav autonomous bin-picking kit – a flexible, automated bin-picking solution that synchronously handles vision processing, collision- ee motion planning, and autonomous realtime robot control.

“ActiNav was the first system we were confident we could get in the space available without creating a bunch of extra obstacles. Just the simplicity of it picking parts out of the bin and onto the conveyor is what we were really looking

automated bin-picking solution that synchronously handles vision processing, collision- ee motion planning, and autonomous real-time robot control. The ActiNav kit consists of: • • • • •

Autonomous motion module 3D sensor (placed above bin) ActiNav user interface Alignment marker All cables, screws, and brackets Universal Robots e-Series cobot (UR5e or UR10e)

for, and ActiNav seemed to meet that demand,” said Gilbert, noting that ActiNav constitutes a major improvement to the vibratory feeders that are o en used for part positioning. “We have vibratory bowl feeders on lots of our machines; but they are loud, and they are expensive, so it just wasn’t justified to put that type of system on this machine. But ActiNav is much lower cost, and much quieter.”

While Allied Moulded had experience with traditional automation, deploying a cobot was “a brand new experience,” said maintenance group lead, Nathan Wells: “It was really exciting to see something that didn’t need to be caged in, and that I could walk around while it was doing its job.

When it came to programming, this was probably one of the easiest robots that I’ve ever had to program. You don’t really have to have any specific numbers to put in, or anything like that; you just have to move it into place, push a few buttons and there you go, there’s the program.”

Feeding ActiNav the data it needs to take care of part recognition is an equally painless process, said Wells: “We used a CAD file of the product, loaded it into the ActiNav and it took that and used it to register parts out of the bin. It was

Allied Moulded’s process begins with stock handlers unloading a full crate of parts into a dumpster. Once activated, the dumpster dumps its parts into the ActiNav bin. | Universal Robots

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very easy to load in. You just put it on a USB and plug it into the controller.”

Meanwhile, teaching the bin was also very straightforward: “We just touch the robot to each part of the bin. You do a few spots of that, and ActiNav learns the bin itself. I would say a er the first day of setup, it took maybe a shi to learn how to actually do the programming, and a er that, we were good on our own.”

The process begins with stock handlers unloading a full crate of parts into a dumpster. Once activated, the dumpster dumps its parts into the ActiNav bin.

ActiNav picks up parts –in this case, extruded fiberglass electric junction box housings – and places them in proper orientation onto a narrow, railed conveyor.

Correct placement is crucial, explained Carlisle: “The part has to be placed in a particular order on the machine because of the secondary operations that the machine performs. If the part is placed incorrectly on the conveyor, you’d have to reject that, so you’ve lost all the labor and materials of that part.”

The conveyor brings the parts to a small, caged work cell that has a rotary table with multiple stations. At each station, there is a fabrication element that is applied to the cup and eventually there is an out-conveyor that dumps finished parts into a large bin. Along the way, Carlisle notes, ActiNav has to make some decisions autonomously: which part to pick, how to place it in the correct orientation and how to identi incorrect parts, place them aside and continue with its main task.

Once the bin is kept full, ActiNav can go all day without operator intervention, said Gilbert. “I’ve been pretty impressed with the ability of the robot to pick our parts out of the bin, no matter the THE ROBOT REPORT

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The Robot Report Programming ActiNav is intuitive thanks to full integration with the UR teach pendant. ActiNav took Gold in the Industrial Automation category at the 2020 LEAP Awards. LEAP (Leadership in Engineering Achievement Program) Awards celebrate the most innovative and forward-thinking products serving the design engineering space. | Universal Robots

orientation, and place them on the machine correctly. A task like that is usually pretty hard for a robot to be set up to do. We’re pretty confident in an operator doing it; but to have the robot do it and not have to use direct labor in that situation has been a big benefit.”

Traditional automation requires mats, fences and enclosures to protect workers om potential injury, but this can lead to enclosures “the size of an office” being required to automate some tasks, noted Carlisle, whereas cobots are designed to operate in close proximity to people: “This lets you have flexibility of where you’re going to place the robot [and] lets you interact with it: if there’s difficulty and you need to go and clear an error, there’s not a large procedure that you have to go through to get access. And it makes it more acceptable to individuals on the floor because it doesn’t seem inaccessible to them; it’s right there in the open.”

Results ActiNav doesn’t take any lunches, cigarette or bathroom breaks and it always shows up for work, Carlisle noted. “It’s like the tortoise and the hare.

ActiNav is consistent. It’s always there, putting the part on. A human operator can be faster, but their consistency can be affected by the need to take breaks. At the end of the day, the total amount of product should be the same, if not better, with ActiNav than a human operator;

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ROS 2 driver for UR cobots PickNik is collaborating with Universal Robots (UR) and Forschungszentrum Informatik (FZI) on developing the official ROS 2 driver for UR’s collaborative robot arms.

PickNik is developing the UR ROS 2 driver as a test platform for ros2_control, the popular control amework for the Robot Operating System (ROS) that is in the final stages of porting to ROS 2. PickNik is also leveraging its in-house UR5 cobots to further test and integrate the motion planning amework MoveIt to ROS 2. As a member of the ROS 2 Technical Steering Committee, PickNik is hoping these hardware demos with MoveIt 2, ROS 2, and UR cobots will speed up the transition to the more industrial and hardened ROS 2 middleware.

The UR ROS 2 driver is based on the original Universal_Robots_ROS_Driver for ROS 1 and will be fairly similar. However, it will take advantage of new ROS 2 features such as component nodes and zero-memory copy integration with ros_control. From a performance perspective, the major benefit is decreased latency.

At press time, the new ROS package was in the alpha stage and provides config files for just the UR5e cobot. PickNik is encouraging the open source community to start submitting patches and bug reports for the new driver as needed. PickNik said launch and config files for the other cobot models, and additional functionality such as end-effector I/O and force/torque data streaming, will be coming soon.

www.therobotreport.com

THE ROBOT REPORT

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The Robot Report but without the fatigue and manual dexterity of moving all the time. At the end, the tortoise just keeps putting it out because he’s consistent.”

Deploying ActiNav has allowed operators at Allied Moulded to upskill, becoming trainers and mentors on the system and contributing design ideas for future automation projects. “As we bring in automation to do a lot of the mundane and unsafe tasks, and to be safer, our operators are the biggest asset that we have and they make the best trainers for your next generation of employees,” said Carlisle.

ActiNav’s versatility is inspiring a host of ideas for future applications at Allied Moulded. “Picture yourself on the candy line with Lucille picking the chocolate drops off,” suggested Carlisle, referring to the famous chocolate factory scene in the television sitcom “I Love Lucy.”

“ActiNav could do that for you. And tomorrow it might be candy canes. The next day it might be fruitcakes. That’s the flexibility you’d like to see.

And once you see the task performed and you say, ‘Well, it can do this,’ you mind goes, ‘I have a hundred other things that I’d like to try.’”

Deploying ActiNav has allowed operators at Allied Moulded to upskill, becoming trainers and mentors on the system and contributing design ideas for future automation projects. | Universal Robots Allied Moulded is “well on its way” to being able to move ActiNav to any machine and set it up for any part style, said Gilbert. “We’re planning to implement ActiNav anywhere we can find a benefit for it. If we had a failed vibratory bowl, for example, we would just have ActiNav pick the part out of the bin and place it on the line.”

The company plans to use ActiNav on multiple machines in its facility. “Table loading would definitely be something that I could see happening,” said Well. “This would be loading parts from a bin directly onto a round table that will rotate around to stations, instead of loading it onto a conveyor.” RR

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3/10/21 10:02 AM

ABB develops next-gen GoFa, SWIFTI cobots ABB’s GoFa and SWIFTI lines offer higher payloads and speeds to complement its YuMi cobots.

Steve Crowe | Editor, The Robot Report

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The Robot Report

ABB is expanding its portfolio of collaborative robotic arms. The 2020 RBR50 company recently introduced its GoFa and SWIFTI cobots that offer higher payloads and speeds to complement its YuMi cobots. The GoFa and SWIFTI cobots are available now.

ABB said the new cobots will accelerate its expansion in high-growth segments, including electronics, healthcare, consumer goods, logistics and food and beverage. ABB introduced a new cobot website that offers additional details and resources about the new cobots.

In 2019, more than 22,000 new cobots were deployed globally, up 19 percent compared to the previous year, according to market research firm Interact Analysis. The demand for cobots is estimated to grow at a CAGR of 17 percent between 2020 and 2025, according to Interact Analysis, while the value of global cobot sales is expected to increase om an estimated $0.7 billion in 2019 to $1.4 billion by 2025.

ABB’s GoFa cobot Let’s start with the new GoFa CRB 15000, a 6-axis cobot with torque and position sensors in each joint, a 950mm reach, 5kg maximum payload, and speeds up to 2.2 meters per second. Pronounced ‘go-fa’, the new cobot has a payload 4.5 kg higher than YuMi and a 70% longer reach than the single-arm cobot.

GoFa is designed for a variety of applications, including material handling, machine tending, component assembly , packaging and inspection, and laboratory automation.

Users can program GoFa via lead-through programming and ABB’s new Wizard programming so ware. Based on simple graphical blocks, Wizard makes it easier for nonspecialists to automate their applications.

“Offering high speed, a 5kg payload, precise performance and a small footprint, coupled with simple set up and programming, GoFa can be quickly and easily deployed to help fill gaps in production lines wherever and whenever needed,” said Andie Zhang, global product manager, collaborative robotics, ABB Robotics. “This provides users of all sizes, om SMEs to large companies, with the flexibility to quickly adapt to changing circumstances and respond instantly to changing customer demand without having to incur delays arising om having to find extra staff at short notice.”

Pronounced ‘go-fa’, the 6-axis cobot has a payload 4.5 kg higher than YuMi and a 70 percent longer reach than the single-arm cobot. | ABB

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The Robot Report The 6-axis SWIFTI cobot line is based on ABB’s IRB 1100 industrial robot and offers a payload of 4 kg and maximum speed of 5 meters per second. | ABB

ABB said the new cobots will accelerate its expansion in highgrowth segments, including electronics, healthcare, consumer goods, logistics and food and beverage.

ABB introduced a new cobot website that offers additional details and resources about the new cobots.

With built-in sensors in each joint, GoFa automatically stops if it makes contact with a human or another robot.

Its plastic and aluminum joints also feature rounded geometry, with no pinch points that could trap limbs. Other safety features include a visual safety configurator on GoFa’s FlexPendant, as well as an interaction status light that changes color depending on GoFa’s operating status.

Comparing ABB’s entire cobot lineup Before we get to the SWIFTI cobots, let’s compare ABB’s entire cobot lineup: ABB SWIFTI cobots The 6-axis CRB 1100 SWIFTI cobot line, which is based on ABB’s IRB 1100 industrial robot, offers a payload of 4kg and maximum speed of 5 meters per second. There are two models that offer different reaches: 475mm and 580mm.

Comparing ABB's Cobot Arms

Payload Reach Degrees of Freedom Max TCP Speed

GoFa

0.5 kg

5 kg

SWIFTI 4 kg

559 mm

559

950 mm

580 mm or 475 mm

14

7

6

6

1.5 m/s per arm

1.5 m/s

2.2 m/s

5 m/s

Repeatability

0.02

0.02

0.05mm

0.01 mm

38 kg (including controller)

9.6 kg

27 kg

21 kg

IP30

IP30

IP54

IP40

Tabletop

Any Position

Any Position

Any Position

• RobotStudio AR viewer • Inherent safety = close collaboration • Soft padded joints • Servo fingers • Integrated vision • Vacuum gripper • Lead through programming"

• RobotStudio AR viewer • Integrated joint design with torque sensors • Arm Side Interface (ASI) featuring user-customizable buttons and light ring • Lead through programming • Interaction status light • Small footprint"

Mounting Positions Features

Single-Arm YuMi

0.5 kg per arm

Robot Weight Protection Class

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Dual-Arm YuMi

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• RobotStudio AR viewer • Inherent safety = close collaboration • Soft padded joints • Servo fingers • Integrated vision • Scanning QR code • 2 x vacuums • Integrated controller"

www.therobotreport.com

• • • • • • • •

RobotStudio AR viewer 4 integrated air supplies Industrial robot speeds Lead through programming Wizard easy programming Interaction status light Safety laser scanner SafeMove cobot software"

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To ensure safety, the SWIFTI line combines ABB’s SafeMove safety certified robot safety software, which is integrated directly into the cobot controller, with a safety laser scanner. | ABB

ABB said SWIFTI is designed to support intermittent collaboration between human and robot, including tasks such as kitting, material handling, and screwdriving to insertion and polishing tasks.

ABB said that since there is no potential for contact between human workers when SWIFTI is moving, it can be used with the same tooling as a standard IRB 1100 industrial robot. An example is the inclusion of a vacuum pack, which features four integrated air supplies that can be used to enable simultaneous picking of multiple items using suction.

To ensure such safety, the SWIFTI line combines ABB’s SafeMove safety certified robot safety software, which is integrated directly into the cobot controller, with a safety laser scanner to create a speed and separation safety concept. ABB said the goal is to avoid any contact between human and robot that could potentially result in injury.

This enables safe collaboration at higher speeds and payloads without the need for containment measures such as fences, ABB said.

Using a ‘green, yellow, red’ zone approach, the robot reacts according to which zone a human worker is in. If the worker is detected in the green zone, then the robot will carry on working at its full speed and range of movement. If the yellow zone is entered, the robot restricts

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its movement and speed to a safe limit.

Entry into the red zone will bring the robot to a complete halt, allowing the worker to safely approach the robot to perform a task such as loading or unloading. The robot will remain stopped until the red zone is cleared and will only return to full movement and speed once the worker is back in the green safety zone.

“As well as helping to reduce the overall cost of an installation through reduced spending on additional safety measures such as fences, being able to remove physical separation between people and robots saves space and makes for more open workspaces,” said Zhang. “This helps people operate and carry out their tasks freely, which minimizes potential disruption and interruption of production processes caused by having to stop the robot to allow operators to enter a cell to sort out issues in the event of a problem.” RR

March 2021 www.therobotreport.com

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The Robot Report

Tactile sensing

for feedback control, object classification

Enabling object classification and real-time feedback control based on tactile sensing enhances manipulation capabilities and will be especially important for cobots being designed to operate with more human-like capabilities.

Alan Sullivan, Diego Romeres, Radu Corcodel

Collaborative robots (cobots) are designed to operate around humans in a factory environment and to execute tasks in a human-like fashion. Interestingly, assembly tasks that are simple for humans to perform such as gripping, grasping, turning and rotating items require highly sophisticated reinforcement learning (RL) protocols and tactile sensors for cobots to repeatedly successfully perform. Visual programming routines in the onboard so ware enable operators to program a robot via a “train by demonstration” graphical user interface. However, the technology behind these easily programmed and controlled robots is complex.

Conventional robots are able to reliably grasp objects due to the availability of highprecision sensing om fixed cameras with known poses relative to the robot. However, the key benefit of using cobots is that they are, by design, easier to set up and program with the result that sometimes the only vision system available to localize objects is a lower-resolution camera mounted on the robot itself.

To close the resulting perceptual gap, tactile sensors have been developed by several research teams, and research is underway on methods to use them for tactile feedback and object classification. This is especially important for tasks such as insertion (e.g., a sha into a bushing) or for handling so or delicate objects such as food.

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The reason tactile sensing is needed for insertion is that – once the robot picks it up – the object being manipulated may change pose, e.g., due to an unsuccessful insertion attempt. It is thus critical for successful insertion to adapt to object pose changes and tactile feedback can provide the necessary information to detect such “in-hand” object pose changes. For so or delicate items, a critical grasp is needed, that being a grasp that is tight enough to hold the object without slipping, but not too tight in order to prevent any damage to the item.

Training with model- ee RL Recently, several research papers related to tactile-based control have been published by research groups at the Mitsubishi Electric Research Lab (MERL, Cambridge, MA). A paper entitled “Tactile-RL for Insertion: Generalization to Objects of Unknown Geometry” was submitted by MERL and MIT researchers to the IEEE International Conference on Robotics and Automation (ICRA) in which reinforcement learning was used to enable a robot arm equipped with a parallel jaw gripper having tactile sensing arrays on both fingers to insert differently shaped novel objects into a corresponding hole with an overall average success rate of 85% with 3-4 tries.

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In this work, the change in tactile signals over time is processed into a tactile flow signal representing the change of contact between the grasped object and the gripper during insertion. Subtle changes in the rotation of the objects in the gripper fingers caused by collisions with the target are detected by the tactile sensing arrays and can be used to provide real-time feedback to correct the object’s position and pose. Using tactile signals as input, a controller was trained with deep, model- ee RL to learn a tactile-based feedback insertion policy. In this manner, the controller learned om its “mistakes” and increased its effectiveness. To further develop the learning regimen of the controller, training was performed on pegs of different shapes (i.e., round and square) in a curriculum-learning fashion, starting with relatively simple tasks and learning increasingly more challenging variations.

This led to a significant reduction in the number of training iterations. The system was first trained to place the pegs against a flat wall with one constraint, next a corner with two constraints, followed by a U with three constraints, and finally inserting into a square hole.

The RL process was successful enabling the resulting controller to generalize to novel real-world objects, with similar shapes as the training pegs, such as a small and big bottle, a phone charger and a paper box. www.therobotreport.com

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Classifying objects by ‘feel’ The controller learning worked well on objects with a firm or hard surface.

But what about objects with a thin or malleable surface that could be damaged by mishandling by a robot arm, such as a peach or cellophane-wrapped package?

To address that problem, MERL researchers presented a second paper that also leverages the patterns obtained by tactile sensing for robotics at the 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

The paper, entitled “Interactive Tactile Perception for Classification of Novel Object Instances,” describes research in which signals from tactile arrays developed at MERL and attached to the fingers of a gripper mounted to a robot arm can be used to classify novel object instances based only on tactile “feel.”

The set of test objects used in the experiment included such household objects as an apple, a stuffed animal, paper cup, toy football, tennis ball and a wine glass. Objects are localized in the workspace using depth sensing after which the robot executed a sequence of palpations of the object using proposals from a grasp pose detector.

The novel tactile arrays consist of temperature-compensated, superminiaturized pressure sensor cells laid in a planar grid and attached to the finger pads of our robotic gripper. The signals from the tactile array are converted into a 3D surface representation that is similar to human tactile perception. This approach conveniently and elegantly represents the tactile information as an implicit subset of the object’s geometry, precisely localized in the robot’s workspace. In essence, the finger pads engage with an object like a human hand and – through controller manipulation and learning – begin to understand the qualities of the object to properly handle it.

The tactile data from the sequence of palpitations was encoded in a tactile feature space using the Viewpoint Feature Histogram (VFH) that encodes both the geometry and the viewpoint of a tactile point cloud. Each palpation’s VFH feature was processed using a OneClass Support Vector Machine (OC-SVM) to determine whether the object was

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similar or different to a previously tested object. If the object is novel, its tactile model consisting of all its VFH features is stored and used for future object detection tasks. An advantage of this approach is the data efficiency due to the omission of the need to pre-train the system on a set of known objects. It therefore allows this approach to easily expand to incorporate novel objects.

Although the tactile information encodes geometry information, the OC-SMV is agnostic to object scale. The results show good object separation for object pairs having significantly different tactile feel such as geometry and hardness, with the accuracy slightly improving as the number and distribution of palpitations increases.

Enhancing manipulation skills Although formulated as an exploratory research, our results show that using pressure-based tactile sensing can successfully be employed for novel object detection by performing few palpitations and without the need for pre-training.

Enabling object classification and realtime feedback control based on tactile sensing enhances the manipulation capabilities of today’s robots and will be especially important for cobots that are being designed to operate with more human-like capabilities. Looking forward, we expect tactile sensing to play a key role in achieving higher levels of dexterous manipulation in contact-rich settings including tactile serving, in-grip pose detection and controlled slipping.

While these applications mostly reside on the factory floor at this stage, the learnings derived in this setting will be critical for the effective use of homebased robots to perform routine tasks such as putting away the groceries, meal preparation and cooking, and just maybe someday changing a baby’s diapers. RR Alan Sullivan, Ph.D., is a Computer Vision Group Manager, Diego Romeres is a Principal Research Scientist, and Radu Corcodel is a Research Scientist with Mitsubishi Electric Research Laboratories (MERL), the US subsidiary of the corporate research and development organization of Mitsubishi Electric Corporation. MERL

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DESIGN WORLD

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The Robot Report

Q&A:

Greg Smith, President, Teradyne Industrial Automation Group Inside Teradyne’s acquisition strategy and the future of collaborative robotics.

Steve Crowe | Editor, The Robot Report

North Reading, Mass.-based Teradyne built its business around automatic test equipment for electronics. This still accounts for the majority of its business, but Teradyne embarked on a series of acquisitions for key industrial robotics companies, including AutoGuide Mobile Robots, Energid, Mobile Industrial Robots and Universal Robots.

The combination of collaborative robots, automated mobile robots and motion control so ware for robots are helping companies improve operational efficiency.

We recently talked to Greg Smith, president, Teradyne’s Industrial Automation Group. Smith explained the goals of acquiring the aforementioned companies, as well as what Teradyne is looking for in future industrial automation-related acquisitions. He discussed the future of collaborative robotics and offered a unique perspective on mobile manipulation.

This interview was adapted om Smith’s appearance on The Robot Report Podcast. To hear the full conversation, check out The Robot Report Podcast wherever you listen to podcasts.

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The Robot Report Teradyne built its business around automatic test equipment for electronics. This still accounts for the majority of its business, but Teradyne embarked on a series of acquisitions for key industrial robotics companies, including AutoGuide Mobile Robots, Energid, Mobile Industrial Robots and Universal Robots.

Can you describe Teradyne’s vision for the future of robotics?

Even though we bought Universal Robots in 2015, we really started this journey back in about 2013. If you look at the core business Teradyne is involved in and the trajectory of that market om 2005-2013, Teradyne was really successful in terms of gaining share and building a strong and profitable business.

But the fundamentals of that market, semiconductor testing, were not that great. The market was shrinking between 5-10% per year during that period on average. We felt we had a long-term problem that we needed to solve. We needed a way to drive growth in the organization and revitalize the core.

Povlsen named Universal Robots president Universal Robots (UR) named Kim Povlsen its new president. He started the role on March 1, leading the cobot arm pioneer into its next stage of growth.

Povlsen, a Danish native, held various executive business and technology leadership roles at Schneider Electric, a global energy management and automation company. He most recently served as VP, Strategy & Technology, and was responsible for the technology strategy and execution within a multi-billion dollar global organization. Kim holds a master’s degree in Computer Science & Embedded Engineering om the University of Southern Denmark. UR is based in Odense, Denmark.

“I have been impressed with Universal Robots for some time,” said Povlsen. “To me, the company represents the pinnacle of innovation and potential and I was thrilled to be approached for this unique leadership role.

The company not only pioneered the category of collaborative robots, created an ecosystem of partner technology solutions and a vast global distribution network to serve customers in their varied industrial automation needs, it also has the potential to fundamentally reshape automation across the global economy. I really look forward to working with, learning om and being part of the great people at Universal Robots.”

UR is owned by Teradyne. Greg Smith, president of Teradyne’s Industrial Automation Group, told The Robot Report someone who loves robots is the right person to run UR. The person needs to be able to simultaneously run a “world-class manufacturing and distribution company, then walk to a meeting where you’re coming up with the ideas on how to open up automation to new areas.”

“Kim combines a fantastic track record as a dynamic executive with a background in and a tremendous passion for robotics,” Smith said. “With Kim on board, Universal Robots is poised to strengthen its leadership in the global market for collaborative robotics. With Kim’s leadership, we can accelerate the growth in new applications and market growth for cobots.

“Universal Robots was one of the original companies at the core of the Odense innovation hub for robotics, and our global customers recognize the innovation and quality of that Danish heritage. I’m thrilled to have a Danish executive who can build on our achievements and support the further development of our robotics hub and headquarters in Odense.”

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The Robot Report The decision we made was to add a new platform to the company. We spent a lot of time trying to figure out where the best opportunity was. We looked at a lot of stuff, energy exploration, healthcare, and finally looked at industrial automation. We saw there was a potential inflection in industrial automation with the introduction of collaborative robotics, new motors and drive trains coming on the market that allowed for lower price points, and the acceleration of AI and UX technologies to make automation much more accessible.

We started to look for companies that would allow us to get a foothold there. We were really fortunate that we engaged with Universal Robots and were aligned in time when Universal Robots was looking to scale globally. They needed a significant investment to bring their organization to the next level, so they became our anchor property in the area of automation.

How has Teradyne’s Industrial Automation Group performed since it was built out?

There are two things that are really interesting. Within industrial automation, we’ve managed to maintain a greater than 25% growth rate for those businesses up to 2020. In 2020, because of COVID, there was a significant impact to the whole automation business.

And we were hit in a very similar way to other players in the space. But we’ve been really pleased in terms of the growth of Universal Robots. Both MiR and AutoGuide are poised to grow at 40-100% per year rates over the next few years. We’re thrilled about how our prospects look in industrial automation.

The thing we didn’t expect is that a er we made this move, Teradyne’s core business started growing as well. So now we are sitting on top of two growth engines at the same time.

How has the COVID-19 pandemic impacted the collaborative robotics business?

COVID has had a near-term effect that is generally negative for the automation business and generally positive for Teradyne’s core business. As soon as the pandemic broke, essentially, everybody

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stayed home and bought electronics.

The semiconductor industry has been growing strongly.

With industrial automation, continuing sales hasn’t been impacted, but getting new customers has. At the end of the day, people buy om people they trust, and it’s hard to build trust with new people if you can’t meet them, sit down and have a conversation. This past year we generated $40 million of new business through lead generation, even though we’ve been locked in our basements. So we’re doing well.

There’s still a huge amount of demand, but there’s been this drag in terms of building awareness because you can’t do a hands-on demo if you can’t be in the same room.

Is awareness about collaborative robotics still the main challenge?

What we’ve been talking about inside of UR, MiR and AutoGuide is that we have two parallel challenges to deal with. In 2020, UR shipped its 50,000 cobot. In 2020 alone, it shipped more than 9,000 cobots. That’s a lot of hardware. There are a lot of Tier-1 companies worldwide relying on our products for critical operations. So product quality, product reliability, service network, completing engineering programs on time — all of that needs to run in a world-class manner.

At the same time, we think we’ve only penetrated the potential market for robotics about 5%. There’s this need to innovate and find new markets and find the things that are barriers for people to adopt collaborative automation.

That needs to be done in a much more interactive way with our customers and at a much faster pace than developing the next robot, which has to be done to the highest industrial quality standards.

How many cobots does Teradyne expect Universal Robots to sell in 2021?

Coming into 2020, we thought we would sell 13,000 robots before COVID hit. We had the potential for that kind of year.

If you look at 2021, we’re cautiously optimistic that we’re going to see a significant increase.

When we came into 2020, we also built the operations capacity, the

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distribution capacity, and the service capacity to deal with that kind of growth. Essentially, we’re crouched at the starting line ready to go in 2021 with the organization that we need to be able to take advantage of the growth I think we’ll see coming out of the pandemic.

At the end of 2020, Jürgen von Hollen stepped down as Universal Robots president a er four-plus years. He is now CEO of Ultimaker, a Dutch 3D printing manufacturer. Why did step down?

All I can tell you is what he shared with me. He said he loved the journey he went on at Universal Robots. When he joined in 2016, Universal’s revenue was less than $100 million. In 2019, we did $250 million in revenue. He managed a 36% growth rate.

When he joined, Universal Robots had just shipped its 10,000 cobot; when he le , we shipped the 50,000 cobot.

He built something amazing in terms of overall structure. He didn’t say this, but I think he loved that a lot — inventing the global organization and building it out into a world-class company. I think that really got him going. I think he saw the opportunity to do that again with Ultimaker. In terms of the trajectory as a company, he had the chance to transform Ultimaker om a startup into a worldclass company. To some extent, I think he felt his job was done at Universal Robots.

Will we see more integrated products or complete solutions om Teradyne’s industrial automation portfolio? For example, a mobile manipulator that combines a MiR mobile robot base and Universal Robots cobot arm?

There’s an interesting economic challenge around arms on mobile bases.

When people look at doing automation, they look at it om an ROI perspective.

How long is payback going to take? How much utilization does the automation get? If you take a cobot arm and stick it on top of a mobile robot, then you’re in a situation where when you’re using the arm, the base isn’t adding any value. And when you’re using the base, the arm isn’t adding any value.

It has to be a much higher value application to justi the spend because

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you’re only using half the robot at any moment. There’s some challenges in terms of getting the right price point to be able to do that. But we also see some interesting niches where even with today’s technology, It makes a whole ton of sense to do.

We’re taking a longer view to see what the right strategy is to try and maximize the available market for [mobile manipulators]. It’s a little bit more subtle than I think it looked like than it looks at first glance. If you put a $25,000 robot on top of a $50,000 robot, you need to get a lot of value out of that before it is less expensive than a person pushing a cart.

Is Teradyne still looking to grow its Industrial Automation Group?

We are, and we categorize the kind of acquisitions we want to do into two buckets. The first bucket would be additional segments of the industrial automation market. That would be

things other AMRs [autonomous mobile robots] and 6-axis robots. We have good product offerings and pretty good market coverage in those two areas. But there are a lot of other robot types that we could potentially be looking at.

We are always looking for companies that have excellent technology that would allow us to make more tasks [able to be automated]. How do we expand the market for robotics? If there’s so ware or hardware that allows us to do that, we’re also interested in those kinds of companies.

We have this incredible community with UR+. Just to give you an idea, even though there was a pandemic in 2020, we went om about 211 products in the UR+ community to 308. We have 300 more products in the pipeline to be added om 100 different companies.

That’s one of our biggest advantages in the collaborative automation space is that we are open to collaborate with

other companies and to support their innovations.

We want to be careful about what investments we make — be sure they’re foundational advances to the state of the art. When we looked at bin picking, we saw that most of the existing bin-picking solutions really didn’t have an ability to do good path planning. With [Energid’s] Actin, we felt it was adding a missing piece to that whole market. We still have bin-picking solutions in UR+ community, and our distribution channel still helps facilitate customers that have binpicking problems that are more aligned to those than our own solution. We think we’ve come up with a fundamental advance in technology, so that’s the kind of thing that we want to invest in. RR

It’s not a web page, it’s an industry information site So much happens between issues of R&D World that even another issue would not be enough to keep up. That’s why it makes sense to visit rdworldonline.com and stay on Twitter, Facebook and Linkedin.

It’s updated regularly with relevant technical information and other significant news to the design engineering community.

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