DESIGN WORLD_ROBOTICS HANDBOOK 2022

www.therobotreport.com November 2022

2022 Robotics

Handbook

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11

•

Contents

2022 • therobotreport.com

DESIGN & DEVELOPMENT

COBOTS

08_ Robotics experts weigh in on Tesla Optimus

50 _ Plasma cutting and MiG welding cobots

humanoid

14 _

Overcoming autonomous farming misconceptions in California

20 _ 6 keys to selecting a contract manufacturer 24 _ NASA’s Terrain Relative Navigation: from ideation to commercialization

MOBILE ROBOTS

30 _ How the cloud can improve human-robot interaction

36 _ Mobile manipulator lends a hand at Wuhan Institute of Shipbuilding Technology

SOFTWARE

40 _ Linux embracing Rust will boost robotics community

yield heavy-duty results

MOTION CONTROL

54 _ How motion engineering helps develop next-gen surgical robots

58 _ How terrain semantics help quadruped learn to walk

END EFFECTORS

62 _ Developing a multifunctional, long-arm gripper

66 _ Harvard researchers create soft, tentacle-like robot gripper

SENSING

70 _ Sensor breakdown: how robot vacuums navigate

44 _ Inside Viam’s cloud-based robotics development platform

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THE ROBOT REPORT

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No,

autonomous vehicles

aren’t dead Steve Crowe | Editorial Director, The Robot Report

The hot-take artists wasted no time a er the recent Argo AI shutdown. This was an unexpected move by Ford and Volkswagen, which were the two largest financial backers of the once-promising autonomous driving startup. But shortly a er the news broke, many “experts” already signed the death certificate for the entire autonomous vehicle industry.

However, some of the industry’s leading players have incredible momentum at the time of Argo AI’s demise. Cruise recently expanded its public robotaxi service in San Francisco, announced it’s bringing robotaxi services to Austin and Phoenix in the coming months, started testing its Origin ridesharing autonomous vehicle in California and started making autonomous deliveries for Walmart in two Arizona locations.

While I was writing this, Waymo, which has been running a robotaxi service in a limited area of Arizona, expanded its service in downtown Phoenix to include pickups and dropoffs at Phoenix Sky Harbor International Airport. Waymo also recently announced it’s expanding to Los Angeles and continues to test its robotaxi service in San Francisco.

Mobileye went public a er spinning out of Intel. And the autonomous vehicle market in China has several major players doing great work, too.

I’ve been fortunate enough to ride in several different robotaxis over the years, most recently with Waymo in San Francisco prior to our RoboBusiness event. It was a roughly 9-mile ride that took just under 30 minutes. Because I’m not a Waymo employee, there was a human safety driver behind the wheel.

The route we took had a myriad of obstacles, including multiple unprotected le turns, pedestrians crossing streets and sidewalks, bicyclists, narrow streets, double-parked Amazon delivery trucks and construction vehicles cutting us off. As you would hope, the trip was flawless and uneventful. Actually, it was quite boring.

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www.therobotreport.com

Cruise and Waymo have had welldocumented hiccups with their robotaxi services. But anyone who calls what these companies are doing simply “flashy demos” is either being disingenuous or hasn’t experienced the technology first-hand.

I understand Waymo and Cruise have been in San Francisco for years, meticulously mapping and training their autonomous driving stack in geofenced areas of the city. But San Francisco is an incredibly challenging city to drive in.

They should be able to take what they’ve learned in San Francisco and more quickly launch similar robotaxi services elsewhere in less chaotic areas.

This is not to say the industry doesn’t have major challenges. Questions about reliability, revenue and scalability abound.

But declaring the entire industry dead is foolish. New technologies rarely develop the way many expect. And the earliest players o en don’t win out.

THE ROBOT REPORT

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NEW!

I rode in this Waymo robotaxi for about 30 minutes around San Francisco.

4 AXIS SERVO from

2.25”

| Steve Crowe

During the five-plus years that Ford owned the majority of Argo AI, it spent nearly $2.7 billion on R&D. During that same time, Ford also generated about $850 billion in sales, $43 billion in operating profit and spent about $39 billion on both capital outlays and R&D. Ford said the plan is to shi its focus away om funding Argo AI’s development of Level 4 autonomous driving technology and towards creating its own Level 2 and Level 3 driving systems. “We’re optimistic about a future for L4 advanced driver assist systems, but profitable, fully autonomous vehicles at scale are a long way off, and we won’t necessarily have to create that technology ourselves,” Farley said.

Certainly, the consolidation will continue.

But other companies will stay the course.

Waymo, for example, could have multiple revenue streams thanks to its robotaxis and autonomous trucking business. And despite less confidence om venture capitalists, new players will come to market with new strategies and technologies.

Chris Urmson, co-founder and CEO of Aurora, a self-driving company that has partnerships with Toyota and Uber, shared his thoughts about Argo AI shutting down.

He said the industry has never been closer to delivering on the promise of self-driving vehicles. And he shared a couple of reasons

DESIGN WORLD

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why the technology is needed.

“Over 40,000 people died in car crashes last year, up 10% om the previous year.

Trucking is an over $700 billion business, moving over 72% of the nation’s eight by weight, but we just don’t have enough drivers to move it all. It’s also dangerous—there are almost half a million accidents involving trucks a year,” Urmson said.

Urmson, of course, is biased since he has a major stake in this game. So, of course, he’s going to say positive things a er a negative situation. And there are rumors that Aurora is running out of money and is looking to be acquired. But I think he’s right.

Just because Argo AI failed doesn’t mean every other company will suffer the same fate. Ford might have simply had a change of heart with its strategy, but it’s also OK to say Argo AI fell behind the competition in recent years. Did the team get the technology as far as it could? We’ll learn more in the coming days and months.

Albeit slower than originally expected, there are autonomous vehicle companies making tremendous strides. Argo AI’s shutdown doesn’t signal the end of the industry. It just reiterates that this technology is difficult to develop. And the path to fully driverless vehicles is being re-routed yet again. RR

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November 2022

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THE ROBOT REPORT

11/4/22 11:04 AM

I T ’ S W H AT ’ S O N T H E I N S I D E T H AT C O U N T S ® E L E C T R O N I C S

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Robotics experts weigh in on

Tesla Optimus humanoid Elon Musk and Tesla showcased a working prototype of the Optimus humanoid robot, and the robotics industry was quick to react.

Steve Crowe • Editorial Director, The Robot Report

| AdobeStock

Elon Musk recently unveiled at Tesla AI Day the company’s much-anticipated Optimus humanoid robot. Last year, of course, the “robot” was simply a human dressed in a robot suit. This time, Tesla briefly demoed a working prototype that walked, waved, and danced on stage. Tesla also played videos that showcased the Optimus prototype doing different tasks, such as picking up boxes in a warehouse and watering a plant in an office.

Musk claimed Tesla will be able to leap og other humanoid developers, such as Agility Robotics and Boston Dynamics, in part because Optimus uses the same neural networks as Tesla’s Autopilot technology. Musk predicted Optimus’ price will be less than $20,000 when it’s commercialized.

Of course, the robotics industry was watching Tesla AI Day in earnest to see exactly what Optimus would be this time around. Many experts om the robotics industry shared their thoughts on social media during and immediately a er the event ended. We have collected some of those thoughts below.

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THE ROBOT REPORT

11/4/22 9:23 AM

Tesla CEO Elon Musk unveiled the Optimus humanoid robot at Tesla AI Day on September 30.

Optimus briefly walked, waved, and danced on stage. | Tesla

Ryan Gariepy, CTO, Clearpath Robotics & OTTO Motors Great credit to the engineering team who pulled it off, of course, but I’m not seeing anything particularly impressive here which we can attribute specifically to Elon or Tesla.

Specifically, there were lots of arguments ahead of the unveil that one or more of the “Tesla FSD stack/data/ EV experience” was going to let them leapfrog all of the other companies in the space, and I didn’t see any of that.

There’s also lots of credit going to Elon for saying that “it’s going to cost 20K,” which reminds me of all the 3D lidar companies that have been saying “our lidar will only cost [US] $100 ... if you pre-order 100K+ units.”

In short, I’d bet that any decent university or corporate robotics lab with a similar budget and an active PR team would be able to pull this off.

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Keerthana Gopalakrishnan, Roboticist, Google Brain Optimus reveal: Mind blown with the velocity of the team and the very sleek hardware design elements. Yet to see autonomy. Surprised Tesla went full Boston Dynamics mode with classical

www.therobotreport.com

control/planning when it’s been around for a while.

Dennis Hong, Professor, UCLA The energy and excitement at AI Day 2 was amazing. “AI Day” is actually a recruitment event, and in that sense, I

November 2022

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Development Boston Dynamics’ Atlas is widely recognized as the most sophisticated humanoid robot ever built.

Boston Dynamics uses Atlas as a research platform to push the limits of wholebody mobility for robots. | Boston Dynamics

believe the event was a big success.

I am aware of critics who say that the prototype had nothing new that they hadn’t seen elsewhere, and that there are other, more impressive humanoids.

There are also people who have doubts about the aggressive timeline Elon had proposed, and I do not necessarily disagree with them.

That being said, I am a true believer of the future with humanoid robots and their eventual applications; that they will be used in our everyday lives “one day” and make our lives better. And for that to happen, we need to start somewhere, and project Optimus is just that.

What was most impressive to me was what the Optimus team was able to accomplish in such a short period of time. If you are in this field, you would agree, too. The prototype they have created will serve as an excellent beginning platform for them to learn from and to build upon.

I would say this is their good first step towards something big—if Tesla truly commits to put its resources, time, and efforts into it long term. The company has great engineers, and with the newly recruited talents, I am even more excited to see what they’ll be able to accomplish next.

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Georgia Chalvatzaki, assistant professor at Technische Universität Darmstadt Looking at the Tesla bot as a roboticist, I am impressed by what the engineers achieved for this prototype in a year.

However, the behaviors demonstrated are less impressive than that of Honda’s Asimo from 20 years ago. What excites me is the idea of cheap and accessible hardware.

Will Jackson, founder and CEO, Engineered Arts I was fortunate enough to have been at the Optimus unveil in Palo Alto. Had a chance to check out the design and talk with many of the engineers involved.

It’s generally an old-school series chain of actuators, excepting wrists and ankles, which are differential roll/pitch. Nothing novel in the kinematics. No mechanical energy storage, parallel springs, etc.—it’s not going to be efficient unless they change that.

Two main classes [of actuators]: rotary and linear. Rotary is an integrated strain wave gear reduction (harmonic drive).

Linear actuators are more interesting, integrated inverted roller screw drive.

Playing with a drive, it’s not inherently very transparent—you certainly wouldn’t get a free swinging knee or hip joint. All the actuators look like they need and use active force loops. This looks nasty to me: It will complicate the control, reduce efficiency, and raise complexity. If they really want to get to [US] $20,000 a unit, this is not the way to go.

Hands: One novel feature here is a clutch on the finger flex/extend. Playing with an actual hand, it felt like it worked quite nicely to decouple the finger from the drive; this will have advantages. The design of the hands leaves very little room for a compliant (soft) layer, and bare metal hands are a terrible idea—try picking up a glass of water with two metal spoons and you will know what I mean. No finger ab/adduction, only two DOFs in the thumb—no chance of doing anything human-level dexterous here.

[Tesla has] a large team of highly capable engineers and will iterate quickly to better designs—if they can find a leader for the mechanical architecture with better ideas than they are currently showing.

The elephant in the room is the application ideas, which are frankly ridiculous. I am amazed that Musk can address an audience so rapturously enamored with the idea of a humanoid and totally fail to recognize that their desire to interact with a robot is the

The energy and excitement at AI Day 2 was amazing.

“AI Day” is actually a recruitment event, and in that sense, I believe the event was a big success.

— Dennis Hong, Professor, UCLA

www.therobotreport.com

THE ROBOT REPORT

11/4/22 9:19 AM

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Development killer application. Did he think they were applauding because finally the world will have a humanoid robot that can lift a pipe in a car factory?

Summary: An extraordinarily brave live demonstration of a herculean effort that sadly lacks novelty and imagination.

Hopefully we will see a course correction by the time of next year’s event.

Mikell Taylor, principal technical program manager, Amazon Robotics There is no “doing it first” with an allpurpose humanoid robot that can 1:1 replace people. That’s simply not where the tech is now and it’s not where it’s going to be in the next 10 years, I will say with complete confidence.

Those of us in the industry were watching to see if Tesla somehow knew something we didn’t know. And …

nope. They did not. The tech isn’t there for anyone. And that’s why the more generous takes some of us try to make for the sake of the engineering team are “you did as well as you could and you’re figuring out the state of the art quickly.”

It’s not that team’s fault. There was no way to achieve an impossible goal.

Here’s the thing: What humanoid robotics needs is a realistic vision. A “here is exactly where this, a humanoid form factor, is needed instead of literally anything else” vision that acknowledges the realities of the technology. But that’s not what it was. It was “today we have this, in a year we’ll have sci-fi.” And that’s just not going to happen. Frankly, it’s disappointingly un-visionary. “Everyone else just hasn’t engineered hard enough” is not a vision. It’s ignorance. RR

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Overcoming autonomous

farming misconceptions in California

Monarch Tractor’s recent petition to Cal/OSHA may have been denied, but this outcome is not the setback many fear.

Karli Petrovic

On June 16, 2022, Cal/OSHA’s 4-3 opinion to deny petition 596 was the decision heard around the agricultural world. Filed by Monarch Tractor on December 15 of the previous year, petition 596 sought to clari the state of California’s agricultural equipment regulations as they relate to modern self-driving tractors.

Monarch Tractor — the company behind a fully electric, driver-optional tractor — argued that the current regulations, which were dra ed in the 1970s, fail to account for the many ways tractors and other farming equipment have advanced in the 21st century. Although the Occupational Safety and Health Standards Board staff agreed with Monarch Tractor that the language that appears in Title 8, section 3441(b) may be outdated, this opinion was not enough to convince Cal/OSHA to approve the petition.

Current regulations unchanged Many industry experts lamented this decision as a step backward for California agriculture. Without a quicker way to introduce the latest technologies on the farm, they argued, the largest agricultural state in the U.S. would surely be le behind.

Autonomous tractors and other ag robotics are, a er all, a necessary part of feeding a growing population in the face of labor shortages, rising input costs, fewer resources and increasing environmental concerns.

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THE ROBOT REPORT

11/4/22 9:05 AM

Full-scale production of Monarch Tractor’s MK-V all-electric, autonomous tractor is scheduled to begin in Q1 2023. | Monarch Tractor

While it is true that advancing technologies provide solutions to many of these problems, the decision to deny Monarch Tractor’s petition does not extend the timeline for bringing new autonomous equipment into the field. Quite the opposite. When Monarch Tractor filed the petition, the company sought to speed things up. The Board’s opinion merely maintains the status quo.

Monarch Tractor’s CEO Praveen Penmetsa noted, “The decision does not change current regulations.

There are already autonomous technologies operating on farms across the country. Monarch Tractor’s petition aimed to make the adoption of autonomous technologies on the THE ROBOT REPORT

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farm easier, faster, and with less paperwork for farmers.”

Although Monarch Tractor brought a strong case to the Board and hoped that its petition would be approved, this decision did not negatively impact the ways the company and Cal/OSHA are collaborating at present.

This includes the temporary experimental variance that’s been in effect since the summer of 2021. Through this variance, Monarch Tractor works with Cal/OSHA and Wente and Crocker & Starr vineyards to gather data in support of the conclusion that autonomous tractors provide the same level of safety as tractors managed by human operators.

According to Penmetsa, “Monarch Tractor is the only company operating under this type of variance in the ag sector, despite www.therobotreport.com

various companies rolling out autonomous agriculture equipment. Despite the ruling, Cal/ OSHA and Monarch Tractor continue to work closely under the temporary experimental variance to clari the regulations, as well as establish safety processes with key milestones for other tech providers to follow specifically in farm environments where autonomous equipment is expected to work in close proximity to farm workers.”

Safety has long been a priority for Monarch Tractor, as the company has shared information and collaborated with Cal/OSHA for the last three years. At the time of the petition, Monarch Tractor revealed that its technology has “operated 760 hours with zero incidents of any kind.” This provides a stark contrast to the labor statistics Monarch Tractor included in the petition: November 2022

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Development John Deere launched in 2022 its 8R fully autonomous tractor. The 8R has six pairs of stereo cameras that use a deep neural network to classify each pixel in approximately 100 milliseconds and determine if the tractor continues to move or stops. | John Deere

“According to the Bureau of Labor Statistics, agriculture is the deadliest profession in the United States and in the State of California with roughly 40% more deaths per 100,000 workers than any other industry [Fatal Occupational Injuries in California 2013-2019 (CFOI) Report. Pg, 18]. Tractor accidents are a leading cause of serious injury,

accounting for about one-third of farm fatalities annually. The majority of tractor fatalities are om side or rear rollovers that can occur due to a range of factors including improper weight distribution, user error, and bad terrain conditions. Rollovers can happen to any operator; roughly 80% of fatalities involve experienced operators [NASD Tractor Overturn Information].”

Latest technologies Monarch Tractor has outfitted its equipment with the latest sensors and camera technologies. The company referenced these advances when comparing the outdated language in Title 8, section 3441 (b) to what autonomous tractors can do now. Monarch Tractor’s petition argued that the technology in self-propelled tractors available today

A letter to Cal/OSHA Stephanie See, director of state government relations for the Association of Equipment Manufacturing (AEM), wrote a letter to Cal/OSHA in support of updating the regulations. That letter is reprinted in its entirety here: AEM is the North American-based international trade group representing off-road equipment manufacturers and suppliers, with more than 1,000 companies and more than 200 product lines in the agriculture and construction-related industry sectors worldwide. The equipment manufacturing industry supports 2.8 million jobs in the U.S. Equipment manufacturers also contribute $288 billion a year to the U.S. economy.

We appreciate the opportunity to express our support for amending California Title 8, Section 3441 (b) to promulgate appropriate safety regulations for the use of autonomous farm equipment.

Off-road autonomous equipment is here and destined to play an increasing role in agriculture. The governing regulations were last reviewed in 1985, long before the technology was developed to create autonomous farm equipment. Within the next five-to-ten years, autonomous tractors will be widely available on the market, thus the time is right to begin examining the regulatory amework that would allow this equipment to operate safely.

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Benefits of autonomous equipment Agricultural use of autonomous equipment promotes the reduction of worker exposure to a variety of hazards: • Driverless sprayers reduce incidents where employees are exposed to pesticides during their application.

• The undistracted nature of onboard sensors can provide an excellent level of detection for monitoring the environment to prevent incidents.

• The use of autonomous tractors can remove workers om environmental health and safety hazards such as dust, heat, and vibration, keeping workers healthier.

• Autonomous machines can perform physically demanding labor such as hauling heavy loads om fields, or shaking nuts om trees, thus lessening the wear and tear on a worker’s body.

Autonomous uit pickers can keep laborers om ladders, reducing fall hazards. Furthermore, the diversity and inclusion benefits of off-road autonomy should not be overlooked. The nature of many employment opportunities on California farms restricts who can apply based upon the applicant’s physical abilities. Together, AEM and Cal/OSHA

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can enable off-road autonomy to pioneer farming operations that create employment opportunities for workers om an expanded range of physical abilities, including disabilities, and professional backgrounds who otherwise cannot be “reasonably accommodated.”

Safety data Due to the emerging nature of this equipment, we do not have extensive data on the safe usage of autonomous farm equipment, however, our industry can draw on the previous experiences of related industries and is currently studying the safety of autonomous farm equipment through a partnership with Cal/ OSHA. Since 1994, over 900 Caterpillar and Komatsu mining trucks outfitted with autonomous systems have hauled 8 billion tons of material across 90 million miles with zero system-related lost time injuries incurred. Employees deployed at these work sites operate in cooperation with the autonomous machines, resulting in a demonstratively safer environment that reduces human exposure to hazards.

Monarch Tractor, an AEM member company, is currently conducting research through an experimental variance period, granted by Cal/OSHA in August 2021 that will evaluate the safety of autonomous tractors through various conditions over several years. Once complete, this data will allow stakeholders to accurately adjudicate the safety of this technology in the environment in which it will be used.

We also encourage the Board to review other data points with similar equipment operating in similar environments: • Through their seeding, spraying and spreading operations, Raven Applied Technology has accumulated 8,000+ hours of operational time, covering 69,000 acres with 18 machines.

• According to its website, Blue-White Robotics, an autonomous agriculture equipment manufacturer, has 10,000+ hours of safe operation.

• KeyBanc Capital Markets published its first Autonomous Truck Technology Dashboard. As of March 1, 2022, KeyBanc counted 147 autonomy-equipped trucks, traveling an estimated 4.1 million miles. KeyBanc reports no unsafe driver violations resulting om 40 roadside inspections in February.

• Schnuck’s Markets announced that it is rolling out artificial intelligence-powered robots to all 111 of its stores in Illinois, Indiana, Missouri and Wisconsin. These robots will be interacting with customers that have had no special training to interact with autonomous machines.

• Because the technology used in autonomy has proven its reliability, the 27 countries of the European Union are considering allowing the self-certification of autonomous agricultural vehicles.

may participate in the process, allowing all viewpoints and comments to be addressed before the standards are finalized and published.

The International Organization for Standardization (ISO) addresses highly automated agricultural machines (HAAM) in ISO 18497 Agricultural Machinery and Agricultural Machines – Safety of Highly Automated Agricultural Machines – Principles for Design (First Edition, 2018). ISO 18497 is a performancebased standard that specifies the principles in the design of self-driving tractors to achieve safe operation. To be compliant with ISO 18497, self-driving tractors must contain, at the minimum, all of the following features into their design: • A perception system capable of detecting and locating persons or other obstacles relative to the machine • A perception system capable of locating and positioning the equipment to prevent unintended excursions beyond the boundary of the working area • Be able to ensure that there is no obstacle in the hazard zone prior to moving • Give audible or visual alarms and enter its defined safe state when an obstacle is detected, or an obstacle enters its hazard zone • Have the means to enable a local or remote operator to stop or start highly automated operation • Allow for adequate supervision by a local or remote operator ISO 18497 is currently undergoing revision, which we anticipate will be complete by the end of 2023. The technical committee will meet at AEM’s headquarters office in Milwaukee, WI in the fall. We invite you to join us for this meeting.

We would also like to invite you to attend FIRA, USA in Fresno, Oct. 18-20. FIRA, USA is the leading industry event in ag robotics, and will host in-field robot demos at the California State University, Fresno campus farm. Attendees will have the opportunity to watch dozens of robots working in real conditions. By bringing this academic community together face-to-face in Fresno, FIRA USA aims to set priorities and focus on solving some pain points.

Conclusion AEM is strongly in agreement that updating this regulation is needed for California to continue to be a world leader in both agriculture and the innovations that support it. AEM looks forward to collaborating with Cal/OSHA to develop a forwardlooking and effective regulation that ensures California workers have the safe workplace they are entitled to while preparing for the inevitable future that off-road autonomy is ushering in.

Design and operation prescribed by international standards Autonomous agricultural equipment is designed and tested to international standards that are developed under an open and balanced consensus process. Any materially interested party

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Development

functions as an operator, which means the vehicle performs safely without an operator inside the tractor. Instead, the operator would manage the autonomous tractor’s work om a distance.

“Monarch has incorporated several additional safety features with direct input om Cal/OSHA,” Penmetsa says.

“Tractors are speed limited in autonomy mode to 3mph and feature digital safety guardrails that deploy whenever a human is within 10m (33 ) of the vehicle. Monarch Tractor also enables 360-degree cameras to help protect the driver, surrounding people, livestock, implements, and crops near the tractor om crashes. The tractor actively addresses power take-off (PTO)-related injuries on the farm by utilizing a camera above the hitch that will stop the tractor and cut off power to PTO if an object or person comes in close proximity to the tractor.”

Gathering data With the temporary experimental variance in place until August 2026, Monarch Tractor, Cal/OSHA and Wente and Crocker & Starr vineyards will continue gathering data. When the variance ends, the data will be used to evaluate whether the current regulations should be changed or updated. Many hope that this information will help make the case for quicker, easier adoption of autonomous farm technologies without sacrificing worker, bystander or animal safety. Penmetsa is committed to continuing this important work.

“Monarch Tractor continues to partner with other agricultural groups and California agencies on clarification of the regulations applicable to autonomous operations in agriculture,” he said.

“Monarch Tractor will also continue to work with Cal/OSHA under the current variance to provide the data requested for evaluation under the variance as the leader in global farm autonomy.” RR

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6 keys to selecting a

contract manufacturer Jim McCall • director of manufacturing, Cirtronics

Trust, values, goals, and complementary skill sets are a strong foundation for long-term, successful commercialization relationships.

Your manufacturer should feel like an extension of your business.

Manufacturing relationships are just that – relationships. Since your contract manufacturer (CM) will be working alongside you, actively learning about your robotic system and the requirements specific to your company and application, your partnering decision needs to be deliberate and extend beyond bottom-line cost comparisons.

The following key considerations are shared as a guide in supporting your selection of a manufacturer who will co-create a path – tailored to you and your robotic system – toward successful commercialization. Each step om onboarding to production should feel like it was made just for you, your priorities, and your product.

So, what are the considerations for choosing a partner who feels like an extension of your business? And what kinds of engagement and interactions will support a win-win relationship?

1: Your capabilities Start by assessing your company’s unique capabilities and strengths. Then when you look for trusted partners, seek organizations whose areas of competence and qualifications complement yours. By collaborating with well-aligned external resources, your team can focus on your

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company’s core competencies – the engineering and innovative expertise that brought your robotic system to manufacturing readiness.

2: Reliable supply chain Trust your partner’s expertise. If you’ve been building prototypes or low quantities inside your organization or with a prototype fabricator, or even if you’ve been working with another manufacturer, your new CM should expertly audit your bill of materials against known or forecasted uncertainties in material availability.

By working with you, they can identify supply chain strategies that provide a balance of stability and flexibility for the parts you need to build your product at scale, over time, within the specifications required. Sourcing strategies could include pre-buys/bulk buys, binding forecasts, and the identification of

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multiple validated sources for critical components.

3: Manufacturing handoff Documentation and optimization of build procedures are required for a successful handoff to production. Active and open knowledge transfer with your manufacturer is critical. Cooperative building (co-building) is one example of best practices. Co-building is building a product directly alongside your manufacturing company’s engineers.

Processes are validated, any changes that are required to increase build efficiency or improve ease of assembly can be made, and the final process is fully documented.

The result is the complete set of experience-based documentation required to manufacture and test the product. This validation process, documentation creation, and hands-on www.therobotreport.com

A Cirtronics team is seen here building telepresence robots from Ava Robotics, which also develops robots for disinfection and security applications. || Cirtronics

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experience will accelerate your product’s ramp to full-scale manufacturing. And the process of building products together builds the relationship as well. It fosters trust, collaboration, and transparent communication between your company and your manufacturer.

4: A path to scale Ensure that your partner has the right capabilities and adaptability for successful commercialization at scale.

Manufacturing partners should provide a path to scale to meet increasing demand for your product. If you have units in the field, do they have the capacity to meet forecasted demand? If you’re transitioning into your first production run, does your CM have the capacity to scale with you? Can they creatively adapt to fluctuations in demand? Depending on your needs, can they handle managing and manufacturing multiple models (SKUs), drop-ship to customers, or even provide direct delivery?

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5. Communication Communication with your manufacturer is critical to your successful partnership.

The intention of all communication – from both sides – should be proactivity, honesty, and transparency. You should be able to access information about any aspect of the manufacturing process of your product that you would like to know, including part sourcing, product build status, and delivery status.

6. Company culture You might be thinking, “culture?

What does the culture of my contract manufacturer have to do with building my product? “ Authentic culture is not a tagline.

It’s more than just a mindset. It is a way of being and acting in the workplace and with customers and partners. A strong culture creates an atmosphere of service, where excellence and integrity begin within the company, and are reflected in every interaction with you and in every action taken on your behalf.

It’s vital that the culture and values of your manufacturer align with your

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American Robotics became the first company approved by the Federal Aviation Administration (FAA) to operate automated aerial drones without humans on site.

Cirtronics is building the ScoutBase, a weatherproof charging and data processing station, for American Robotics’ Scout drones. | Cirtronics

company’s vision. Shared values enable mutual trust. Trust is necessary for creating and maintaining a strong and successful relationship between your two companies.

Conclusion Selecting a partner is not a one-size-fitsall approach. It takes time and energy to find the right manufacturing relationship.

The manufacturing partner you choose is key to the successful commercialization of your product. Leveraging insourcing as a model, they will act as an extension of your business. Your partner’s process, style of work, and communication must be aligned with yours. Trust, values, goals, and complementary skill sets are a strong foundation for long-term, successful commercialization relationships. RR

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NASA’s Terrain Relative Navigation: from ideation to commercialization

NASA

Terrain Relative Navigation facilitates increased landing accuracy and helps spacecraft avoid surface hazards. It allows the exploration of other worlds, like Mars and various moons, in areas previously considered too difficult for spacecraft to land.

Jezero Crater on Mars is full of hazards such as rocky hills and smaller craters, making it a challenge to land in – until NASA’s Mars 2020 mission with the agency’s Perseverance rover did just that with the help of improved navigation technology.

Terrain Relative Navigation (TRN), a technology developed by NASA, facilitates increased landing accuracy and helps spacecra avoid surface hazards. It allows the exploration of other worlds, like Mars and various moons, in areas that were previously considered too difficult for the spacecra to land. TRN uses a camera to correlate visible terrain features to onboard maps, calculating relative positions and altitudes during descent within seconds. Furthermore, TRN can autonomously navigate spacecra away om medium to large hazards within a target landing zone to ensure a safe landing for a successful mission.

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Having proven the value of TRN’s precision landing capability, researchers are now combining TRN into several other entry, descent, and landing (EDL) and hazard detection technologies for missions to the Moon and beyond.

During the Apollo missions, astronauts looked out the windows of the spacecra to identi landmarks to determine their estimated position and manually choose a landing spot away om hazards, such as craters, dunes, and rock fields. For safe and

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A diagram of the key steps in the Mars 2020 mission’s entry, descent and landing on Feb. 18, 2021. | NASA/JPL-Caltech

successful robotic and eventual crewed Mars missions, spacecraft require a more accurate and autonomous system.

A “high-precision” landing is one where the spacecraft can touch down within about 160 feet (50 meters) of its target. Before TRN, high-precision landing capabilities did not exist. Mars 2020 was the first robotic mission to Mars to use vision-based navigation for a safe and precise landing. In previous rover missions, the location was estimated through data provided by the Deep Space Network, NASA’s international array of giant radio antennas, with an estimated error of up to nearly 1.25 miles (2 kilometers). Harsher terrain – like that found within Jezero Crater on Mars – provides opportunities for diverse

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geological sampling, so missions without high-precision landing capabilities must choose safer landing sites over sites with the potential for enlightening discoveries.

Advantages of TRN “If we didn’t have TRN, the probability of landing safely at Jezero Crater was about 80 to 85%. With TRN, the probability increased to 99%,” said Swati Mohan, guidance, navigation, and control operations lead for NASA’s Perseverance rover at JPL. High Precision Position Estimation: As high as 2.6 miles (4.2 kilometers) above the surface, the Mars 2020 TRN system’s onboard camera started taking realtime photos of the terrain and matching landmarks to preloaded maps to provide

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spacecraft position, like GPS, all within 10 seconds. For the Mars 2020 mission, TRN improved the location estimate accuracy from 2 miles (3.2 kilometers) to 0.025 miles (40 meters) or better.

Multi-Point Landing: With the addition of TRN, a spacecraft has options for landing sites.

After the position estimates are calculated, TRN can choose the safest landing position within its target landing zone and use the small amount of fuel left onboard to divert, avoiding medium to large-size hazards. With more fuel, the spacecraft could perform larger adjustments to provide other landing options.

With multi-point landing capabilities, instead of arriving at a safe location and driving to the science site, a rover can land directly at the target destination.

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Development NASA’s Perseverance Mars rover snapped this view of a hill in Mars’ Jezero Crater called “Santa Cruz” on April 29, 2021, the 68th Martian day, or sol, of the mission. | NASA/JPL-Caltech

Simple Design: TRN’s simple, costeffective design is advantageous for missions, not only in functionality but also volume and power. TRN only has two main compact components, a camera, and a computer. Although the computer needs to calculate position estimates and recommendations in addition to processing and storing images, it uses relatively low power. This allows greater allocation of power to other science payloads and functional systems.

Technology Development Pre-2014: Inception and Early Development: As scientists narrowed down the list of target locations on Mars to collect precious samples, many of the most interesting sites had hazardous terrain where it would be difficult to land a rover. NASA JPL recognized the critical need for precision landing capabilities and came up with the concept of TRN. TRN was advanced over years with multiple funding sources through various NASA programs.

2013-2014: Flight Demonstration: In 2014, through two suborbital flights funded by STMD’s Flight Opportunities program, TRN was tested as part of the Autonomous Descent and Ascent Powered-flight Testbed (ADAPT) aboard Masten Space Systems’ Xombie vertical

takeoff, vertical landing rocket in the Mojave Desert. During descent, TRN successfully navigated Xombie’s course by recognizing terrain features and providing relative position to the target landing site.

2015-2017: Technology Maturation and Growth: STMD’s Game Changing Development (GCD) program advanced TRN as part of the Intelligent Landing System, improving capabilities for safe landing for a potential future mission to land on Europa, one of Jupiter’s moons.

In 2017, TRN was demonstrated again on Masten Space Systems’ Xodiac rocket as part of STMD’s CoOperative Blending of Autonomous Landing Technologies (COBALT) project.

2018: Commercialization: STMD awarded two TRN-related Tipping Point technology development award to

Astrobotic Technology and Blue Origin to develop TRN solutions for lunar missions.

2019-2021: Technology Demonstration: STMD’s Technology Demonstration Missions (TDM) supported further maturation of TRN, including several design reviews, an additional helicopter demonstration in 2019 in Death Valley National Park, and integration of the software, algorithms, and sensors into a single system before the Mars 2020 launch.

As TRN evolved, it was also implemented for other projects. GCD’s Safe & Precise Landing – Integrated Capabilities Evolution (SPLICE) project included TRN in its suite of technologies around precision landing and hazard avoidance. In 2019, the SPLICE TRN was tested onboard Masten’s Xodiac rocket as a critical step toward follow-on

NASA’s Perseverance rover was able to use its new Terrain-Relative Navigation technology to avoid hazards and find a safe place to land in Jezero Crater on Mars. | NASA/JPL-Caltech 26

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flight testing in 2020 and 2021 through a GCD and Flight Opportunities-supported suborbital flight demonstration aboard Blue Origin’s New Shepard rocket.STMD’s GCD is funding a Lunar Digital Elevation Maps, Mapping, Modeling, and Validation effort for improving lunar digital elevation maps for TRN and hazard detection systems. In 2020, Intuitive Machines was awarded an STMD Tipping Point related to TRN image and map processing.

Infusion and commercialization Mars Exploration Infusion: TRN fulfilled a mission-critical capability for Mars 2020, enabling a safe landing at the preferred science location to meet mission objectives.

Perseverance’s main goals are to study the geological environment of the landing area, seek signs of ancient microbial life, and collect precious Martian samples for possible return to Earth. Studying Martian terrain and habitability will further prepare NASA for future crewed Mars missions. At least 13 other STMD-supported technologies are also onboard the Perseverance Rover, including MOXIE, MEDLI2, Motiv Robotic Arm, and more.

Lunar Exploration Commercial Infusion: Astrobotic is working with JPL under an STMD Tipping Point to integrate parts of the Mars 2020 Lander Vision System into a commercial lunar TRN solution called OPAL. The maps for TRN are critical to the success of high-stakes missions to the Moon. Lunar TRN maps are significantly larger in extent than those for Mars due to the shape of the lander descent profile. The sweeping shadows at the poles where future lunar missions will land provide further challenges. Astrobotic’s “bolt-on” solution incorporates all flight hardware and software, as well as tools for 3D terrain modeling and real-time physics-based lighting simulation required for generating and validating accurate TRN maps for precision lunar landing.

OPAL will complete a technology demonstration on Peregrine Mission 1. Astrobotic will also use TRN to support the landing of NASA’s Volatiles Investigating Polar Exploration Rover (VIPER). Both landings support deliveries as part of NASA’s Commercial Lunar Payload Services initiative.

Blue Origin collaborated with JPL and Johnson Space Center to mature critical technologies that enable safe and precise landing for lunar missions through an STMD Tipping Point. This award matured several of NASA’s descent and

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landing sensors, such as TRN, including a flight demonstration aboard its New Shepard vertical takeoff, vertical landing suborbital vehicle. Blue Origin’s TRN solution will demonstrate landing capabilities necessary for enhancing lunar missions and create new commercial opportunities for planetary exploration.

Future opportunities: planetary exploration TRN is a part of GCD’s Intelligent Landing System (ILS), which would support future missions to Europa. Unlike Mars and the Moon, there aren’t high-resolution images of Europa’s surface, so a vision-based navigation sensor alone would be insufficient. Furthermore, a spacecraft landing on Europa would encounter not only terrain hazards, but also a high radiation environment and limited onboard resources. Therefore, the ILS combined several precision landing, navigation, and hazard detection capabilities designed to ensure a successful Europa landing mission. Combining TRN with other technologies, a spacecraft could further reduce dangerous terrain risks, while capturing photos of the surface and determining velocity of the spacecraft. ILS would also be able to generate high-elevation maps of the surface, beneficial for future missions as well.

The GCD SPLICE project includes TRN within a broader suite of technologies for safe and precise touchdown of landers that can be leveraged for future robotic and human missions to the Moon, Mars, and other planetary exploration. The technologies include high-resolution lidar sensors, high-performance computing, and advanced algorithms, which together enable a lander to detect small, basketball-sized hazards (20-30 cm) during descent toward touchdown and to do so even in the presence of unlighted or shadowed terrain where cameras are unable to acquire imagery. Working in tandem, the suite of sensors in the SPLICE projects can enable even larger landing adjustments on future missions to target safe landing in even more hazardous terrain that has high scientific and exploration potential. RR

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To optimize their effectiveness, increase human-robot collaboration and reduce the risk of mishaps, autonomous mobile robots must understand the social behavior of human coworkers.

can improve human-robot interaction Melonee Wise • VP of Robotics Automation • Zebra Technologies

Robots are finding their place alongside people in many work environments, including factories, warehouses, retail stores and even hospitals. As they do, we need to make it easy for people to trust robots, and for robots to take the right cues om humans.

This is especially true when autonomous mobile robots (AMRs) are in the mix, as these dynamic robots are just as the name states – autonomous. There is no one standing off to the side or in a backroom controlling the AMR with a remote control or traditional human-machine interface (HMI). The AMR is programmed to do a certain job and then is sent off to complete it – much like a human goes through a standard onboarding process and is then trusted to work independently.

Given the eedom that both AMRs and humans have to go about their business without much oversight, we must ensure they know how to interact with one another. We must teach them both proper social behaviors.

A different point of view Teaching robots how to act more like humans might make some people nervous.

But it is necessary given how they must interact with one another to keep workflows running smoothly in fast-paced, high-stakes supply chain operations. If you are to deliver to customers what they need, when they need it, everyone must be able to get along. We must show workers that AMRs know when to engage and when to keep their distance, which means we need to teach AMRs what’s okay and what’s not.

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www.therobotreport.com

THE ROBOT REPORT

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Multiple sensors ensure Fetch Robotics’ CartConnect robots safely navigate between locations and work safely alongside people, forklifts, and other material handling equipment. | Fetch Robotics/Zebra Technologies

But before we can do that, we must ensure AMRs can see, understand, and react to what is happening around them. They cannot be in their own world like many robots are today – seeing only “myself,” “obstacle” or “free space.”

Likewise, human workers must be able to look at what is happening around them from a different perspective.

Their world cannot just be comprised of “myself,” “automation equipment,” “fixed infrastructure,” “other workers” and “many unknowns.” They must be able to understand the depth and breadth of the world around them, especially the extent of AMRs’ intelligence and capabilities.

If we don’t change how robots and people think and react to one another, we can fully expect people to feel intimidated, hesitant and unsure

THE ROBOT REPORT

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of themselves when AMRs enter their world. Their minds might trick them into believing a robot is too aggressive or too close – or that it is ignoring them.

Alternatively, they could humanize the robot too much and make assumptions that could be harmful to all. Your AMRs will end up underutilized, and it will take you longer to get a return on investment (ROI) – if you get one at all.

AMR Benefits Your workers and customers will also miss out on the benefits AMRs offer them. And what are those benefits?

Consider the results of a double-blind Warehousing Vision Study, recently commissioned by Zebra Technologies. In that study, 83% of warehouse associates who work alongside AMRs today claim the autonomous robots have helped www.therobotreport.com

increase their productivity and reduce walking/travel time – a win-win for you and your front-line teams. What’s more, three-quarters of associates say AMRs have helped reduce errors, which is good for you and your customers, while nearly two-thirds (65%) credit AMRs with career advancement opportunities, which helps with employee retention.

So, it is critical we eliminate the biases that result from a “me, myself and I” mindset or preconceived notions. We must ensure neither AMRs nor human workers fall victim to “sole agent syndrome.” The best way to do that is to put our heads (together) in the cloud.

New techniques for teaching trustworthiness For as long as I can remember, robotics automation innovation has been driven by November 2022

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Mobile Robots

The CartConnect robots autonomously pick up and drop off our FetchCarts to any location within facilities with material handling needs. | Fetch Robotics/Zebra Technologies

three things – repeatability, scalability and increased throughput. That’s why many robotic arms, automated guided vehicles (AGVs) and static robots have been built to complete tasks within enclosed work cells, along conveyor lines or in travel lanes.

It is also why most robots are programmed to complete tasks using pre-defined motions, with behaviors fully controlled by a person. Most robots do not need to “figure things out.” They just need to do what a person tells them to do.

AMRs are different, however. While they collaborate and interact with people, they are reliant on a person guiding their every move – telling them when to stop, start or move in a different direction.

They must be able to make both decisions and the right moves, on their own, without a person intervening.

Behaving like people At Zebra Technologies, we use customer scenarios, simulation, and the cloud to understand current AMR behaviors, as well as the changes needed to achieve desired behaviors. We then develop navigation behaviors for the robots, which are based on heuristics/biases that we encode into their navigation and planning code.

These heuristics/biases help AMRs behave more like people socially. For example, robots will drive down the right side of hallways in the United States and the left side of hallways in Great Britain because those are the

social norms in those countries. By encoding these behaviors into AMRs’ navigation and planning, associates have a better understanding of how the robots will behave as they drive around the facility, which results in trust, better collaboration and improved robot performance.

Because our AMRs are managed via the cloud, it is also easy to record data that helps us understand each robot’s performance in the facility. We use velocity and path conformance for low frequency and high frequency interactions as a baseline to understand how changes to the navigation code

A block diagram explaining how the FetchCore cloud-based robotics software works. | Fetch Robotics/ Zebra Technologies

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Mobile Robots improve performance. This allows us to create a vibrant diagram of how each robot performed in different facilities and then make refinements. Using these techniques, we have been able to measure as much as a 54% improvement in robot velocity as it moves through the facility with improved robot social behaviors.

The cloud is a (training) force multiplier Traditionally, when teaching robots their jobs, we would tell them what they need to do, give them operating parameters, execute the motion, then work to adapt their capabilities as needed. Now, thanks to machine learning, convolutional neural nets and other cloud-based technologies, we are providing AMRs with the ability to adapt to the world around them. They can detect and delineate between different semantic objects like people, forkli s, and pallets to make the right decisions about how to behave based on encoded behaviors as well as current sensory inputs.

These AMRs are not working exclusively om inferred guidance… they operating in reality. In other words, the cloud is enabling us to encode AMRs with the social behaviors required to help humans feel comfortable working alongside them. In turn, it becomes easier to teach people the social behaviors required when working around robots.

People will be able to see how AMRs successfully navigate around – or away om – a person who is in their bubble and should not be. They will also see how AMRs can enter their space safely to support them when assistance is needed.

And once robots can be trusted not to go rogue – a er they are equipped with the right social behaviors – then human behavior toward those robots will change. The hesitancy to engage an AMR will fade as confidence in the robot’s “demeanor” grows. People will begin to see and appreciate how AMRs can help them and adoption rates will rise. As a result, companies will be able to increase their use of robotics automation without resistance.

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So, the next time someone tells you the cloud is not doing much for robotics automation, remind them that if it were not for the cloud, AMRs would not be able to work autonomously – or collaboratively with people – the way they do today. The cloud is driving robotics progress. It is truly a force multiplier, at least when it comes to instructing intelligent robots how to behave socially and teaching people that AMRs are iendly. RR

About the author: Melonee Wise is the Vice President of Robotics Automation at Zebra Technologies. She joined Zebra through the acquisition of Fetch Robotics where she was the CEO. Wise was the second employee at Willow Garage where she led a team of engineers developing next-generation robot hardware and so ware, including ROS, the PR2, and TurtleBot. She serves as the Chair of the IFR Service Robot Group, as a robotics board member for A3, and on the MHI Roundtable Advisory Committee. Wise has received the MIT Technology Review’s TR35 and has been named to the Silicon Valley Business Journal’s Women of Influence and 40 Under 40, the Robotics Business Review RBR50, and as one of eight CEOs changing the way we work by Business Insider.

www.therobotreport.com

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Mobile

manipulator

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Wuhan Institute of Shipbuilding Technology A MiR250 AMR equipped with a FANUC CRX-10iA cobot arm has become an integral part of the institute’s demo production line.

Steve Crowe • Editorial Director The Robot Report

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The Wuhan Institute of Shipbuilding Technology (WSPC) is a leading professional and technical institution specializing in advanced training in the fields of marine engineering, modern manufacturing and information technology.

Established 70 years ago, the WSPC is a national training hub working to address China’s skills shortages in engineering and technology. Those shortages were highlighted in China’s national Manufacturing Talent Development Planning Guidance, which notes that three out of the top 10 industries facing the most severe talent shortage gaps are offshore engineering equipment and high-tech shipbuilding, new generation information technology, and high-end computer numerical control (CNC) machine tools and robotics.

The ongoing development and upgrade of smart manufacturing in recent years means that advanced automation technologies, such as autonomous collaborative robots (AMRs), are increasingly used in the field of shipbuilding.

To ensure the technical abilities mastered by its students match the needs of industry, the WSPC has built a complete automated demo production line for marine parts, one that enables it to simulate the real production environment when teaching.

As a key part of its demo production line, the WSPC introduced AMRs om Mobile Industrial Robots (MiR). Working together with FANUC’s CRX-10iA collaborative robot arm, the MiR250 AMR has become a collaborative mobile manipulator responsible for the loading and unloading tasks on the production line.

www.therobotreport.com

THE ROBOT REPORT

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Solution By deploying this advanced intelligent manufacturing line for marine parts, the WSPC aims to improve the overall quality of training for its students, as well as enhance the research and development (R&D) for new production technologies.

The WSPC set out three tasks for the demo production line: 1. Make it an R&D base for its teachers and professors 2. Ensure students master the design, deployment and front-end equipment operation 3. Watch it become an educational and scientific research base for the whole central China region and provide shipbuilding practitioners the opportunity to improve their skills Operating in a simulated manufacturing environment, the MiR250 AMR and FANUC cobot are responsible for completing the logistical tasks along the demo production line, ensuring smooth delivery of materials and spare parts across different stops.

After the manufacturing execution system (MES) places an order, the MiR AMR collects building materials from warehouses and delivers them to the subsequent production procedures. The mobile manipulator can work seamlessly with CNC machines, carrying out a variety of picking and packing tasks.

Building the WSPC demo production line was no easy task. It required close integration between different machines and automation technologies, along with complex high-precision capabilities across the manufacturing process. The stability of the automation technology deployed on this production line is critical.

“The MiR250 AMR is easy and safe to use, and can quickly adapt to the site environment,” said Wang Fan, senior development engineer at Beijing FANUC Electromechanical Co. and developer of the WSPC demo production line. “Thanks

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A MiR250 AMR equipped with a FANUC CRX-10iA cobot arm is responsible for the loading and unloading tasks on the production line at the Wuhan Institute of Shipbuilding Technology. | Mobile Industrial Robots

By deploying this advanced intelligent manufacturing line for marine parts, the WSPC aims to improve the overall quality of training for its students, as well as enhance the research and development of new production technologies. | Mobile Industrial Robots

www.therobotreport.com

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Mobile Robots to the excellent hardware design, the MiR AMR seamlessly connects with each station along the production line.

In addition, the powerful MiR AMR so ware collects production-line data in real time, making it convenient and more valuable for the engineers. They can then analyze a range of information, such as angles and positions, and then apply it to a virtual, three-dimensional

model to create digital twins, centralize information management, and allow robots to be deployed and get real-time optimization.

The demo production line enables WSPC students to complete their training on the entire manufacturing process.

“From learning how to operate an AMR and cobot, mastering equipment configuration skills, to placing ERP

(enterprise resource planning) orders, MES orders, and finally the completion of the processing tasks at each production unit, our students can practice intelligent manufacturing across the whole cycle using this demo production line and go on to graduate as real technical talent,” said Zhou Yu, deputy director of the School of Mechanical Engineering at WSPC. RR

AutoGuide merges with MiR Teradyne companies Mobile Industrial Robots and AutoGuide Mobile Robots recently merged to become a single supplier of autonomous mobile robots (AMRs). The integrated company officially became known as Mobile Industrial Robots (MiR).

Long-time Teradyne executive Walter Vahey took the helm as president. The company’s headquarters will be in Odense, Denmark, where MiR has managed its global operations since its launch in 2013.

Prior to the merger, MiR offered a range of AMRs capable of carrying payloads and pallets up to 3,000 lb. (1350 kg). By combining with AutoGuide, the portfolio will expand to include high-payload AMR tuggers and forkli s that will operate on the MiRFleet so ware.

The new combined company employs 450 employees, including 250 engineers. MiR is already well-established in the AMR market with more than 7,000 AMRs sold in more than 60 countries. The AMRs can pick up, transport, and deliver pallets or other loads automatically and safely in even highly dynamic environments, which is why they constitute a safe and efficient alternative to traditional automated guided vehicles (AGVs), forkli s and pallet trucks.

The newly merged company MiR has a global distribution network with more than 200 partners worldwide. In addition to its headquarters in Odense, Denmark, MiR has regional offices in Boston; Holbrook, New York; San Diego; Chelmsford, Massachusetts; Georgetown, Kentucky; Singapore; Frankfurt; Barcelona; Tokyo; Seoul, and Shanghai.

Teradyne president Greg Smith said the company decided about a year ago that the best way to differentiate its AMR business was to provide a broad product line under a single so ware control.

“We heard over and over again om big customers that they were struggling to implement complex workflows because complex workflows generally need AMRs to interact with each other,” Smith said. “The dominant way people were talking about that happening was through fleet management. That was putting those customers into an uncomfortable position where they didn’t know who to go to when things om multiple vendors didn’t work right. ” Smith said Teradyne wants to take responsibility for the performance of the hardware and so ware and turn to partners to ensure a positive customer experience.

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www.therobotreport.com

“If you look at any AMRs, whether they’re ours or someone else’s, customers can take up to two years to go om an initial pilot to a volume deployment. That’s because they have to work out their processes and adapt to the technology,” he said. “In some cases, like automakers, they have to invent new jobs. They don’t have people who know how to maintain AMRs, so they have to figure out how to fit that into their union regulations. That’s a complex issue to work through. We believe the ultimate destination for AMRs has incredible potential, but we need to simpli the process. And simpli ing that process for us meant putting all of our AMRs under one so ware control and engaging with customers as one organization.

Smith said the bulk of the work went into reworking the sensor suite of the AutoGuide robots to optimize their performance with MiR’s so ware and to enhance the MiR so ware to handle the higher speeds of the heavy payload vehicles om AutoGuide.

“The basic chassis stays the same, but because of the higher top speeds, we need to look much further ahead of the vehicle to react to obstacles and do the right thing.

We had to modi the sensor suite of the AutoGuide robots and enhance the MIR so ware so it could handle the specific requirements of the heavy payload space.

And that’s faster speed and more control of the path the AMRs take.”

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Linux embracing Rust

will boost robotics community

The inclusion of Rust into the Linux Kernel might seem like a small detail, but it couldn’t have come at a better time.

Brandon Minor • Tangram Vision

Linux’s Benevolent Dictator For Life Linus Torvalds recently announced that the Rust programming language would be used in the Linux 6.1 kernel. Currently, the Linux kernel is at preview version 6.0-rc6 (codenamed “Hurr durr I’ma ninja sloth”) so we have a bit of time before we all have Rust powering the kernel, But the mere announcement is newsworthy. This embrace of Rust at the very core of Linux will be a huge boost to the robotics community.

There are a few reasons for my optimism. First, let’s acknowledge that those in charge of the capital-K Linux Kernel have traditionally forbidden the use of any language other than good old-fashioned C; leaving those confines willingly is remarkable. This will do two important things for the community: start to relieve tech’s complete reliance on C as a programming protocol, and invite programmers who are Rust-forward to make a mark on Linux as a whole. A er all, this movement has already started as Android incorporated Rust in 2021.

Second, the addition of Rust into the Kernel wasn’t trivial. A laundry list of features was needed to make Rust more secure and functional before it could be trusted at such a low level. However, with these features completed, they can be wrapped into the larger ecosystem, which will make everyone’s lives better. The more use Rust gets in the Kernel, the better Rust as a language will become.

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www.therobotreport.com

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www.therobotreport.com

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Tying it all together is robotics’ implicit reliance on Linux. Linux has kept up with the times remarkably well and is now used on most smart and autonomous devices. It is and will remain the preferred platform for robotics for the foreseeable future; furthermore, Linux’s adoption of Rust in the Kernel signals that it welcomes a future beyond C and wants to engage the wider community.

There’s a huge ecosystem of robotics tools and paradigms like ROS and OpenCV that operate best within the Linux ecosystem, and like it or not, most robotics engineers get their start playing around in these sandboxes.

Whole companies have based their work on these tools and have done very well for themselves. However, I can attest (anecdotally) that a growing number of engineers in the robotics field are recognizing the need for more powerful, more reliable so ware and are looking for alternative solutions.

Those that do are turning to Rust more o en than not. This has led to a budding robotics ecosystem full of enthusiastic developers who just want to write better tools in the most loved programming language around. As enthusiastic as these developers might be, though, these tools by and large aren’t ready for prime-time. They are missing features that most engineers take for granted, or haven’t been used enough to be trusted by the larger community.

This means many older robotics companies are still playing it safe, still working in the sandbox full of familiar

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so ware. Some simply loathe leaving the comfort of C++, Python, or whatever the senior engineer on staff believes is the right language. It’s certainly still early days for Rust in robotics, and it takes an enterprising team to take it on. Yet those who have ventured out beyond the familiar and invested the time have been rewarded for their efforts with better products. In fact, for the newest generation of engineers, Rust is familiar.

And that’s great news.

Between old tools, new programming languages, and the rise of automation, robotics is in a time of change. The inclusion of Rust into the Linux Kernel might seem like a small detail, but it couldn’t have come at a better time. The robotics community has been pushing Rust development for years now; for Linux to support, and be supported by, these efforts is a tide that li s all boats.

For the curious: survey a full catalog of open-source robotics solutions in Rust at https://robotics.rs/. RR

About the Author Brandon Minor is the founder and CEO of Tangram Vision, a sensor fusion company.

The Tangram Vision Platform approaches sensors holistically, knitting together LiDAR, CMOS, IMU and depth data all at once. This allows users to stop dealing with sensor support over and over, and instead focus on building what makes their product stand out.

www.therobotreport.com

THE ROBOT REPORT

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Inside Viam’s cloud-based

robotics development platform Eliot Horowitz, the co-founder of MongoDB, describes his new venture that aims to simplify the robotics development process.

Mike Oitzman • Editor, The Robot Report

New York-based startup Viam recently announced the public beta release of its new cloud-based robotics development platform.

Viam is building a one-stop, cloud-based repository for the tools required to prototype, code, deploy and scale robots. Viam de-veloped its system to be hardware and language agnostic.

Viam was founded in 2020 by Eliot Horowitz, who is a co-founder and former chief technology officer of MongoDB. MongoDB is a popular open-source, cross-platform, and distributed document-based database designed to ease application development.

Horowitz was a recent guest on The Robot Report Podcast, where he described in depth what Viam is building. The full interview with Horowitz can be found anywhere you listen to your podcasts. The text below is om that interview and has been edited for brevity and clarity.

Eliot Horowitz co-founded MongoDB, a soft-ware company that develops and provides commercial support for the open source NoSQL database. The company went public in 2017. | Viam

Why did you start Viam?

I le MongoDB in early 2020. As I was looking for the next big thing to work on, everything that interested me kept coming back to robotics, whether it was cleaning oceans, helping forests, fix-ing potholes in New York or cleaning dishes.

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Software Viam is building a one-stop, cloud-based repository for the tools required to prototype, code, deploy and scale robotics systems. Viam developed its system to be hardware and language agnostic. | Viam

So I did what most normal people would do and bought a collaborative robot arm, put it in my liv-ing room, and tried to make it play chess against me. I consider myself a pretty good programmer, but this was a fairly frustrating experience. The robot arm was quite impressive, but writing the software to make it play chess against me was pretty hard. The chess part was easy, but the robotics side was challenging.

I hired a few people and started trying to understand why this was so hard.

We were talking to a lot of people in the robotics space, doing research on the kinds of problems people are having.

And about 6–12 months after we started, we came up with the thesis that formed Viam.

Is Viam building an operating system or a programming language? Describe the layers of the solution being put together.

It has to be easier for people who are comfortable with hardware and less comfortable with soft-ware to work with software engineers who are less comfortable with hardware. And not just from a communication standpoint, but even from a process standpoint. We’ve got to make it easier for those sorts of lifecycles, too.

We want to be very unopinionated about the software, the languages people use to write code for robots and how they deploy them, and very opinionated about the things that matter.

It’s incredibly important that the basic building blocks are clean, it’s simple to use APIs for soft-ware engineers to do everything from basic low-level control to higher-level robotic features.

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We also think security and privacy have to be baked in from the beginning.

If you’re going to have robots running around your house with cameras that can interact with you and your family, if those things aren’t secure and have good privacy controls, we’re going to have all sorts of problems and adoption will never really happen.

And last but not least, all of these things need to work easily with the cloud and machine learning tools so that you can do things like fleet management and deploy new code without having to rewrite a lot of those building blocks.

Do you envision this as a universal software solution for all types of robots?

We think the building blocks are the same whether the robot is in a warehouse, a forest, a house or running around New York. Obviously, the hardware is different, and the software you have to write as the engineer building that solution is different.

A lot of code, infrastructure and plumbing are the same. Our job is to make all the undifferentiated code those companies have to write today go out the window. We’ll handle that. We want the person thinking about washing dishes or picking up trash in New York to only think about the problem.

Think about what’s happened in the web development space. Twenty years ago, if you wanted to build a small e-commerce website, you had to build a lot of this yourself, as well as credit card processing and security. Today, you can go to Shopify and build a website in a day.

www.therobotreport.com

The robotics space needs that sort of evolution. We all want the robotics industry to grow 100x. But how do we enable that? How do we provide the tools that make more engineers excited about the space and less scared about starting a robotics company? If you get three 25-year-olds together today, they’re probably not thinking about starting a robotics company. It’s too hard. There aren’t enough success stories. We want to change that.

What types of computing will Viam interact with?

We’re very hardware flexible. We’ll run on almost anything, but I think we’ll see a lot of Raspberry Pis, NVIDIA Jetsons and some of the higher-end Arduinos. That’s what people have — they’re affordable and accessible.

What programming languages can developers use on Viam’s platform?

For every component, let’s use an arm or a motor, there’s a gRPC protocol specification that we have as open source. With that, you can use it in any language that gRPC supports, which is basically all of them.

This is true both on the hardware integration side and on the software developer side. So let’s say that you have a new robotic arm coming in, and you are building your arm in Rust. You want to use Rust? Great. You want to use C++? Great. You can write to our API and implement the server side of the API in whatever language you want.

On the other hand, the client using the robot can write in any language they want — whether it’s Python, C++, ROS, Go, TypeScript, JavaScript.

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Software We can also run everything over WebRTC. What that does is it lets us do peer-to-peer, over-the-internet communication. So whether you’re running on the same physical box in the same data center, in the same warehouse, or across the planet, there’s a communication channel that works.

All of this is authenticated and encrypted. There’s nothing novel about the kinds of security we’re doing. What’s novel is the way we’re applying it to a space and making it easy to have great se-curity out of the box.

Who is Viam targeting with its solution?

I think it’s everyone from: • Someone building production robots • Hobbyists who want to tinker and make robots to play with their cat • Researchers trying to work on new SLAM algorithms • Hardware experts trying to come up with a new design for a novel robotic arm • Educators who want to teach high schoolers how to build robots I’m not saying we have every use case nailed perfectly today in the public beta.

But one of the key things is that we want it to be easy to move from space to space. Everything is designed to be flexible so that your system can move from space to space as it progresses from prototype to production.

The Robot Operating System (ROS) is one of the popular platforms for robotics development. Is ROS a competitor or will your solution work on top of ROS? Because of the way we built the system, we can work with or around anything.

If you already have a robot running ROS at a low level but you need a way to do teleoperation or data man-agement, you can write a wrapper for that in our system and then still use the lower-level pro-cess. So they can coexist, if needed.

Our goal is to make it easy to write software to bring the learning curve down as short as it can be. ROS has done amazing things in the robotic space.

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What’s on your roadmap for higherlevel functions?

Cloud configuration and logging management are there today. So you can see all of your robots deployed, where they are and what they’re doing. You can also have a full-tail operation out of the box. If you want to build a robot that your end user can drive around from an iPhone app, you can do that today.

Today, we also make it easy to work with data. Robots use a variety of sensors that take data from the real world and do something with it. We’re able to collect all that data. The data is first stored locally on the robot and then, based on the configuration, is uploaded to the cloud at a cer-tain speed and at a certain frequency where there are APIs to do whatever you want with it.

Over time, we’re working on making it easy to deploy new versions of code. How do you do that in a safe way where you can’t go and break robots in the field?

Let’s get new software tested on five robots, then deploy it to 1%, 10% and 50% of the robots. How do you handle things like roll-backs and mistakes? How do you deploy code versus new machine learning models? Those are things that are coming very soon.

What can we expect from Viam in the near future?

We are investing heavily in the platform.

We’re hiring more engineers in all sorts of different are-as, whether it’s in SLAM, computer vision or deploying robots.

We’re investing heavily for the long term.

This is a public beta, and we would love people to try it and give us feedback.

I’m sure we made some mistakes, but we want to understand the kinds of challenges people are having, what works, what is working well with the platform today, the issues they have with it, and the features that they need to go even faster. RR

www.therobotreport.com

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Plasma cutting

and MIG welding cobots yield heavy-duty results Cobots from Universal Robots help heavy-equipment manufacturer reduce time and eliminate manual cleanup on curved plasma cuts by 75%.

The Robot Report Staff

Carriere Industrial Supply (CIS) in Sudbury, Canada, produces heavy equipment for harsh mining environments; much of it—such as hauling equipment, scoops and earth movers—is used to move material om underground to the surface. Like most manufacturers, the company is adapting to a changing workforce—hiring new workers and retaining skilled talent, while strengthening its safety culture so that every employee goes home safely every day.

Automation is an ideal approach for repeatable applications. But in a low-volume, highmix manufacturing environment, and with many large workpieces that are difficult to move, traditional robots may not be considered.

The CIS team discovered Universal Robots (UR) at a trade show and was struck by the sight of collaborative robots (cobots) performing tasks while people interacted with them. Cobots om UR allow CIS to bring the robot to the work—rather than the other way around—and their easy programming empowers workers to continuously innovate to improve quality and output.

Solution The first project CIS identified for the UR application was plasma cutting of large metal parts.

Manual cuts require extensive cleanup due to the accumulation of dross at the bottom of the piece along with the jagged edges that occur when workers need to reposition themselves for long cuts. Reducing the cleanup time was an ideal area for improvement. Pierre Levesque,

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manager of innovation and technologies, says, “Using a robotic arm, we knew that we would get a more precise cut and the possibility of eliminating all of the grinding and cleanup of the joints.”

CIS chose the UR10e, which met both its reach and payload requirements, even with the weight of the plasma cutting tool and long workpieces. The UR10e offers a reach of up to 51.2 inches and payload capacity of 27.55 lbs. And despite the size and power of the robot arm, Levesque describes it as a “very approachable robotic cell” in terms of ease of use, even for operators with no robotics experience. They can place the workpiece on the table, “teach” the robot where the part is, and run the program for a clean, precise plasma cut, even on curved parts with complex geometries.

After some innovative programming, the cell became even more approachable for operators, who were excited to make continual adjustments to improve quality and output. Mason Fraser, junior software engineer at CIS, initially programmed the cutting of the most complex parts from start to finish, then built a new URCap program (software handshake between the cobot arm and its peripherals accessible on the cobot’s teach pendant) that “puts the operator in the driver’s seat” with an easy-to-use interface.

Now the operators are fully engaged in instructing the robot on the points and speed to do the cut.

“What the URCAP does is augment that operator’s ability by automatically navigating any plate geometry imperfections, and adjusting corner speed when necessary, based on the geometry and the points they provided,” Levesque added. “What you end up with at the end is the operator feeling in control, but elevating the game to make sure that the right parameters, the speeds, the material you are cutting— all that’s covered through the URCAP. So now you have a very successful cut, reduced time, reduced risk for the operator, and it is a win-win for both the operation and the operator.”

While operators appreciate that the work is more rewarding and less physically demanding, CIS also saw significant time and cost savings.

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Marc Sauve, process leader for steel processing at CIS, operates the plasma-cutting robot with no prior robotics experience. | Universal Robots

A UR10e plasma cutting robot.

| Universal

Robots

A UR10e MIG welding cobot is mounted onto a 7th axis and placed on a mobile skid to bring the robot to large workpieces. A human welder and robotic welder work sideby-side, leap-frogging across the side of the truck body to double output. | Universal Robots

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Cobots Previously, 80% of the plasma-cutting time was spent cleaning up the manual cut. On a single large truck body contract over the next three years, Levesque determined that the trimming process on that project alone would be more than 50 hours for every truck. Moving to a robotic application reduced that time to 12 hours per truck, ultimately delivering 1,000 hours and a significant cost savings on this project, exceeding CIS’ expectations “The interesting thing is to see the operators taking it even further, and applying thought on their cut process,” Levesque said. “With the ease of being able to manipulate the robot and using the free drive to position the torch in different angles, the operators were taking more care on applying bevels onto the final parts, which was quite impressive.”

Marc Sauve, process leader for steel processing at CIS who runs the plasma cutting robot, addressed concerns some may have about robots and jobs. “If I had a colleague who was fearful of a UR robot coming to take their job, I would put them at ease,” he said. “Every one of those robots needs an operator, so it’s just an asset to them; it’s not a tool to remove them.”

Results After the success of the plasma-cutting robot, CIS knew it could leverage that programming to MIG welding projects, even though that is a more difficult application. Fraser said, “The MIGwelding UR10e is doing similar profiles to what the plasma-cutting robot is doing, in the sense that it is following curvatures and following profiles; It’s just welding them instead of cutting them.”

Levesque knew MIG welding would pay dividends based on the large volume of welding work the company does.

The challenge was to find repeatable parts in its low-volume, high-mix environment. One application stood out: the production of truck bodies with seven large side-by-side filet-welded ribs, spaced three to four feet apart.

“We envisioned that the welder can be working on one of the ribs while the cobot can be doing the next rib in coordination, and then you just index them over,” Levesque said.

Fraser added, “There’s a ton of welding on those, so we are trying to make this save time for the welders.

They can work alongside the robot and split the work in half.”

Because of the length of the welds, the manual work raises critical ergonomic challenges to consider for welders. Fraser said, “The robot doesn’t care about ergonomics, so the operator can set up the robot and go work on other stuff that’s more productive and easier to do. Some of the more productive work they could do is cleaning up the welds, making them look nice. The more we can free them up to do that kind of work, the better.”

The MIG welding process is applied to massive parts weighing over 15 tons on the bodies of heavy-duty mining trucks; workpieces that can’t be fixtured inside a traditional robot cell. That required CIS to bring the robot to the workpiece, rather than the other way around. Unable to find a standard solution, the CIS team developed a custom welding skid that can be moved with a forklift to wherever the welding robot is needed. The robot is mounted on a lift to create a seventh axis to reach the entire weld on the side of a truck body. The relatively light weight of the UR cobot arm allowed CIS to develop this innovative approach. RR

Case Study Breakdown Company

Carriere Industrial Supply

Location

Sudbury, Canada

Industry

electronic & technology

Employees

130

Challenge

low-volume, high-mix manufacturing of large, complex workpieces

Robot

UR10e

Tasks

MIG welding, plasma cutting

Value Drivers doubling output, increasing quality and safety, lowering costs Results

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plasma-cutting cobot saves 1,000 hours and over $90,000 on a single project

www.therobotreport.com

THE ROBOT REPORT

11/4/22 7:41 AM

Meeting Customer Needs with Diverse Product Categories and Customized Products

Linear Piezo Motor

DC Brushless Servo Motor

Canon Precision proprietary technology and internal production systems provide our partners with micro-motor design flexibility, quality control and rapid delivery.

Canon Precision motors can also be equipped with optional gear units and encoders and can be optimized to meet your size, speed, gear ratio and reliability requirements.

CANON U.S.A., INC. Motion Control Products 3300 North 1st Street • San Jose, CA 95134 TEL: 1-408-468-2320 • Email: motors@cusa.canon.com www.usa.canon.com/ Canon is registered trademark of Canon Inc. in the United States, and may also be registered trademarks or trademarks in other countries. All other referenced product names and marks are trademarks of their respective owners. Specifications and availability subject to change. Not responsible for typographical errors. ©2021 Canon U.S.A., Inc. All rights reserved.

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How motion engineering

helps develop next-gen surgical robots The single-column, multiple-arm design of conventional surgical robots limits the angle of approach when multiple instruments are deployed. This is the principle challenge that needs to be overcome.

The Robot Report Staff

What if you could design and build a surgical robot that helps doctors perform less invasive, more precise operations and achieve better patient outcomes? While the results of any surgery depend on the challenges of the specific case and the skill of the surgeon, better tools support better care.

Here’s how next-generation motion engineering can help you develop the next generation of surgical robots.

Place the arms as close together as possible Conventional surgical robots include large columns with multiple arms holding a tiny camera and various instruments such as scissors, graspers, needle holders, clip applicators and more. Depending on the surgery, the ideal procedure is performed through a single, small incision that must simultaneously accommodate the visualization camera and any needed instruments.

If you ask any surgeon, they will tell you the ideal angle of approach for the camera and instruments into the incision site is as parallel and close together as possible—both to minimize trauma and to eliminate any discrepancy between the camera view and the angle at which each instrument operates.

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Achieving an identical angle of approach is, of course, impossible, as the instruments can’t occupy the same space. Today’s instruments are very thin and compact, however. It’s the single-column, multiple-arm design of conventional surgical robots—plus the sheer bulk of their arm joints—that limits the angle of approach when multiple instruments are deployed. This is the principle challenge to overcome when designing the next generation of robots.

Minimize the axial length of arm joints Standalone arms provide much greater flexibility in positioning compared to the conventional design, allowing multiple arms to be aligned in a plane much closer to parallel. To further approach the parallel ideal, the bulk of each arm must be minimized.

The limiting factor for how closely together the arms can operate is the axial length of the arm joints. You need a motor and gearing system that delivers all the required torque with the shortest possible axial length. Every millimeter saved without compromising

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performance helps surgeons work more effectively and creates an important market advantage for your surgical robot.

Start with the gearing High-torque motors with short stack lengths are key to achieving optimum torque while minimizing axial length, total volume and weight. However, beyond the stack length of the motor itself, the gearing and feedback devices also need to be tightly integrated within the joint.

Ultimately, it’s the gearing that translates the relatively high-speed motion of the motor into the lower speed and higher torque needed to move the load of the robotic arm at the optimum speed, precisely position it, and hold the load steadily in place. Because the selection of gearing also impacts the axial length of the joint, this is the place to start in creating your design.

The required speed, performance and load points will determine the

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Motion Control

To enable robotic arms to operate as closely together as possible, you instead need to minimize the axial length. | Kollmorgen appropriate gear set. No matter what ratio is required, this application calls for strain wave technology, also known as “harmonic” gearing.

Strain wave gearing provides three indispensable advantages: 1. It enables the most compact axial integration within the joint.

2. It offers relatively high gear ratios— typically ranging from a gear reduction of 30:1 to 320:1—to accelerate/decelerate loads smoothly and position them precisely.

3. It operates with zero backlash to minimize any unwanted movement that could potentially affect the precision of the procedure or induce unnecessary trauma.

Match the motor to the gearing and thermal requirements Having specified the appropriate gear technology and ratio, you can select a motor based on the gear ratio, the speed at which the arm must run, and the mass it needs to hold. Thermal rise when operating at typical or maximum load can also be an important consideration, as excessive heat in the tight confines of the joint can damage gearing lubricant, encoder electronics and other components in close proximity. A motor that can deliver full performance at a lower thermal rise is desirable.

Take advantage of the D2L rule As part of your motor specification process, you can further reduce axial length through an often-overlooked principle of motor design referred to as the D2L rule.

In robotic joint design, the diameter of the motor is typically of minor concern.

To enable robotic arms to operate as closely together as possible, you instead need to minimize the axial length. The D2L rule allows you to trade off a larger diameter for a significantly reduced axial length. Here’s how it works.

In the frameless motors used in robotic joints, torque increases or decreases in direct proportion to changes in motor length, but as the square of changes in the moment arm of the motor. In other words, under the D2L rule, doubling the moment arm—and thereby approximately doubling the overall diameter—produces a fourfold increase in torque.

Or, more relevant to surgical robot design, doubling the moment arm allows you to reduce the stack height by a factor of four while maintaining the same torque. This is a huge advantage when your design priority is to achieve the most compact axial length.

For next-generation surgical robot performance, choose next-generation motors specially designed for robotic applications. This will help you accelerate your development time and deliver surgical robots that allow doctors to operate instruments as close together and as close to parallel as possible.

Better tools mean better healthcare— and a healthier surgical robotics business. RR

According to surgeons, the ideal angle of approach for the camera and instruments into the incision site is as parallel and close together as possible. | Kollmorgen 56

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www.therobotreport.com

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C o n g r a t u l a t e s

maxon is a developer and manufacturer of brushed and brushless DC motors. as well as gearheads, encoders, controllers, and entire mechatronic systems. maxon drives are used wherever the requirements are particularly high: in NASA’s Mars rovers, in surgical power tools, in humanoid robots and in precision industrial applications, for example. To maintain its leadership in this demanding market, the company invests a considerable share of its annual revenue in research and development. Worldwide, maxon has more than 3000 employees at nine production sites and is represented by sales companies in more than 30 countries.

www.maxongroup.us • 508.677.0520

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How terrain semantics

help quadruped learn to walk

Google’s robotics researchers developed a learning framework that decides the locomotion skill for a quadruped, including the speed and gait of the robot based on the perceived semantics.

This allows the robot to walk robustly on a variety of off-road terrains, including rocks, pebbles, deep grass, mud, and more.

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Yuxiang Yang Researcher, Robotics at Google

An important promise for quadrupedal robots is their potential to operate in complex outdoor environments that are difficult or inaccessible for humans. Whether it’s to find natural resources deep in the mountains or to search for life signals in heavily-damaged earthquake sites, a robust and versatile quadrupedal robot could be very helpful. To achieve that, a robot needs to perceive the environment, understand its locomotion challenges, and adapt its locomotion skill accordingly.

While recent advances in perceptive locomotion have greatly enhanced the capability of quadrupedal robots, most work focuses on indoor or urban environments, thus they cannot effectively handle the complexity of offroad terrains. In these environments, the robot needs to understand not only the terrain shape (e.g., slope angle, smoothness), but also its contact properties (e.g., friction, restitution, deformability), which are important for a robot to decide its locomotion skills. As existing perceptive locomotion systems mostly focus on the use of depth cameras or LiDARs, it can be difficult for these systems to estimate such terrain properties accurately.

In “Learning Semantics-Aware Locomotion Skills from Human Demonstrations,” we designed a hierarchical learning framework to improve a robot’s ability to traverse complex, off-road environments. Unlike previous approaches that focus on environment geometry, such as terrain shape and obstacle locations, we focus on environment semantics, such as terrain type www.therobotreport.com

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Google tested its learning framework on an A1 quadruped from Chinese startup Unitree Robotics. | Unitree Robotics

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Motion Control

Google’s learning framework selects different speeds based on the conditions of the terrain. | Google (grass, mud, etc.) and contact properties, which provide a complementary set of information useful for off-road environments. As the robot walks, the framework decides the locomotion skill, including the speed and gait (i.e., shape and timing of the legs’ movement) of the robot based on the perceived semantics, which allows the robot to walk robustly on a variety of off-road terrains, including rocks, pebbles, deep grass, mud, and more.

Overview The hierarchical framework consists of a high-level skill policy and a low-level motor controller. The skill policy selects a locomotion skill based on camera images, and the motor controller converts the selected skill into motor commands.

The high-level skill policy is further decomposed into a learned speed policy and a heuristic-based gait selector. To decide on a skill, the speed policy first computes the desired forward speed, based on the semantic information from the onboard RGB camera.

For energy efficiency and robustness, quadrupedal robots usually select a different gait for each speed, so we designed the gait selector to compute a desired gait based on the forward speed. Lastly, a low-level convex modelpredictive controller (MPC) converts the desired locomotion skill into motor torque commands and executes them

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on the real hardware. We train the speed policy directly in the real world using imitation learning because it requires less training data compared to standard reinforcement learning algorithms.

Learning speed command from human demonstrations As the central component in our pipeline, the speed policy outputs the desired forward speed of the robot based on the RGB image from the onboard camera.

Although many robot learning tasks can leverage simulation as a source of lower-cost data collection, we train the speed policy in the real world because the accurate simulation of complex and diverse off-road environments is not yet available. As policy learning in the real world is time-consuming and potentially unsafe, we make two key design choices to improve the data efficiency and safety of our system.

The first is learning from human demonstrations. Standard reinforcement learning algorithms typically learn by exploration, where the agent attempts different actions in an environment and builds preferences based on the rewards received. However, such explorations can be potentially unsafe, especially in off-road environments, since any robot failures can damage both the robot hardware and the surrounding environment. To ensure safety, we train the speed policy using imitation learning

www.therobotreport.com

from human demonstrations. We first ask a human operator to teleoperate the robot on a variety of off-road terrains, where the operator controls the speed and heading of the robot using a remote joystick. Next, we collect the training data and then train the speed policy using standard supervised learning to predict the human operator’s speed command. As it turns out, the human demonstration is both safe and highquality, and allows the robot to learn a proper speed choice for different terrains.

The second key design choice is the training method. Deep neural networks, especially those involving high-dimensional visual inputs, typically require lots of data to train. To reduce the amount of real-world training data required, we first pre-train a semantic segmentation model on RUGD (an off-road driving dataset where the images look similar to those captured by the robot’s onboard camera), where the model predicts the semantic class (grass, mud, etc.) for every pixel in the camera image. We then extract a semantic embedding from the model’s intermediate layers and use that as the feature for on-robot training. With the pre-trained semantic embedding, we can train the speed policy effectively using less than 30 minutes of real-world data, which greatly reduces the amount of effort required.

Gait selection and motor control The next component in the pipeline, the gait selector, computes the appropriate gait based on the speed command from the speed policy. The gait of a robot, including its stepping frequency, swing height, and base height, can greatly affect the robot’s ability to traverse different terrains.

Scientific studies have shown that animals switch between different gaits at different speeds, and this result is further validated in quadrupedal robots, so we designed the gait selector to compute a robust gait for each speed.

Compared to using a fixed gait across all speeds, we find that the gait selector further enhances the robot’s navigation performance on off-road terrains.

THE ROBOT REPORT

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Connect with confidence

The last component of the pipeline is a motor controller, which converts the speed and gait commands into motor torques. Similar to previous work, we use separate control strategies for swing and stance legs. By separating the task of skill learning and motor control, the skill policy only needs to output the desired speed and does not need to learn lowlevel locomotion controls, which greatly simplifies the learning process.

Experiment results We implemented our amework on an A1 quadrupedal robot and tested it on an outdoor trail with multiple terrain types, including grass, gravel, and asphalt, which pose varying degrees of difficulty for the robot. For example, while the robot needs to walk slowly with high foot swings in deep grass to prevent its foot om getting stuck, on asphalt it can walk much faster with lower foot swings for better energy efficiency.

Our amework captures such differences and selects an appropriate skill for each terrain type: slow speed (0.5m/s) on deep grass, medium speed (1m/s) on gravel, and high speed (1.4m/s) on asphalt. It completes the 460m-long trail in 9.6 minutes with an average speed of 0.8m/s (i.e., that’s 1.8 miles or 2.9 kilometers per hour). In contrast, non-adaptive policies either cannot complete the trail safely or walk significantly slower (0.5m/s), illustrating the importance of adapting locomotion skills based on the perceived environments.

To test generalizability, we also deployed the robot to a number of trails that are not seen during training.

The robot traverses through all of them without fail and adjusts its locomotion skills based on terrain semantics. In general, the skill policy selects a faster skill on rigid and flat terrains and a slower speed on deformable or uneven terrain. At the time of writing, the robot has traversed over 6km of outdoor trails without failure.

Conclusion In this work, we present a hierarchical amework to learn semantic-aware locomotion skills for off-road locomotion.

Using less than 30 minutes of human demonstration data, the amework learns to adjust the speed and gait of the robot based on the perceived semantics of the environment. The robot can walk safely and efficiently on a wide variety of off-road terrains.

One limitation of our amework is that it only adjusts locomotion skills for standard walking and does not support more agile behaviors such as jumping, which can be essential for traversing more difficult terrains with gaps or hurdles. Another limitation is that our amework currently requires manual steering commands to follow a desired path and reach the goal. In future work, we plan to look into a deeper integration of high-level skill policy with the lowlevel controller for more agile behaviors and incorporate navigation and path planning into the amework so that the robot can operate fully autonomously in challenging off-road environments. RR

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Developing a

multifunctional, long-arm gripper

Gripper automatically packs manufactured components with three fingers, places them in boxes and places a layer of protective cardboard over them using a vacuum gripper.

The Robot Report Staff

Mohsen Saadat has always been inventive and technically gi ed. As a young boy, the 5-year-old Iranian invented his own toys, building small cars out of wire, for example – without any tools. The now 75-year-old’s passion for technology has never le .

At 19, Saadat moved to Germany, studied engineering, and taught as a professor. In 1991, he founded GMG – Gesellscha für modulare Greifersysteme – in Soest, North Rhine-Westphalia. His goal was to combine higher design theory scientific methods with state-of-the-art manufacturing processes.

“Within a few years, we successfully developed lightweight and flexible gripper systems for robots and automation systems based on the human hand,” says Saadat proudly.

He convinced numerous industries of his technology. The grippers, which have up to six individually movable fingers and, in some cases, over 100 joints, are used to handle car wheels in the automotive industry, to hold up sacks when filling them with bulk material, or to package sausage and cheese in the food industry.

A flexible and torsional rigid tower However, one of the inventions that makes Saadat proudest is a multifunctional long-arm gripper system. The gripper can automatically pack manufactured components – such as brake discs – with three fingers, place them in boxes and then place a layer of protective cardboard over them using a vacuum gripper.

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One of the challenges in the development process was to find suitable bearings for the moving metal components of the gripper, such as the finger joints. | igus

“In this gripper system, a creatively designed, flexible, and torsional rigid tower serves as the long arm of the gripper,” explained Saadat. “Depending on the task, gripping elements emerge om this tower that mechanically picks up components. A er the work is complete, the gripping and suction elements retract to their starting position within the tower.”

One of the challenges in the development process was to find suitable bearings for the moving metal

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components of the gripper, such as the finger joints. All the gripper components had to be low- iction, abrasionresistant, maintenance and lubrication ee, and easy to install. Therefore, Saadat quickly ruled out traditional rolling bearings.

“Rolling bearings are suitable for sustained rotational motion. They require the manufacture of a more accurate fit, involve complex assembly and disassembly, and result in metallic noise,” stated Saadat.

www.therobotreport.com

These disadvantages led Saadat to opt for an alternative: plain bearings made of high-performance plastics om igus – a motion plastics specialist om Cologne that tribologically optimizes plastics for industrial applications.

“We have been relying on plain bearings om igus since 1991. It was, therefore, clear om the outset that the polymer bearings would also be used in the multifunctional long-arm gripper. There is virtually no alternative to these bearings for us in automation technology, where

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Improving automation design with performance polymers

End Effectors there are constant back-and-forth movements,” said Saadat.

Another advantage is that compared to traditional metal bearings, polymer bearings are light, corrosion-free, and maintenancefree. They allow dry operation without needing lubrication thanks to integrated solid lubricants.

“That’s a critical specification,” said Saadat. “Because we couldn’t expect our customers to have to lubricate the gripper on a regular basis.”

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Still going strong after 200,000 cycles The polymer bearings from igus are so robust that the bearings will outlast a gripper life of around 30 years.

“This is an advantage for our multifunctional gripper, as the maintenance effort is reduced and productivity increases,” continued Saadat.

A test in the igus in-house laboratory also demonstrates how wear-resistant the bearings are. The igus polymer bearings were tested against classic metal bearings in the laboratory. Both bearing types pivot on a gas-nitrided St52 steel shaft – with a load of 30MPa and a speed of 0.01 meters per second.

“In the case of the metal bearings, the gliding layer was worn after 60,000 cycles,” said Stefan Loockmann-Rittich, head of the iglidur bearings business unit. “The iglide G plain bearings, on the other hand, showed almost no signs of wear even after 200,000 cycles. They are therefore ideally suited for reliable and maintenance-free use over many years.” RR

Depending on the task, gripping elements emerge from this tower that mechanically picks up components. | igus

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Harvard researchers

create soft,

tentacle-like robot gripper The gripper mimics the mechanics of curly hair and can grasp fragile or irregularly shaped objects without damaging them.

Steve Crowe • Editorial Director, The Robot Report

Researchers at the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) have created a tentacle-like gripper that can grasp irregularly shaped or so objects without damaging them.

The gripper is made up of many thin, so tentacles that rely on inflation to wrap themselves around an object without any sensing, planning or feedback control. Individually, each tentacle is too weak to pick up many objects, but with many working together the gripper can gently li heavy and oddly shaped objects.

Each tentacle is made up of a foot-long hollow, rubber rubes. The tubes are made with thicker plastic on one side, so that was the tube is pressurized it curls like a pigtail. As the tube curls, it wraps and entangles itself around an object. Each added tentacle increases the strength of this hold. The gripper releases the object by simply depressurizing the tentacles.

When designing the gripper, the research team took inspiration om nature. The gripper’s tentacles act similarly to how a jellyfish stuns its prey.

“With this research, we wanted to reimagine how we interact with objects,” said Kaitlyn Becker, former graduate student and postdoctoral fellow at SEAS and first author of the paper. “By taking advantage of the natural compliance of so robotics and enhancing it with a compliant structure, we designed a gripper that is greater than the sum of its parts and a grasping strategy that can adapt to a range of complex objects with minimal planning and perception.”

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A close-up of the tentacle-like gripper’s filaments wrapping around an object. | Harvard Microrobotics Lab/Harvard SEAS

To test how effective the gripper was, the research team used simulation and experiments where the gripper was tasked with handling a range of objects, including different houseplants and toys.

The team hopes that the gripper can be used to grasp fragile objects, like soft fruits and vegetables in agricultural production and distribution and delicate tissue in medical settings, as well as irregularly shaped objects, like glassware, in warehouses. The gripper could replace traditional grippers that rely on embedded sensors, complex feedback loops and advanced machine-learning algorithms to work.

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“Entanglement enables each highly compliant filament to conform locally with a target object leading to a secure but gentle topological grasp that is relatively independent of the details of the nature of the contact,” said Mahadevan, the Lola England de Valpine Professor of Applied Mathematics in SEAS, and of Organismic and Evolutionary Biology, and Physics in FAS and cocorresponding author of the paper.

“This new approach to robotic grasping complements existing solutions by replacing simple, traditional grippers that require complex control strategies with extremely compliant, and morphologically www.therobotreport.com

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End Effectors complex filaments that can operate with very simple control,” said Wood, the Harry Lewis and Marlyn McGrath Professor of Engineering and Applied Sciences and co-corresponding author of the paper. “This approach expands the range of what’s possible to pick up with robotic grippers.”

The team’s research was published in the Proceedings of the National Academy of Sciences (PNAS). It was co-authored by Clark Teeple, Nicholas Charles, Yeonsu Jung, Daniel Baum and James C. Weaver, and supported by the Office of Naval Research, the National Science Foundation, the Simons Foundation and the Henri Seydoux fund. RR

The gripper wrapping around a succulent. | Harvard Microrobotics Lab/Harvard SEAS

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ASTM forms group on robotic grasping and manipulation ASTM International’s committee on robotics, automation, and autonomous systems (F45) has formed a new subcommittee on grasping and manipulation. This new subcommittee (F45.05) will develop standards that evaluate performance in several major areas of robotic manipulation.

The first three task groups of the committee will develop standards for the performance of grasping-type end-effectors, mobile manipulators and robotic assembly systems, covering their use in both fixed and mobile base systems.

Aaron Prather, ASTM International’s new director of robotics and autonomous systems programs, said these standards will help speed up deployments and cut wasteful spending on selecting the wrong tool. Prather noted the subcommittee supports UN Sustainable Development Goal #9 on industries, innovation, and in astructure.

“As robotics and automation continue to expand into new and diverse industries, performance standards that help end users better select their end-effectors and/or manipulators to the task they are working on will be key,” said Prather. “Seeing the number of experts om across the world joining this work shows just how much this group is needed.”

The subcommittee will be initially headed by two co-chairs, Joe Falco and Omar Aboul-Enein, both om the National Institute of Standards and Technology (NIST). Experts om countries around the world, including Germany, New Zealand, Canada, and the United States are participating in the committee, with more welcome.

Out of six proposed standards currently planned for development, the subcommittee plans to register two by the end of 2022, on grasp strength and finger repeatability.

Monthly calls will be held for the task groups through 2023, and the subcommittee met at ASTM International’s October standards development meetings. ASTM welcomes participation in the development of its standards.

Prather was named to this position in August 2022 a er spending nearly 27 years at FedEx Express. He developed and deployed robotics and autonomous systems in numerous operations across the globe in his previous role with FedEx. He has participated in standards development at both A3 and UL. Prather is also passionate about working with workforce development programs and building up the 21st workforce in Manufacturing, Logistics, Robotics, and Automation.

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Sensor breakdown:

how robot vacuums navigate Technologies like ToF sensors, pressure sensors, IMUs and motor controllers, along with improvements in battery efficiency, have increased the performance of robot vacuums.

Peter Hartwell • CTO • Invensense

Over the past few years, robot vacuums have advanced immensely. Initial models tended to randomly bump their way around the room, o en missing key areas on the floor during their runtime. They also became trapped on thick rugs, and if vacuuming upstairs, came tumbling down with a heavy thud. Their runtime was also relatively short, and you’d o en come home hoping for a nice and clean room only to discover that it had run out of juice halfway through.

Since those early days, these cons have turned into pros with the innovative use of sensors and motor controllers in combination with dedicated open-source so ware and drivers. Here is a look at some of the different sensors used in today’s robot vacuums for improved navigation and cleaning.

Ultrasonic time-of-flight sensors Ultrasonic time-of-flight (ToF) sensors work in any lighting conditions and can provide millimeter-accurate range measurements independent of the target’s color and optical transparency. The sensor’s wide field-of-view (FoV) enables simultaneous range measurements of multiple objects. In a robot vacuum, they are used to detect if an object, such as a dog or children’s toy, is in its way and whether it needs to deviate its route to avoid a collision.

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An iRobot Roomba Combo j7+ robot vacuum navigating on a hardwood floor. | iRobot

Short-range ultrasonic ToF sensors Short-range ultrasonic ToF sensors can be used to determine different floor types. The application uses the average amplitude of a reflected ultrasonic signal to determine if the target surface is hard or so .

If the robot vacuum detects that it has moved om a carpet onto a hardwood floor, it can slow the motors down because they do not need to work as hard compared to carpet use.

The cliff detection feature can enable the robot vacuum to determine when it’s at the top of a set of stairs to prevent a fall.

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SLAM and LiDAR Most companies developing high-end robot vacuums use visual simultaneous localization and mapping (VSLAM) or LiDAR technology to build a virtual map of the room. These technologies enable the robot vacuum to move around more efficiently, covering an entire level of a home with multiple rooms. However, if you li the robot and put it down, it will not know its new location. To find out where it is, the robot must go off in a random direction and, once it detects an object and starts tracing the walls, it can find out where it is relevant to the map.

VSLAM or LiDAR technologies may not be applicable for low-light areas, for example, if the robot vacuum goes under a table or couch, where it is unable to read the map. www.therobotreport.com

Inertial Measurement Units (IMU) IMUs take the roll, pitch, and yaw of movements of the robot vacuum in the real world both om a linear and rotational perspective. When the robot vacuum is doing circles or moving in a straight line, it knows where it is supposed to go and how it is moving.

There may be a slight error between where it should be and where it is, and the IMU can hold that position in a very accurate way.

Based on rotational and linear movement, plus the mapping of the room, the robot vacuum can determine that it is not going over the same areas twice and can pick up where it le off if the battery dies. And, if someone picks up the robot vacuum and places November 2022

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Sensors it somewhere else or turns it around, it can detect what is happening and know where it is in real space. The IMU is essential to making robot vacuums efficient.

For robot vacuums that do not use VSLAM or LiDAR mapping technology, their position and navigation can be determined using dead reckoning by combining measurements from the wheel’s rotations with the inertial measurements from the IMU and object detection from the ToF sensors.

Smart speaker microphones As developers of robot vacuums continue to implement artificial intelligence (AI) with the ability to use voice assistants, microphones become an essential sensor technology. Take beamforming, for example. Beamforming is a type of radio frequency (RF) management technique that focuses the noise signal toward the microphone in combination with AI for tweaking. At the moment, the noise of the motors and the turning brushes on the robot vacuum is a bit loud. However, as microphone technology progresses and motors and brushes become quieter, coupled with beamforming, microphones will be able to determine the user’s voice in the not-too-distant future.

Algorithms can also be trained to disregard certain noises and listen

specifically for the voice of the user.

Ostensibly, the user wants to call for the vacuum cleaner to clear up something or tell it to go home without going through an app or voice assistant product. You want that to happen in real-time inside the host processor of the robot vacuum.

Alternatively, if the microphone notices that something is being spoken, it may be possible for the robot vacuum to stop all of its motors to listen to the command.

Embedded motor controllers The embedded motor controllers are turning the gears to ensure the wheels are moving the robot vacuum in the correct direction with accuracy that can tell when the wheel is actually turned 90 degrees as opposed to 88 degrees.

Without this high level of accuracy, the robot vacuum will be way off track after a certain amount of time. The embedded motor controller can be flexible whether you use sensors or not, making the robot vacuum scalable.

Pressure sensors The level of dust inside the dust box is estimated by monitoring the flow of air through the dustbin with a pressure sensor. Compared to the air pressure when the dustbin is empty, the air pressure inside the dustbin begins to

An example diagram block for a robot vacuum.

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drop when the airflow begins to stagnate due to an increase in suction dust or clogging of the filter. However, for more accurate detection, it is recommended to detect it as a differential pressure that uses a similar pressure sensor to measure the outside air pressure.

A lot of the high-end bases have the capability to suck out the contents of the dust box automatically. The robot vacuum can then return to base, empty its contents, return to its last known position and continue cleaning.

Auto-recharging To determine the battery’s state of charge (SoC), you need accurate current and voltage measurements. The coulomb counters and NTC thermistors in the battery pack provide this information.

When the battery reaches an arbitrary SoC level, the battery communicates an instruction for the robot vacuum to stop cleaning and return to the base for a recharge. When fully charged, the robot vacuum goes back to its last known position and continues cleaning.

Regardless of the size of the room, in theory, with multiple chargers and multiple abilities to empty the dustbin, the robot vacuum can cover the entire floor space.

| Invensense, a TTDK company

www.therobotreport.com

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11/3/22 9:31 PM

Thermistors Thermistors, which are a type of temperature sensor, can be used to monitor the running temperature of the MCU or MPU. They can also be used to monitor the temperatures of the motors and brush gears. If they are running way too hot, the robot vacuum is instructed to take a break and perhaps run a few system diagnostics to find out what is causing the problem. Also, items caught in the brushes, like an elastic band or excess hair, can make the motors overcompensate and overheat.

Robot vacuum developers should understand what the motors are supposed to sound like at a certain threshold of equency. It is possible to use a microphone to detect whether the motors are running abnormally, thereby detecting early stages of motor degradation. Again, by using

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diagnostics, the abnormal noise om the bushes could indicate that they have picked.

Conclusion The retail price of a robot vacuum goes hand in hand with functionality and accuracy; some of the high-end models can be as much as $1,100. You can get a robot vacuum for closer to $200, but you will be sacrificing some of the bells and whistles. It all depends on the value the robot vacuum developer wants to create and the cost structure that works best for the user.

As component costs come down, it seems likely that more mid-tier robot vacuums will enter the market.

Technologies like ToF sensors, pressure sensors, IMUs and motor controllers, along with improvements in battery efficiency, will drive this growth. RR

www.therobotreport.com

About the author: For seven years, Peter Hartwell has been the chief technology officer at Invensense, a TDK company. He holds more than 40 patents and his operation oversees 600 engineers who have developed a broad range of technologies and sensors for drones, automotive, industrial and, more broadly, IoT. Hartwell has 25-plus years of experience commercializing silicon MEMS products, working on advanced sensors and actuators, and specializing in MEMS testing techniques.

Prior to joining InvenSense, he spent four years as an architect of sensing hardware at Apple where he built and led a team responsible for the integration of accelerometer, gyroscope, magnetometer, pressure, proximity, and ambient light sensors across the entire product line.

Hartwell holds a B.S. in Materials Science om the University of Michigan and a Ph.D. in Electrical Engineering om Cornell University.

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Max Mobile Robots ForwardX Max Mobile Robots for Case and Pallet Picking Workflows Max series robots offer the payload capacity to support your case-load and pallet-load movements. Deploying a fleet of Max series robots can help increase workflow capacity, reduce forklift movement, and reduce related costs.

Features & Benefits • 360° obstacle detection and avoidance for guaranteed safety • Lift function availability for autonomous pallet or rack pick-up and drop-off Autonomous charging for 24/7 operation • • Payload capacities of up to 2,645 lbs • Can be configured with handheld devices, printers, etc. and adapt to your existing workflows ForwardX Max AMRs are already helping some of the world’s leading companies reach up to 3x previous picking rates and reduce operating costs by up to 50%.

Visit en.forwardx.com to learn more.

ForwardX Robotics Website: en.forwardx.com Email: oversea@forwardx.com

Interconnect Solutions LEMO® is the industry leader in the design and production of precise custom interconnect systems. LEMO products are designed and manufactured according to rigorous and controlled processes. Inspection and traceability of products are systematically ensured in compliance with our standards. High-quality LEMO Push-Pull connectors are used in a wide range of challenging application environments, such as medical, test & measurement, research, defense & military, information systems, aerospace & autonomous vehicles, robotics, automotive, industrial control, nuclear, broadcast & audio-video, and communications.

LEMO® has been designing precision connectors for over seven decades. Offering more than 90,000 combinations of products that continue to grow through customer-specific designs, LEMO® and its brands REDEL®, NORTHWIRE®, and COELVER® currently serve more than 100,000 customers in over 80 countries around the world.

THE ROBOT REPORT

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www.therobotreport.com

LEMO USA, Inc. 635 Park Ct. Rohnert Park, California 94928 Ph: 707.578.8811 E-mail: info_us@lemo.com Website: https://www.lemo.com/en

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End Effectors/Grippers mGripAI: High-Speed Bulk Picking for Food Processing mGripAI™ is a food automation solution combining 3D vision, soft grasping, and artificial intelligence software that together solve the largest food processing challenges facing the world today. This unprecedented combination of robotic “hands,” “eyes,” and “brains” enables, for the first time ever, the high-speed automation of bulk picking processes.

• Pick delicate and variable products directly from bulk • Increase production by minimizing reliance on human labor • Deliver greater throughput - robot pick at >90 ppm • Safe product handling with IP69K food-grade materials • Increase operational efficiencies • Reduce automation footprint • Automate primary and secondary food processing applications • Lower operational costs • Easily integrates with all industrial robots mGripAI is the fastest food automation solution in the world!

Soft Robotics 32 Crosby Drive, Suite 101 Bedford, MA 01730 USA Info@softroboticsinc.com www.softroboticsinc.com

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 for the design engineering community.

rdworldonline.com PRODUCT SPOTLIGHT TIPS 11-22_Vs2.indd 76

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Robotics Robotics

Canon U.S.A., Inc.

DC brushless Servo Motors Today’s increasing demands of automation and robotics in various industries, engineers are challenged to design unique and innovative machines to differentiate from their competitors. Within motion control systems, flexible integration, space saving, and light weight are the key requirements to design a successful mechanism.

Canon’s new high torque density, compact and lightweight DC brushless servo motors are superior to enhance innovative design. Our custom capabilities engage optimizing your next innovative designs.

Canon U.S.A., Inc. Motion Control Products

We are committed in proving technological advantages for your success.

408-468-2320 www.usa.canon.com

THE ROBOT REPORT

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3300 North First Street San Jose, CA, 95134

CGI Inc. Advanced Products for Robotics and Automation At CGI we serve a wide array of industries including medical, robotics, aerospace, defense, semiconductor, industrial automation, motion control, and many others. Our core business is manufacturing precision motion control solutions.

CGI’s diverse customer base and wide range of applications have earned us a reputation for quality, reliability, and flexibility. One of the distinct competitive advantages we are able to provide our customers is an engineering team that is knowledgeable and easy to work with. CGI is certified to ISO9001 and ISO13485 quality management systems. In addition, we are FDA and AS9100 compliant. Our unique quality control environment is weaved into the fabric of our manufacturing facility. We work daily with customers who demand both precision and rapid turnarounds.

ISO QUALITY MANAGEMENT SYSTEMS: ISO 9001• ISO 13485 • AS9100 • ITAR SIX SIGMA AND LEAN PRACTICES ARE EMBRACED DAILY WITHIN THE CULTURE

www.therobotreport.com

CGI Inc. 3400 Arrowhead Drive Carson City, NV 89706 Toll Free: 1.800.568.4327 Ph: 1.775.882.3422 Fx: 1.775.882.9599 WWW.CGIMOTION.COM

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Robotics Robotics

Double sided bonding solutions for custom automation Double sided 3M VHB™ or transfer adhesives are an ideal bonding solution for custom automation or robotics applications. Utilizing a double-sided adhesive in place of mechanical fastening reduces weight, increases flexibility, without sacrificing strength or durability. Double sided adhesive tapes provide efficient bonding that saves time and money by an easy peel and stick installation. Looking for a more specialized double-sided tape? CS Hyde specializes in double sided adhesive lamination fusing acrylic and or silicone adhesive to high performance polymer films like Kapton®, fiberglass, or PTFE. For more specific applications, we can help maximize design versatility by die cutting double sided tapes into precise shapes and sizes based on your application.

CS Hyde Company

www.cshyde.com 800.461.4161

FESTO Corporation Plan for the Unplanned With Festo AX The Festo Automation Experience (AX) is an easy-to-use solution that leverages artificial intelligence (AI) and machine learning to help you extract the most value from your data.

Empowered with this information, you can make better maintenance decisions, increase productivity, reduce energy costs and prevent quality losses. Festo AX analyzes and delivers asset data in real time, which means you receive the information you need as soon as an anomaly occurs — no waiting or latency. Not only is this application compatible with other Festo components, you can easily integrate it with third-party components and machines using common protocols like OPC-UA and MQTT.

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Festo Corporation 1377 Motor Pkwy. Ste 310 Suffolk County Islandia, NY 11749 Phone: 1.800.993.3786 Web: www.festo.us E-mail: customer.service.us@festo.com

THE ROBOT REPORT

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Robotics Robotics

GAM GAM provides a full range of robotic flange gearboxes GAM’s extensive product offering includes three different flange gearboxes: Strain Wave (harmonic), Cycloidal, and the revolutionary Zero-Backlash Planetary. The GAM GPL zero-backlash planetary gearbox features a unique design ensuring backlash of ≤ 0.1 arcmin for the life of the gearbox. The GPL provides vibration-free motion and high positional accuracy for precise smooth path control and repeatability with a life of 20,000 hours. The GCL cycloidal gearbox provides precise point-to-point motion and high impact resistance of 5x nominal torque with the option of an integral pre-stage. The GSL strain wave gearbox uses harmonic-type gearing for high accuracy and drops in for popular competitor gearboxes. With three options, GAM can provide the zero-backlash gearbox for your precision application.

GAM 801 E Business Center Drive Mount Prospect, IL 60056 888.GAM.7117 | 847.649.2500 www.gamweb.com info@gamweb.com

Harmonic Drive Servo Grade AMR Propulsion Drive Trains The drive wheels on Autonomous Mobile Robot platforms benefit from the inherent characteristics of harmonic planetary technology; primarily, smoothness of travel, backdrivability, and an efficiency curve that does not degrade over time.

The integral cross roller bearing construction contributes to an excellent balance of torque density, stiffness, and radial load support in a compact and reliable package. Available in dozens of standard reduction ratios, these low backlash drive trains include motor adaptation as required.

THE ROBOT REPORT

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42 Dunham Ridge Beverly, MA 01915 United States www.harmonicdrive.net

Harmonic Drive is a registered trademark of Harmonic Drive Systems

www.therobotreport.com

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Kona Connectors 60A per contact, High-reliability Connectors Kona expands the Harwin High-Reliability portfolio into new levels of current – 60A per contact.

Designed to withstand testing environments and conditions.

• 2, 3 or 4 single row configurations • Vertical cable-to-board or cable-to-cable • Vibration and shock resistant, compact power future-proofed • 60A max per contact • 6-finger contact design to maintain electrical contact through high vibration and shock Other useful features include reverse fix screws, polarization, and identification of the #1 position. Harwin provides CAD Models, Test Reports and F.O.C samples to assist you in the design process.

For more information, visit harwin.com

Easily design a maintenance-free gantry robot system to your exact specifications for up to 40% less cost Gantry robots have become a critical component for manufacturing and warehouse automation. igus® provides turnkey and custom gantry systems that are built with self-lubricating plastic liners which are engineered to slide instead of roll, allowing for smoother and quieter operation vs. traditional recirculating ball bearings.

Every gantry robot system that igus® offers provides a lightweight, corrosion-resistant solution that is ideal for pick and place, sorting, labeling, measuring, inspection, and repetitive material handling applications.

Due to their modular nature, igus® gantry robots are easily customizable for any workspace, and free onsite consultation is available to ensure the perfect solution at the lowest possible cost.

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www.therobotreport.com

igus, inc.

257 Ferris Avenue Rumford, RI 02916 Ph: 800.521.2747 sales@igus.com www.igus.com

THE ROBOT REPORT

11/4/22 1:30 PM

Robotics Robotics

Keystone Electronics Corp.

A World Class Manufacturer of precision electronic components & hardware for over 70 years. Keystone’s design and engineering experts are fully integrated with their inhouse precision tool & die division supported by advanced manufacturing systems to produce close tolerance Stamping, Machining, Assembly, CNC and Injection Molded parts.

Keystone utilizes state-of-the-art software to support the

thousands of standard products found in their Product Design Guide M70 and Keystone’s Dynamic Catalog on-line.

Product Overview: Battery Clips, Contacts & Holders; Fuse Clips & Holders; Terminals & Test Points; Spacers & Standoffs; Panel Hardware; Pins, Plugs, Jacks & Sockets; Multi-Purpose Hardware.

As an ISO9001:2015 certified manufacturer, Keystone’s

quality control system, responsive customer service and custom manufacturing division can meet your challenges with a standard or custom design solution.

DESIGNERS & MANUFACTURERS

www.keyelco.com

Keystone Electronics 55 S. Denton Ave. New Hyde Park, NY 11040 Tel: 1.800.221.5510 www.keyelco.com

Motorizing an AGV Today’s AGVs must be compact and functional robots which are able to move vertically and carry heavy loads. These AGVs cannot fail, and so the choice of their motorization is crucial. There are 5 key points to consider when motorizing an AGV. 1. Choose compact motorization where possible - Drives must fit into restricted spaces, as they are sometimes integrated into existing trucks. A small footprint is critical for applications in logistics.

2. Focus on ease of use – select a plug-and-play solution.

3. Opt for fast delivery of your motor solution 4. Base the design on modularity - Not all AGVs do the same job and therefore having the flexibility to select a solution to match needed specifications is essential.

5. Prioritize safety – select motor options with integrated sensors.

maxon’s IDX motor has a diameter of only 56 mm, its performance is equivalent to that of a motor with a footprint 25% larger. The IDX motorization thus combines performance in a compact size and ideal for AGVs.

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125 Dever Drive Taunton, MA 02780 Phone: 508.677.0520

Go to Drive.tech for more details.

Visit www.maxongroup.us for more maxon solutions.

THE ROBOT REPORT

maxon precision motors, inc.

www.maxongroup.us info.us@maxongroup.com

www.therobotreport.com

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Fully Automate Your Automation The factory of the future demands higher output with increased flexibility, and cobots can’t do it alone. The Cobot Feeder from Applied Cobotics addresses these demands with high-mix, high-volume production while eliminating cobot downtime and alleviating staffing issues. The bottom-line result is increased output without increased labor.

The Cobot Feeder presents a worktable that adjusts vertically, synchronizing with each custom tray on the rack tower. A horizontal loader/unloader provides accurate and repeatable motion while positioning trays in front of the cobot. These features, along with the portable dunnage tray cart, make the Cobot Feeder from Applied Cobotics an essential complement to any collaborative automation system. With a 90-day ROI, small to medium-sized enterprises will quickly achieve lights-out manufacturing, increasing safety, quality—and profits.

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PBC Linear 6402 E. Rockton Road Roscoe, Illinois 61073 USA +1.815.389.5600 pbclinear.com

Pepperl+Fuchs, Inc. AGV Collision Avoidance and Cliff Detection– 4 Scanning Layers in Just One Device Pepperl+Fuchs‘ R2300 is a cost-effective and versatile multi-layer LiDAR sensor for object perception in 3D space.

The sensor – powered by Pulse Ranging Technology (PRT) – ensures high accuracy, noise immunity, and cross-talk protection. The high sampling rate and precise light spot is ideal for positioning, object classification, and navigationsupport tasks. The R2300 is also equipped with an integrated visible-red pilot laser that can be switched on to simplify installation and commissioning and switched off during operation.

The R2300 is made with solid-state electronics ensuring durability, efficiency, and longevity. www.pepperl-fuchs.com/usa/en/R2300_photoelectric_sensors.htm

November 2022

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Pepperl+Fuchs, Inc. 1600 Enterprise Parkway Twinsburg, OH 44087 330-425-3555 sales@us.pepperl-fuchs.com www.pepperl-fuchs.com

www.therobotreport.com

THE ROBOT REPORT

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Robotics Robotics THE ROBOT REPORT

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POSITAL-FRABA, INC. POSITAL’s 22 mm Diameter Kit Encoder: accurate, rugged, and zero-maintenance multiturn!

Only 22 mm across and 23 mm high, POSITAL’s miniature kit encoders are designed to be integrated with popular miniature BLDC and stepper motors, providing absolute position feedback for motion control. The multiturn rotation counter is powered by a Wiegand energy harvesting system, ensuring reliable absolute multi-turn position measurement with no backup batteries or complex gear systems.

The new 22 mm kit encoders offer 17-bit electronic resolution and a 32-bit multi-turn measurement range. The simple installation process and can be carried out under normal factory conditions.

Available with SSI or BiSS C vendor-neutral interfaces.

For more information, please visit: https://www.posital.com/en/news/product-news/22mmkits.php

POSITAL-FRABA Inc. 1 N Johnston Avenue, Suite C238 Hamilton NJ Phone: + 1 609-750-8705 E-Mail: info@fraba.com

Ruland Manufacturing Zero-Backlash Couplings for Robotic Systems Ruland Manufacturing offers a variety of zero-backlash servo couplings designed for use in high precision applications like automation and robotics. Ruland offers beam, bellows, disc, oldham, jaw, and newly-released Controlflex couplings in thousands of off-the-shelf combinations and sizes to help designers optimize their systems.

Robotic vision systems, material handling robots, and automated guided vehicles have infamously strict requirements that require engineers to balance torque, weight, dampening, and more, all while retaining extremely precise power transmission. Ruland servo couplings excel in demanding applications and can be selected based on a wide variety of performance characteristics.

Visit Ruland.com for access to everything you need to make a coupling design decision including: full technical product data, 3D CAD models, installation videos, and eCommerce to make prototyping easy.

www.therobotreport.com

Ruland Manufacturing 6 Hayes Memorial Dr. Marlborough, MA 01752 508-485-1000 www.ruland.com email: sales@ruland.com

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Compact, rugged motion sensing for any task In any environment Silicon Sensing’s gyroscopes, accelerometers and inertial systems offer a precise, compact and affordable solution for robotics application.

Our products include: • DMU11 - a low cost, compact, precise, six-degrees-of-freedom (6-DOF) device delivering market-leading performance that is calibrated over its full rated temperature range.

• CMS300 - a robust, compact gyro and dual-axis accelerometer delivering precise performance with low power consumption.

Available in both flat and orthogonal mount packages.

• PinPoint® - A tiny gyro measuring only 5mm x 6mm and delivering on performance, reliability and price.

Available in both flat and orthogonal mounts.

Inertial sensing for any task. www.siliconsensing.com/products

Silicon Sensing www.siliconsensing.com Clittaford Road Southway Plymouth Devon PL6 6DE England Ph: 01752 723330

EE Classroom on Silicon Carbide

Silicon Carbide (SiC) has made its mark in bringing faster, a smaller, and more reliable components than its fellow semiconductors to market. While SiC components have been around for a couple of decades, there is still a lot to learn and a lot to consider when choosing the most suitable WBG semiconductor for your device.

LET US HELP with tutorials, from looking at how WBG semis stack up in power conversion efficiency to an overview of SiC FETs and MOSFETs.

Check out our EE Classroom to learn more:

www.eeworldonline.com/silicon-carbide-classroom

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Robot guide streamlines automation process Kuka kuka.com Designed to decrease the apprehension and intimidation some manufacturers might face during their initial foray into robotic automation; the new KUKA Robot Guide makes the process fast and easy to apply the right automation to specific application needs. In three easy steps, users are presented with options based on their industry, application, and environment for the perfect automation match.

Within the guide, users can choose between several industries, including automotive, food & beverage, medical, plastics, electronics, and metal industry, then drill down to almost any application environment. These robots are suited for applications requiring extreme precision and repetitive tasks with fast cycle times, and for those within large foundry operations.

Application categories include arc and laser welding, machining, measuring, and inspection, and range from applying/gluing and painting to handling and assembly. Users can also indicate whether the robot will work autonomously in an isolated environment or collaboratively with humans.

Robotic item picker with new ABB AI solution ABB global.abb The ABB Robotic Item Picker helps users automate order picking and sorter induction operations and fulfills the company’s vision of a fully automated warehouse, combining automated storage with automated order picking.

The Item Picker consists of a robot, a robot controller, a suction gripper, a machine vision sensor, and software with the latest cutting-edge technology in artificial intelligence developed internally by ABB. The Pack Expo demo featured an IRB 1200 robot and the IRC5 compact controller, and it picked an assortment of variously shaped products.

This AI solution provides: • Unprecedented accuracy in picking items from unstructured scenery.

• High throughput application thanks to reduced computing time, achieving pick rates up to 1500 items per hour (peak).

• Advanced software leveraging artificial intelligence allows the robot to learn and adapt to various items including cuboids, cylinders, pouches, blisters, and random shapes, as found in electronics, pharma, healthcare, cosmetics, and other consumer product industries.

THE ROBOT REPORT

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Extended range of Cartesian subsystems Bosch Rexroth boschrexroth.com Bosch Rexroth has expanded its portfolio of linear robots for various applications in factory automation by adding new axis combinations and sizes.

The much wider range of working areas and loads makes the Cartesian subsystems also suitable for applications like battery handling or intralogistics. The linear robots can be selected and sized quickly and easily thanks to predefined axis combinations. They can then be configured and finalized online and ordered as preassembled subsystems — optionally with controllers for the new ctrlX AUTOMATION platform. Each multi-axis system is available as a Smart Function Kit for handling or dispensing. Preinstalled software then allows even quicker commissioning and intuitive programming. This significantly reduces engineering time.

The expanded range includes eight different axis combinations with 68 sizes. The products can be used in many sectors, such as automotive (including battery production), pharmaceuticals, and FMCG. Applications range from pick and place, positioning and palletizing, to feeding, shifting, loading, and even dispensing tasks.

All-new collaborative, industrial cobot Universal Robots universal-robots.com This all-new collaborative, industrial cobot from Universal Robots delivers the longest reach and payload in its class, offering the ability to automate even more hard-to-staff tasks in a market struggling to hire.

The tedious task of loading and unloading parts into machines has long been a bread-andbutter application for cobots gaining significant traction in the industry. With its 1,750 mm (68.90in.) reach and 20kg payload (44.1 lbs.), the UR20 from Universal Robots expands automation opportunities such as the ability to reach further into machines, tend several machines in the same cycle, and handle 25% heavier parts.

Despite being UR’s heaviest robot, the UR20 is the lightest cobot in its class, weighing only 64kg (141.1 lbs.), making it both a versatile technical tool and a manual laborer.

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For further information about products on these pages visit the Design World website @ www.designworldonline.com

Next-generation TILTIX inclinometers POSITAL posital.com

POSITAL has updated its family of TILTIX inclinometers with new three-axis MEMS accelerometers, enhanced firmware, and a new housing concept. These changes enable a streamlining of manufacturing processes and a reduction in delivery times while maintaining full environmental protection. The new versions are compatible with older models, with identical mounting footprint and support for CANopen and analog communications interfaces, while offering improved accuracy and better signal-to-noise ratios.

A significant feature of the new TILTIX inclinometers is an enhanced programming function that enables users or distributors to set the measurement range of each device through simple configuration updates. These devices can be customized to function as a single-axis (0-360°), two-axis (± 90 °), or 2-axis pitch/roll (± 180 °) sensor, depending on what’s required for a specific application. Distributors and system integrators will appreciate this feature because it allows them to stock fewer items and still provide customers with a full range of measurement range options.

Cobot Feeder PBC Linear pbclinear.com The Cobot Feeder from Applied Cobotics is designed to assist collaborative robots and other types of automation robots by consistently loading and unloading material dunnage trays within the cobot/robotaccessible work area.

Why the Cobot Feeder?

The company’s experiences with implementing cobots taught them that a single tray of parts did not take advantage of a cobot’s full potential. At any given moment, operators might be called to other tasks or change shifts, resulting in significant cobot downtime. In other words, cobots were spending more time idling. In addition, the vision systems required to pick parts from a bin were unreliable, so a more consistent solution was needed.

Benefits This solution was to design and build an innovative and unique Cobot Feeder that substantially increases robot productivity. The repeatable action of the Cobot Feeder in conjunction with the parts trays results in consistent robot performance.

With the Cobot Feeder from Applied Cobotics, robots can now run longer unattended projects, include a higher mix of parts, and ultimately achieve lights-out production.

THE ROBOT REPORT

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AD INDEX Advantech USA ............................................................... 43

SALES

LEADERSHIP TEAM

Ryan Ashdown

Publisher Mike Emich

rashdown@wtwhmedia.com 216.316.6691

AllMotion ................................................................................5

memich@wtwhmedia.com 508.446.1823 @wtwh_memich

Jami Brownlee

Bally Design ........................................................................ 13

jbrownlee@wtwhmedia.com 224.760.1055

Bodine Electric Company .........................................27,29

Managing Director Scott McCafferty

Jordan Callender

Brother International ...................................................... 18

smccafferty@wtwhmedia.com 310.279.3844 @SMMcCafferty

jcallender@wtwhmedia.com 408.201.4886

Canon U.S.A. ..................................................................... 53

EVP Marshall Matheson

Mary Ann Cooke

CGI Inc. ................................................................................ 28

mcooke@wtwhmedia.com 781.710.4659

Chieftek Precision ........................................................... 73

mmatheson@wtwhmedia.com 805.895.3609 @mmatheson

Jim Dempsey

CS Hyde Company .......................................................... 64

jdempsey@wtwhmedia.com 216.387.1916

DeviceTalks ........................................................................69

Mike Francesconi

Digi-Key Electronics ...........................................................3

mfrancesconi@wtwhmedia.com 630.488.9029

DOOSAN Robotics Americas .................................... IFC

Jim Powers

jpowers@wtwhmedia.com 312.925.7793 @jpowers_media

FESTO .....................................................................................11 ForwardX Robotics Inc. ................................................. 47

Courtney Nagle

GAM ......................................................................................BC

cseel@wtwhmedia.com 440.523.1685 @wtwh_CSeel

Harmonic Drive .....................................................................1 Harwin .................................................................................. 61 igus ....................................................................................... 33 Keystone Electronics Corp. ............................................7 LEMO USA ......................................................................... 39 maxon ............................................................................ 49,57

com

www.therobotreport.

November 2022

Check out the digital edition!

Pepperl+Fuchs, Inc. ........................................................ 23

So much happens between issues of Design World that even another issue

2Ro0bo2tic2s

PBC ......................................................................................IBC POSITAL FRABA ............................................................... 42

would not be enough to keep up. That’s why it makes sense to visit designworldonline.com and stay on Twitter, Google plus, Facebook and Linkedin. It’s updated regularly with relevant technical information and other significant news to the design engineering community.

Handbook

Renishaw ............................................................................. 12

designworldonline.com

Ruland Manufacturing ................................................... 35 11/1/22 4:42 PM

Silicon Sensing Systems ............................................... 19

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NOV 2022 COV_RRHBK_FINAL.ind

Soft Robotics .................................................................... 65

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THE ROBOT REPORT

11/7/22 11:52 AM

TheASRS

Elevates Cobot Productivity

Applied Cobotics Automated Storage and Retrieval System Running 24/7 on the Strength of PBC Linear Parts

Steel Shafting

Ball Bearing Pillow Block

CNC Rolled Lead Screw

The biggest issue that this machine is solving is cobot downtime. Without some sort of automated loading and unloading system, cobots will inevitably sit idle, falling far short of their desired potential. The Automated Storage and Retrieval System (ASRS) is built to continuously feed parts to the cobot.

MTB Series Actuator

PBC Linear has implemented the ASRS and cobots on their CNC mills and lathes that produce their signature bearings. With roughly 80 CNC machines in their shop and 15 cobot stations in operation, the ASRS has boosted cobot production up to 1600%, and created a more flexible manufacturing model while elevating profits.

The Automated Storage and Retrieval System is easy to install, operate, and can be purchased by itself or with a cobot. In addition, PBC Linear offers production of custom dunnage trays for your specific parts.

Find out more at appliedcobotics.com and pbclinear.com.

Applied Cobotics (PBC Linear) 11-22_RR HBK.indd 1

6402 E. Rockton Road Roscoe, Illinois 61073 USA +1.800.962.8979 • pbclinear.com

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PRECISION FLANGE GEARBOXES FOR ROBOTIC & MOTION CONTROL APPLICATIONS

GPL Robotic Planetary Backlash ≤0.1 arcmin for the life of the gearbox.

Vibration-free for high positional accuracy

GSL Strain Wave

Backlash ≤0.5 arcmin Harmonic-type gearing High torque density Easy integration

SPH Helical Planetary

Backlash ≤4 arcmin Quiet operation Highest precision for demanding servo applications

GCL Cycloidal

Backlash ≤1.0 arcmin Impact resistance 5x nominal torque Available with integral pre-stage

EPL Planetary

Backlash ≤8 arcmin Precision gearbox for general servo applications Easily customizable

GAM offers a full range of robotic and servo gearboxes, along with rack & pinion, couplings, and linear mount products for motion control and robotic applications.

With our broad product offerings in the gearbox market, as well as the in-house engineering design experts and manufacturing capabilities to develop customized solutions, we can help with your application.

GAM Can.

t www.gamweb.com/flange | info@gamweb.com | 888.GAM.7117

GAM 11-22_RR HBK.indd 1

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