North American paper mills are starting to use robotics for smelt spout cleaning. Source: Valmet

Recovery boilers represent a significant capital expenditure in the pulp and paper industry. While a well-maintained boiler can last for decades, routine care of this system can present challenges. Maintenance duties are often messy and risky for the operator, and many tasks are time-consuming and require full or partial boiler shutdown. This can harm overall productivity and mill safety.

One maintenance task that is particularly challenging in the care of recovery boilers is smelt spout cleaning. While cleaning smelt spouts is essential for efficient recovery boiler performance, it can pose serious safety risks to the operator when the spouts are cleaned manually.

These risks include the operator encountering molten smelt, green liquor, and hot gasses, as well as repetitive-motion back and shoulder injuries. Finding operators who are willing to perform these tasks, training them, and retaining them over time have also become part of the challenge.

To improve operator safety during smelt spout cleaning and increase both operator and boiler productivity, pulp and paper facilities now have automated robotic solutions that can take on these more difficult tasks.

Robotic technology for smelt spout cleaning has been available since 2008, but it has only recently entered North American paper mills. Its delayed entry has been largely due to low numbers of new recovery boiler installations, as the robot requires a certain amount of space that is often difficult to allocate within existing operations.

Now, as North American operations are in greater need of the benefits that accompany smelt spout cleaning robots, they can invest in retrofitting existing recovery boilers with robotic solutions.

Smart design removes barriers to robotics retrofits

For pulping operations, one of the biggest barriers to adopting a smelt spout cleaning robot is often the amount of space that’s required for the robot to move around the spout deck during the cleaning cycle. In many facilities, this area around the smelt spout systems is already tight, which is part of what makes manual smelt spout cleaning difficult and risky for operators.

As automation designers have continued to invest in understanding the safety and productivity challenges faced by the pulp and paper industry, new solutions have emerged that remove this common barrier to adding robotics.

For instance, one smelt spout cleaning robot offers the option of a standing mount or a hanging mount. All that’s required to employ the hanging mount and position the robot next to the recovery boiler is a linear rail assembly.

The assembly allows the robot to move side-to-side along the spout deck to clean all spouts. Then, it moves off the spout deck once it completes the cleaning cycle. This configuration maintains sufficient room for the robot to perform its tasks while also ensuring that operators can safely enter the area to perform other duties.

Protective fencing and multiple entry and exit points will also be incorporated for additional operator safety and efficiency. The majority of retrofit work can typically be completed pre-outage, leaving sufficient time during the maintenance outage for robot installation and commissioning.

Robots can relieve worker strain but require careful integration and deployment. Source: Valmet

Smelt spout-cleaning robots proven in the field

In June 2023, Valmet installed its first smelt spout-cleaning robot in North America at the Pixelle Specialty Solutions mill in Spring Grove, Penn. The new robot performs a smelt spout cleaning cycle every 30 minutes — twice as often as operators were previously able to perform the same task manually. Each cycle takes 15 minutes, and when the robot is not actively cleaning, it rests in its home position safely out of the way.

Physical safety barriers around the robot further protect the operators by triggering the robot to freeze if the barrier is broken. Operators can also remotely control the robot’s cleaning frequency and cycles using pre-programmed sequences. Meanwhile, an onboard camera mounted on the robot wrist allows for real-time inspection of the robot’s performance and troubleshooting from the safety of the control room.

By automating smelt spout cleaning with a robot, the manufacturer added another level of safety for its operators and improved productivity by freeing them up to perform other critical tasks. Additionally, the new robot has helped raise the boiler’s liquor quality, green-to-black liquor standard deviation, and smelt standard deviation by double digits.

Collaboration is key

When retrofitting a smelt spout robot to an existing recovery boiler or planning a new installation, it’s important to choose an automation designer that has industry experience and will collaborate on-site during the design phase.

Since every operation and facility is different, the installation of a smelt spout cleaning robot is not a cookie-cutter process. The designer will have to account for existing components around the spouts like piping, flex hoses and evaluate available structural beams for their ability to support the robot carriage and the linear rail.

A skilled designer will also provide an installation plan that avoids significant spout deck alterations, as changes can be costly and time-consuming.

Smelt spout cleaning robots are meant to work with operators, not replace them. Source: Valmet.

Technology works in harmony with humans

Automation often comes with the assumption of replacing human labor, but that is not the case with smelt spout cleaning robots. Instead, this technology works in harmony with boiler operators to increase their safety. It also frees them up to perform other essential recovery boiler tasks.

Helping operators feel safer and engaging them in a wider variety of tasks throughout their workday can make it easier for pulp and paper manufacturers to hire and retain personnel in these positions. With the efficiencies of automation and well-trained, experienced personnel, manufacturers can improve productivity in many areas, making robotics retrofits worth the investment.

About the author

Dan Morrison is Valmet’s product manager for Smelt Spout Systems and the Smelt Spout Cleaning Robot. The Espoo, Finland-based company is a leading global developer and supplier of process technologies, automation and services for the pulp, paper and energy industries.

Valmet and Körber recently established a joint venture to connect the FactoryPal platform with machinery expertise to streamline digital optimization across the production lines of tissue shop floors and beyond.

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The group’s board, as of November 2023, from left to right, back row: Dr. Sue Keay (chair), Brenton Cunningham, Christian Ruberg, Tim Bradley, Dr. Nathan Kirchner; front row: Dr. John Vial, Tamanna Monem, Kathie van Vugt, Nicci Rossouw, Angus Robinson. Source: Robotics Australia Group

The robotics industry in Australia stands at the precipice of a transformative era, driven by a shared vision of sustainability and innovation. At the forefront of this movement is the Robotics Australia Group, an organization committed to nurturing a comprehensive robotics ecosystem.

From companies developing cutting-edge robotic technologies to educational institutions cultivating future talent, the group supports all facets of this burgeoning industry. Its mission aligns with the broader national objectives, as recently underscored by the Australian government’s National Robotics Strategy.

National Robotics Strategy points the way to innovation

Ed Husic, MP and the minister for industry and science, recently announced the National Robotics Strategy. It marks a significant milestone for the Australian robotics sector, said the Robotics Australia Group.

“The strategy not only highlights the current achievements, but also lays a robust foundation for future developments,” stated Dr. Nathan Kirchner, founding director of the group. “It is a call to industry stakeholders to collaborate and drive forward this ambitious vision.” 

This strategy aims to accelerate the adoption of robotics and automation technologies across various industries, a move that is integral to the broader vision of a “Future Made in Australia.” The strategy is imbued with optimism, promising substantial advancements and positioning Australia as a leader in robotics innovation on the global stage.

Minister Husic’s declaration signaled the Australian government’s commitment to harnessing the potential of robotics to address the country’s unique challenges.

Some examples of the world-leading field robotics delivered by group members. Source: Robotics Australia Group

Minister recognizes Robotics Australia contributions

The group said its contributions have been instrumental in shaping the current landscape of the Australian robotics industry. During his announcement of the National Robotics Strategy, Husic acknowledged its sustained efforts, active participation in the development of the strategy, the contributions made through publishing Australian Robotic Roadmaps, and continued advocacy.

“We have deep pockets of robotics excellence in Australia, we will become greatly more competitive on the world stage by joining them together,” said Kirchner. “The National Robotics Strategy is a significant step towards that. I am very proud that the underpinning groundwork of the Robotics Australia Group has been recognized.”

The organization has worked to support various stakeholders within the ecosystem. By fostering collaborations, facilitating research and development, and promoting educational initiatives, it said it has created a fertile ground for the robotics industry to thrive. The group added that it is working to ensure that the benefits of robotics and automation are accessible to a broad range of industries and applications.

Robotics provides Australia a strategic advantage

”We have overcome the core challenges of a very large land and sparsely populated country in order to deliver a number of notable outcomes,” said Kirchner. “Nevertheless, through doing so, we have developed a significant strategic advantage in the field hard robotics” 

Australia’s geographical and demographic characteristics make it an ideal candidate for pioneering advanced robotics, asserted the group. The country’s vast landmass, coupled with a relatively small and dispersed population, creates a unique set of challenges that robotics can effectively address. Remote areas often require complex tasks to be completed, and robots can significantly enhance efficiency and safety in these environments.

Moreover, Australia boasts a remarkable depth of local talent and expertise in both hardware and software aspects of robotics, said the organization.

Industries such as mining, ports, transport and logistics, construction, agriculture, and defense have long benefited from Australia’s field-hardened robotics intellectual property, the group added. This robust foundation of expertise and innovation positions Australia to leverage robotics in solving critical problems and improving operational efficiencies across these sectors, it said.

One of the cutting-edge manufacturing installations developed by Applied Robotics, a group member. Source: Robotics Australia Group

Sector celebrates wins and looks ahead

“The announcement of the National Robotics Strategy is an exciting and commendable first step,” said the group. “However, it is essential to recognize that this is merely the beginning. The path to a fully realized, sustainable robotics industry in Australia requires continued effort and focus. While we celebrate this significant achievement, it is crucial to remain vigilant and committed to solidifying these initial steps to ensure long-term progress.”

The future of robotics in Australia holds immense potential, it noted. By using the momentum generated by the National Robotics Strategy, the nation’s industry can aspire to new heights on the global stage. This requires a concerted effort from all stakeholders to foster an environment conducive to innovation, collaboration, and international exchange, the group said.

“With the National Robotics Strategy as a guiding framework, Australia is poised to become a global leader in robotics and automation,” said Kirchner.

This vision can only be realized through collective effort and a strategic approach to international collaboration. By establishing a bi-directional conduit for deep commercial exchange in robotics and AI, Australia can position itself at the forefront of technological innovation.

The future success of the robotics industry hinges on the ability to integrate advanced technologies into practical applications that address real-world challenges. The group said that it and other industry stakeholders must continue to advocate for policies and initiatives that support research, development, and the commercialization of robotics technologies.

“The commitment of the Robotics Australia Group to building a sustainable robotics industry in Australia is both inspiring and crucial,” Kirchner said. “Their efforts, coupled with the strategic direction provided by the National Robotics Strategy, pave the way for a future where robotics and automation play a central role in addressing the nation’s unique challenges. By celebrating current achievements and maintaining a steadfast focus on future goals, Australia can achieve remarkable advancements in the robotics industry.”

In this journey, it is essential to remain proactive, collaborative, and visionary. With a collective effort, the vision of a “Future Made in Australia” powered by advanced robotics is not just a dream, but also an imminent reality. The group is currently spearheading the production of the third edition of the Robotics Roadmap for Australia, scheduled for release in 2025.

“Together, we can propel Australia to new heights of innovation and global leadership in the robotics sector,” said the group.

About the author

Dr. Nathan G.E. Kirchner is a serial startup founder and advisor, corporate ventures advisor, professor, and founding director of a peak body. He has been recognized as one of “Australia’s Most Innovative” by Engineers Australia and one of the “Top Ten Young Scientists” by Popular Science magazine.

With over 25 years in industry and academia, Kirchner has founded and led several robotics-AI startups, and he serves as a founding director of the Robotics Australia Group. Kirchner is also a venture partner at a leading hardware-first venture capital firm.

He has held prestigious positions such as head of robotics at a major construction company and at Stanford University, the University of Technology Sydney, and Ohio State University.

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Organization: Slip Robotics
Country: U.S.
Website: www.sliprobotics.com
Year Founded: 2019
Number of Employees: 11-50
Innovation Class: Application & Market

Imagine you’re a truck driver finally arriving at your destination after hours of driving. Once you drop off your cargo, you know you have hours more to go before the end of your workday.

In between all this driving, you spend a significant amount of time simply waiting for your trailer to be unloaded and loaded again. While there are robots that can unload pallets or boxes individually, Slip Robotics has taken a different approach to the problem.

Instead of creating a robotic arm to pick items individually, the Atlanta-based company developed SlipBot, also known as an automated loading robot (ALR).

It’s a large, omnidirectional mobile robot that can carry up to eight full pallets and a total of 6 tons. Once the pallets are on the ALR, it autonomously drives into a trailer for transport to the next destination.

When it gets there, it drives off the truck and into the warehouse. Once the truck has been unloaded, the ALRs waiting in the wings can drive onto the trailer.

This can reduce driver wait time from 1.5 hours down to just five minutes, said Slip Robotics. The company also said it can load 20 pallets per minute without driving a forklift into a trailer.

Besides reducing wait times for divers, Slip claimed that its robots can load eight times as many trailers with the same number of operators. It can also reduce damage by 40% by reducing touches and impacts in material handling.

Finally, the company said its systems can improve worker safety. Twenty-five percent of industrial accidents involve a loading dock, noted Slip Robotics, and ALRs make it so operators never need to enter trailers to unload, load, or secure.

Register now.

Explore the RBR50 Robotics Innovation Awards 2024.

RBR50 Robotics Innovation Awards 2024

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GrayMatter automated manually intensive tasks at Lawrence Brothers. Source: GrayMatter Robotics

Like businesses in other industries, U.S. manufacturers face widening labor shortfalls and need automation to help fill those gaps. GrayMatter Robotics today announced that it has raised $45 million in Series B funding. The Carson, Calif.-based company said it plans to use the investment to expand to meet customer demand. 

“We founded GrayMatter to enhance productivity while prioritizing workforce well-being,” stated Ariyan Kabir, co-founder and CEO of GrayMatter Robotics. “With our physics-based AI-powered systems, we are fulfilling our mission while unlocking new levels of efficiency. With our investors’ support, we are making a real difference for shop workers and addressing the critical labor shortages in manufacturing today.”

GrayMatter Robotics said it bundles proprietary artificial intelligence with off-the-shelf robots, sensors, and tools for application-specific, turnkey solutions. The company offers its systems through a robotics-as-a-service (RaaS) model and said they relieve shop floor workers of tedious and ergonomically challenging tasks. They can also enhance production capacity and reduce scrap, repair, and rework costs, it said. 

GrayMatter applies AI to production tasks

The $2.5 trillion U.S. manufacturing industry is grappling with a growing backlog of unfilled orders due to a severe labor shortage. Many of these roles are hazardous and demand extensive training, leading to a critical gap of 3.8 million unfilled jobs, according to Deloitte.

SK Gupta, Ariyan Kabir, and Brual Shah founded GrayMatter Robotics in 2020. The company said it holds 10 patents and has processed more than 7.5 million sq. ft. (about 700,000 sq. m) of product surface area.

GrayMatter said its proprietary GMR-AI technology enables robots to self-program and adapt to high-mix, high-variability manufacturing environments, providing consistent quality and reducing cycle times. 

Smart workcells with GrayMatter technology can autonomously handle complex tasks such as sanding, polishing, grinding, coating, and finishing, it added. By automating such jobs, businesses can meet global demand while also improving the quality of life for their workers, said the company. 

Products including Scan&Sand, Scan&Polish, Scan&Buff, and Scan&Grind can increase quality and consistency while reducing costs, said GrayMatter. Manufacturers can benefit a system availability of 95% to 98%, and most contingencies can be resolved in under five minutes, it said.

GrayMatter claimed that its systems can work two to four times faster than manual operations and that employee training that used to take six months can now be done in less than a day. In addition, the company said its robots can help businesses address sustainability goals by reducing consumption and consumable waste by 30% or more over traditional methods.

GrayMatter combines AI and robotics to improve finishing efficiency and reduce waste. Source: GrayMatter Robotics

Users report increased efficiencies

Over the past two years, GrayMatter Robotics has deployed robots across North America in aerospace, defense, specialty vehicles, marine, recreation, metal fabrication, and consumer products. The company said its RaaS model helps manufacturers enhance production capacity and reduce costs associated with scrap, repair, and rework.

“We are excited to partner with GrayMatter Robotics, as their AI-driven robotic solutions have enabled us to more efficiently address major demand growth in our operations stemming from increased football participation and market-share gains, ensuring consistent quality and throughput despite workforce staffing challenges,” said Drew Dixon, director of distribution and strategy at sports equipment maker Riddell.

“Collaborating with GrayMatter Robotics underscores Riddell’s ongoing commitment to innovation and excellence in both its manufacturing operations as well as the protective equipment it delivers to the field,” he added.

“GrayMatter helps us replace some of our more taxing manual labor,” said Melanie Protti-Lawrence, president of steel fabricator Lawrence Brothers Inc. “We are proud to partner with GrayMatter in an effort to provide longevity in the workforce. We’re constantly working toward a healthier work-life balance, with a focus on working to live rather than living to work.”

“Their robots are not just tools but [also] enablers of growth,” she said. “They allow our workers to engage in more meaningful and less physically taxing tasks, contributing to a healthier and more productive work environment.”

Investors help GrayMatter to grow

With the new capital, GrayMatter is actively hiring for a wide range of roles to meet customer demands, expanding its Los Angeles headquarters, and accelerating the development and deployment of its next-generation AI-powered robots.

Wellington Management led the Series B round, which also included NGP Capital, Euclidean Capital, Advance Venture Partners, and SQN Venture Partners. They joined existing investors 3M Ventures, B Capital, Bow Capital, Calibrate Ventures, OCA Ventures, and Swift Ventures.

“GrayMatter is driving a pivotal transformation in manufacturing with their advanced AI solutions,” said Sean Petersen, sector lead for private climate investing at Wellington Management. “Their ability to enhance productivity, energy efficiency and safety while managing costs, positions them uniquely in the market.”

Wellington Management Co. advises 2,500 clients in more than 60 countries. The Boston-based firm manages more than $1.2 trillion for clients, including pensions, endowments and foundations, insurers, and global wealth managers.

Wellington’s Private Investing Team has raised more than $8.5 billion in global assets, and it invests in multiple sectors and technologies. The team includes more than 1,000 professionals with private market experience with public market expertise, extensive networks, and robust research to benefit both investors and entrepreneurs.

“The combination of AI-driven technology and depth of domain expertise in the GrayMatter solution blew us away,” said Debjit Mukerji, partner at NGP Capital. “It is incredibly challenging to develop high-performance and ultra-reliable robots for such difficult manufacturing conditions.”

“Going to market with GrayMatter Robotics aligns with our mission to foster innovative solutions that drive efficiency and sustainability in manufacturing,” said Adi Leviatan, president of 3M’s Abrasives Division. “This technology addresses critical industry challenges and delivers significant value to our customers.”

The post GrayMatter raises $45M Series B to ease robot programming for manufacturers appeared first on The Robot Report.

Zebra’s portfolio includes FlexShelf robots for parts fulfillment. Source: Zebra Technologies

Only 1 in 6 manufacturers has a clear understanding of its own processes, according to a new study from Zebra Technologies Corp. The report also found that 61% of manufacturers expect artificial intelligence to drive growth by 2029, up from 41% in 2024.

Zebra said the surge in AI interest, along with 92% of survey respondents prioritizing digital transformation, demonstrates manufacturers’ intent to improve data management and use new technologies that enhance visibility and quality throughout production.

“Manufacturers struggle with using their data effectively, so they recognize they must adopt AI and other digital technology solutions to create an agile, efficient manufacturing environment,” stated Enrique Herrera, industry principal for manufacturing at Zebra Technologies. “Zebra helps manufacturers work with technology in new ways to automate and augment workflows to achieve a well-connected plant floor where people and technology collaborate at scale.”

Zebra commissioned Azure Knowledge Corp. to conduct 1,200 online surveys among C-suite executives and IT and OT (information and operational technology) leaders within various manufacturing sectors. They included automotive, electronics, food and beverage, pharmaceuticals, and medical devices. Respondents were surveyed in Asia, Europe, Latin America, and North America.

The fully connected factory is elusive

Although manufacturers said digital transformation is a strategic priority, achieving a fully connected factory remains elusive, noted Zebra Technologies. The company asserted that visibility is key to optimizing efficiency, productivity, and quality on the plant floor.

However, only 16% of manufacturing leaders globally reported they have real-time, work-in-progress (WIP) monitoring across the entire manufacturing process, reported the 2024 Manufacturing Vision Study.

While nearly six in 10 manufacturing leaders said they expect to increase visibility across production and throughout the supply chain by 2029, one-third said getting IT and OT to agree on where to invest is a key barrier to digital transformation.

In addition, 86% of manufacturing leaders acknowledged that they are struggling to keep up with the pace of technological innovation and to securely integrate devices, sensors, and technologies throughout their facilities and supply chain. Zebra claimed that enterprises can use its systems for higher levels of security and manageability, as well as new analytics to elevate business performance.

Technology can augment workforce efficiency

Manufacturers are shifting their growth strategies by integrating and augmenting workers with AI and other technologies over the next five years, found Zebra’s study. Nearly three-quarters (73%) said they plan to reskill labor for data and technology usage, and seven in 10 said they expect to augment workers with mobility-enabling technology.

Manufacturers are implementing tools including tablets (51%), mobile computers (55%), and workforce management software (56%). In addition, 61% of manufacturing leaders said they plan to deploy wearable mobile computers.

Across the C-suite, IT, and OT understand how labor initiatives must extend beyond improving worker efficiency and productivity with technology. Six in 10 leaders ranked ongoing development, retraining/upskilling, and career path development to attract future talent as high priorities for their organizations.

Automation advances to optimize quality

The quest for quality has intensified as manufacturers across segments must do more with fewer resources. According to Zebra and Azure’s survey, global manufacturers said today’s most significant quality management issues are real-time visibility (33%), keeping up with new standards and regulations (29%), integrating data (27%), and maintaining traceability (27%).

Technology implementation plans are addressing these challenges. Over the next five years, many executives said they plan to implement robotics (65%), machine vision (66%), radio frequency identification (RFID; 66%), and fixed industrial scanners (57%).

Most survey respondents agreed that these automation decisions are driven by factors including the need to provide the workforce with high-value tasks (70%), meet service-level agreements (SLAs; 69%), and add more flexibility to their plant floors (64%).

Zebra Technologies shares regional findings

• Asia-Pacific (APAC): While only 30% of manufacturing leaders said they use machine vision across the plant floor in APAC, 67% are implementing or planning to deploy this technology within the next five years.
• Europe, the Middle East, and Africa (EMEA): In Europe, reskilling labor to enhance data and technology usage skills was the top-ranked workforce strategy for manufacturing leaders to drive growth today (46%) and in five years (71%).
• Latin America (LATAM): While only 24% of manufacturing leaders rely on track and trace technology in LATAM, 74% are implementing or plan to implement the technology in the next five years.
• North America: In this region, 68% of manufacturing leaders ranked deploying workforce development programs as their most important labor initiative.

The Manufacturing Vision Study provided insights around digitalization and the connected factory. Source: Zebra Technologies

Zebra to discuss digital transformation

While digital transformation is a priority for manufacturers, achieving it is fraught with obstacles, including the cost and availability of labor, scaling technology solutions, and the convergence of IT and OT, according to Zebra Technologies. The Lincolnshire, Ill.-based company said visibility is the first step to such transformation.

Emerging technologies such as robotics and AI enable manufacturers to use data to identify, react, and prioritize problems and projects so they can deliver incremental efficiencies that yield the greatest benefits, Zebra said. The company said it provides systems to enable businesses to intelligently connect data, assets, and people.

Zebra added that its portfolio, which includes software, mobile robots, machine vision, automation, and digital decisioning, can help boost visibility, optimize quality, and augment workforces. It has more than 50 years of experience in scanning, track-and-trace, and mobile computing systems.

The company has more than 10,000 partners across over 100 countries, as well as 80% of the Fortune 500 as customers. Zebra is hosting a webinar today about how to overcome top challenges to digitalization and automation.

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Realtime Robotics demonstrates a multi-robot workcell during Mitsubishi Electric’s visit. Credit: Eugene Demaitre

BOSTON — As factories and warehouses look to automate more of their operations, they need confidence that multiple robots can conduct complex tasks repeatedly, reliably, and safely. Realtime Robotics has developed hardware-agnostic software to run and coordinate industrial workcells smoothly without error or collision.

“The lack of coordination on the fly is a key reason why we don’t see multiple robots in many applications today — even in machine tending, where multiple arms could be useful,” said Peter Howard, CEO of Realtime Robotics (RTR). “We’re planning with Mitsubishi Electric to put our motion planner into its CNC controller.”

The company last month received strategic investment from Mitsubishi Electric Corp. as part of its ongoing Series B round. Realtime Robotics said it plans to use the funding to continue scaling and refining its motion-planning optimization and runtime systems. 

Last week, a high-ranking delegation from Mitsubishi Electric visited Realtime Robotics to celebrate the companies’ collaboration. RTR demonstrated a workcell with four robot arms from different vendors, including Mitsubishi, that was able to optimize motion as desired in seconds.

“Mitsubishi Electric is a multi-business conglomerate, a technology leader, and one of the leading suppliers of factory automation products worldwide,” said Dr. Toshie Takeuchi, executive officer and group president for factory automation systems at Mitsubishi. “I see this partnership as the perfect point where experience meets innovation to create value for our customers, stakeholders, and society.”

She and Howard answered the following questions from The Robot Report:

Mitsubishi Electric, Realtime Robotics integrate technologies

How is Realtime Robotics’ motion-optimization software unique? How will it help Mitsubishi Electric’s customers?

Takeuchi: Realtime Robotics’ software is unique in many ways. It starts with the ability to do collision-free motion planning. From there, the motion planning in single robot cells as well as multirobot cells can be automatically optimized for cycle time.

Our customers will benefit by optimizing cycle time to improve production efficiency and reducing the amount of engineering efforts required for equipment design.

Howard: Typically, to provide access for multiple tools at once, you need an interlocked sequence, which loses time. According to the IFR [which recognized the company for its “choreography” tool], up to 70% of the cost of a robot is in programming it.

With RapidPlan, we automatically tune for fixed applications, saving time. Our cloud service can consume files and send back an optimized motion plan, enabling hundreds of thousands of motions in a couple of hours. It’s like Google Maps for industrial robots.

Does Mitsubishi have a timeframe in mind for integrating Realtime’s technology into its controls for factory automation (FA)? When will they be available?

Takeuchi: We are starting by integrating RTR’s motion-planning and optimization technology into our 3D simulator to significantly improve equipment and system design.

Our plan is to incorporate this technology into our FA control systems, including PLCs and CNCs, and this integration is currently under development and testing, with a launch expected soon.

Howard: We’re currently validating and characterizing for remote optimization with customers. We’re also doing longevity testing here at our headquarters.

In the demo cell, you couldn’t easily program 1.7 million options for four different arms, but RapidPlan automates motion planning and calculates space reservations to avoid obstacles in real time. We do point-to-point, integrated spline-based movement.

Toyota asked us for a 16-arm cell to test spot welding, and we can add a second controller for an adjacent cell. We can currently control up to 12 robots for welding high and low on an auto body.

Mitsubishi Electric recently launched the RV-35/50/80 FR industrial robots — are they designed to work with Realtime’s technology?

Takeuchi: Yes, they are. Our robots are developed on the same platform which seamlessly integrate with RTR’s technology.

Howard: For example, Sony uses Mitsubishi robots to manufacture 2-cm parts, and we can get down to submillimeter accuracy if it’s a known object with a CAD file.

Cobots are fine for larger objects and voxels, but users must still conduct safety assessments.

MELCO’s Dr. Takeuchi changes optimization parameters during RTR demonstration by Kevin Carlin, chief commercial officer. Source: Realtime Robotics

RTR optimizes motion for multiple applications

What sorts of applications or use cases do Mitsubishi and Realtime expect to benefit from closer coordination among robots?

Takeuchi: Our interaction with and understanding from customers suggest that almost all manufacturing sites are continuously in need of increasing production, efficiency, profitability, and sustainability.

With our collaboration, we can reduce the robots’ cycle time, hence increasing efficiency. Multi-robot applications can collaborate seamlessly, increasing throughput and optimizing floor space.

By implementing collision-free motion planning, we help our customers reduce the potential for collisions, thereby reducing losses and improving overall performance.

Howard: It’s all about shortening cycle times and avoiding collisions. In Europe, energy efficiency is increasingly a priority, and in Japan, floor space is at a premium, but throughput is still the most important.

Our mission is to make automation simpler to program. For customers like Mitsubishi, Toyota, and Siemens, the hardware has to be industrial-grade, and so does the software. We talk to all the OEMs and have close relationships with the major robot suppliers.

This is ideal for uses cases such as gluing, deburring, welding and assembly. RapidSense can also be helpful in mixed-case palletizing. For mobile manipulation, RTR’s software could plan for the motion of both the AMR [autonomous mobile robot] and the arm.

Members of Realtime Robotics and Mitsubishi Electric’s teams celebrate their collaboration. Source: Realtime Robotics

Mitsubishi strengthens partnership

Do you expect that the addition of a member to Realtime Robotics’ board of directors will help it jointly plan future products with Mitsubishi Electric?

Takeuchi: Yes. Since our initial investment in Realtime Robotics, we have both benefited from this partnership. We look forward to integrating the Realtime Robotics technology into our portfolio of products to continue enhancing our next-gen products with advanced features and scalability.

Howard: RTR has been working with Mitsubishi since 2018, so it’s our longest customer and partner. We have other investors, but our relationship with Mitsubishi is more holistic, broader, and deeper.

We’ve seen a lot of Mitsubishi Electric’s team as we create our products, and we look forward to reaching the next steps to market together.

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As shown at CVPR, Omniverse Cloud Sensor RTX microservices generate high-fidelity sensor simulation from
an autonomous vehicle (left) and an autonomous mobile robot (right). Sources: NVIDIA, Fraunhofer IML (right)

NVIDIA Corp. today announced NVIDIA Omniverse Cloud Sensor RTX, a set of microservices that enable physically accurate sensor simulation to accelerate the development of all kinds of autonomous machines.

NVIDIA researchers are also presenting 50 research projects around visual generative AI at the Computer Vision and Pattern Recognition, or CVPR, conference this week in Seattle. They include new techniques to create and interpret images, videos, and 3D environments. In addition, the company said it has created its largest indoor synthetic dataset with Omniverse for CVPR’s AI City Challenge.

Sensors provide industrial manipulators, mobile robots, autonomous vehicles, humanoids, and smart spaces with the data they need to comprehend the physical world and make informed decisions.

NVIDIA said developers can use Omniverse Cloud Sensor RTX to test sensor perception and associated AI software in physically accurate, realistic virtual environments before real-world deployment. This can enhance safety while saving time and costs, it said.

“Developing safe and reliable autonomous machines powered by generative physical AI requires training and testing in physically based virtual worlds,” stated Rev Lebaredian, vice president of Omniverse and simulation technology at NVIDIA. “Omniverse Cloud Sensor RTX microservices will enable developers to easily build large-scale digital twins of factories, cities and even Earth — helping accelerate the next wave of AI.”

Omniverse Cloud Sensor RTX supports simulation at scale

Built on the OpenUSD framework and powered by NVIDIA RTX ray-tracing and neural-rendering technologies, Omniverse Cloud Sensor RTX combines real-world data from videos, cameras, radar, and lidar with synthetic data.

Omniverse Cloud Sensor RTX includes software application programming interfaces (APIs) to accelerate the development of autonomous machines for any industry, NVIDIA said.

Even for scenarios with limited real-world data, the microservices can simulate a broad range of activities, claimed the company. It cited examples such as whether a robotic arm is operating correctly, an airport luggage carousel is functional, a tree branch is blocking a roadway, a factory conveyor belt is in motion, or a robot or person is nearby.

Microservice to be available for AV development 

CARLA, Foretellix, and MathWorks are among the first software developers with access to Omniverse Cloud Sensor RTX for autonomous vehicles (AVs). The microservices will also enable sensor makers to validate and integrate digital twins of their systems in virtual environments, reducing the time needed for physical prototyping, said NVIDIA.

Omniverse Cloud Sensor RTX will be generally available later this year. NVIDIA noted that its announcement coincided with its first-place win at the Autonomous Grand Challenge for End-to-End Driving at Scale at CVPR.

The NVIDIA researchers’ winning workflow can be replicated in high-fidelity simulated environments with Omniverse Cloud Sensor RTX. Developers can use it to test self-driving scenarios in physically accurate environments before deploying AVs in the real world, said the company.

Two of NVIDIA’s papers — one on the training dynamics of diffusion models and another on high-definition maps for autonomous vehicles — are finalists for the Best Paper Awards at CVPR.

The company also said its win for the End-to-End Driving at Scale track demonstrates its use of generative AI for comprehensive self-driving models. The winning submission outperformed more than 450 entries worldwide and received CVPR’s Innovation Award.

Collectively, the work introduces artificial intelligence models that could accelerate the training of robots for manufacturing, enable artists to more quickly realize their visions, and help healthcare workers process radiology reports.

“Artificial intelligence — and generative AI in particular — represents a pivotal technological advancement,” said Jan Kautz, vice president of learning and perception research at NVIDIA. “At CVPR, NVIDIA Research is sharing how we’re pushing the boundaries of what’s possible — from powerful image-generation models that could supercharge professional creators to autonomous driving software that could help enable next-generation self-driving cars.”

Foundation model eases object pose estimation

NVIDIA researchers at CVPR are also presenting FoundationPose, a foundation model for object pose estimation and tracking that can be instantly applied to new objects during inference, without the need for fine tuning. The model uses either a small set of reference images or a 3D representation of an object to understand its shape. It set a new record on a benchmark for object pose estimation.

FoundationPose can then identify and track how that object moves and rotates in 3D across a video, even in poor lighting conditions or complex scenes with visual obstructions, explained NVIDIA.

Industrial robots could use FoundationPose to identify and track the objects they interact with. Augmented reality (AR) applications could also use it with AI to overlay visuals on a live scene.

NeRFDeformer transforms data from a single image

NVIDIA’s research includes a text-to-image model that can be customized to depict a specific object or character, a new model for object-pose estimation, a technique to edit neural radiance fields (NeRFs), and a visual language model that can understand memes. Additional papers introduce domain-specific innovations for industries including automotive, healthcare, and robotics.

A NeRF is an AI model that can render a 3D scene based on a series of 2D images taken from different positions in the environment. In robotics, NeRFs can generate immersive 3D renders of complex real-world scenes, such as a cluttered room or a construction site.

However, to make any changes, developers would need to manually define how the scene has transformed — or remake the NeRF entirely.

Researchers from the University of Illinois Urbana-Champaign and NVIDIA have simplified the process with NeRFDeformer. The method can transform an existing NeRF using a single RGB-D image, which is a combination of a normal photo and a depth map that captures how far each object in a scene is from the camera.

Researchers have simplified the process of generating a 3D scene from 2D images using NeRFs. Source: NVIDIA

JeDi model shows how to simplify image creation at CVPR

Creators typically use diffusion models to generate specific images based on text prompts. Prior research focused on the user training a model on a custom dataset, but the fine-tuning process can be time-consuming and inaccessible to general users, said NVIDIA.

JeDi, a paper by researchers from Johns Hopkins University, Toyota Technological Institute at Chicago, and NVIDIA, proposes a new technique that allows users to personalize the output of a diffusion model within a couple of seconds using reference images. The team found that the model outperforms existing methods.

NVIDIA added that JeDi can be combined with retrieval-augmented generation, or RAG, to generate visuals specific to a database, such as a brand’s product catalog.

JeDi is a new technique that allows users to easily personalize the output of a diffusion model within a couple of seconds using reference images, like an astronaut cat that can be placed in different environments. Source: NVIDIA

Visual language model helps AI get the picture

NVIDIA said it has collaborated with the Massachusetts Institute of Technology (MIT) to advance the state of the art for vision language models, which are generative AI models that can process videos, images, and text. The partners developed VILA, a family of open-source visual language models that they said outperforms prior neural networks on benchmarks that test how well AI models answer questions about images.

VILA’s pretraining process provided enhanced world knowledge, stronger in-context learning, and the ability to reason across multiple images, claimed the MIT and NVIDIA team.

The VILA model family can be optimized for inference using the NVIDIA TensorRT-LLM open-source library and can be deployed on NVIDIA GPUs in data centers, workstations, and edge devices.

VILA can understand memes and reason based on multiple images or video frames. Source: NVIDIA

Generative AI drives AV, smart city research at CVPR

NVIDIA Research has hundreds of scientists and engineers worldwide, with teams focused on topics including AI, computer graphics, computer vision, self-driving cars, and robotics. A dozen of the NVIDIA-authored CVPR papers focus on autonomous vehicle research.

“Producing and Leveraging Online Map Uncertainty in Trajectory Prediction,” a paper authored by researchers from the University of Toronto and NVIDIA, has been selected as one of 24 finalists for CVPR’s best paper award.

In addition, Sanja Fidler, vice president of AI research at NVIDIA, will present on vision language models at the Workshop on Autonomous Driving today.

NVIDIA has contributed to the CVPR AI City Challenge for the eighth consecutive year to help advance research and development for smart cities and industrial automation. The challenge’s datasets were generated using NVIDIA Omniverse, a platform of APIs, software development kits (SDKs), and services for building applications and workflows based on Universal Scene Description (OpenUSD).

AI City Challenge synthetic datasets span multiple environments generated by NVIDIA Omniverse, allowing hundreds of teams to test AI models in physical settings such as retail and warehouse environments to enhance operational efficiency. Source: NVIDIA

About the author

Isha Salian writes about deep learning, science and healthcare, among other topics, as part of NVIDIA’s corporate communications team. She first joined the company as an intern in summer 2015. Isha has a journalism M.A., as well as undergraduate degrees in communication and English, from Stanford.

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igus has acquired Atronia, its partner for the iSense EC.W sensor. Source: igus

The combination of sensing with motion plastics, which eliminate the need for lubricants, promises easier-to-maintain machinery for Industry 4.0. igus, a global leader in motion plastics and moving cable management systems, last week acquired the majority stake in Atronia Tailored Sensing.

“The acquisition of Atronia by igus is a promising partnership that will undoubtedly lead to further breakthrough innovations and improved technology integration,” stated Carlos Alexandre Ferreira, manager at Atronia Tailored Systems. 

Gafanha da Nazaré, Portugal-based Atronia develops wireless products for measuring and monitoring applications. The company said it supports product-development strategies including innovation, renewables, and sensing.

Since 2016, Atronia has supported igus with smart plastic sensors. These sensors monitor the condition of the product, whether it needs to be serviced or replaced, or whether a problem is occurring. igus said this strategic acquisition is intended to help expand its market offerings for for networked plastic components.

Industry 4.0 demands mass production of critical sensors

Industry 4.0 encompasses automation, artificial intelligence, and networking for greater productivity, agility, and safety. igus said its goal is to mass-produce next-generation products and make them accessible to small and midsize businesses (SMBs).

For years, igus has invested in research and development for new types of smart plastics. The Rumford, R.I.-based company‘s lines include plain bearings, energy chains, and cables that are equipped with sensors and integrated into the Internet of Things (IoT).

“Intelligent predictive-maintenance software calculates optimum maintenance times and alerts technicians in good time via e-mail and text message in the event of critical conditions to prevent expensive system failures,” explained igus. The company recently won an RBR50 Robotics Innovation Award winner for a gripper for its ReBeL collaborative robot.

Michael Blass, CEO of igus e-chain Systems, and Carlos Alexandre Ferreira, manager of Atronia Tailored Systems, celebrate the development of new Industry 4.0 products together. Source: igus GmbH

Atronia acquisition part of igus strategy

“By acquiring Atronia, we can harmonize the processes, systems, and teams of both companies even better, which will lead to synergies and efficiency gains in the long term,” said Michael Blass, CEO of e-chain Systems at igus. “This allows us to start series manufacturing for the Industry 4.0 era and make the products accessible to small and medium-sized companies with limited budgets and little experience.”

The collaboration between igus and Atronia resulted in the iSense EC.W sensor. Mounted on energy chain crossbars, it records the chain’s state and remaining service life.

Customers have given positive feedback about the sensor’s cost-effectiveness and intuitive design, said Atronia and igus. The partnership plans to jointly create more products in the future.

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The Robotics Manufacturing Hub is modular, adaptable, and multi-use, with OEM diversity. Source: The ARM Institute

When the ARM Institute launched its Robotics Manufacturing Hub about a year ago, it quickly realized that U.S. manufacturers weren’t looking at robotics and automation because they weren’t interested in the technology. Instead, the barriers to automation loomed so large that it was impossible for small and midsize firms to know where to start.

When the ARM Institute announced its no-cost Robotics Manufacturing Hub for manufacturers in the Pittsburgh region, its pipeline of interested manufacturers rapidly filled. With the ARM Institute offering a pathway to minimize the risks they associate with robotics and automation, U.S. manufacturers were, and still are, eager to explore the possibilities.

Larger manufacturing firms can more easily navigate the process of implementing automation. With greater general resources, in-house R&D, financing to invest in the upfront costs, and more time to explore solutions, they’ve more successfully been able to see the process through from start to finish.

Small and midsize manufacturers (SMMs) have to navigate more risk. They need to spend more time understanding how the changes will affect their operations. They often lack in-house robotics expertise, and they need systems that will dynamically meet their needs without requiring constant upkeep when, in many cases, their workforce is already strained.

The ARM Institute’s Robotics Manufacturing Hub is a free resource to help manufacturers navigate these barriers and others by identifying the best business cases for robotics, testing the systems within the manufacturer’s budget, and offering a path to implementation. Part of this solution includes the ability for SMMs in Southwestern Pennsylvania to work directly with the institute’s team of robotics engineers and get hands-on with advanced technologies in the institute’s Pittsburgh facility.

Register now.

ARM Institute shares case studies

Since the Robotics Manufacturing Hub’s creation, the ARM Institute has worked with several manufacturers in the Pittsburgh region to explore their challenges and help them understand where robotics can address these challenges.

For example, the ARM Institute worked with a manufacturer of castings and forgings to automate its manual quality-inspection process. Partnering with FARO and NEFF Automation through the Robotics Manufacturing Hub, the ARM Institute performed a proof-of-concept of a Universal Robots cobot controlling a FARO laser scanner. The manufacturer plans to pursue implementation.

The ARM Institute also worked with a company that needed to package heavy iron and steel parts into shipping containers, creating an ergonomically uncomfortable task for a human worker. In this situation, requirements for the robotic end effector were highly specific, and it’s critical to calculate the correct pick place on the parts and speed limitations of the robot to move heavy parts and prevent failure or injury.

The ARM Institute is working with its member CapSen Robotics on a solution.

CapSen Robotics has designed end effectors to sort metal parts. Source: CapSen Robotics

Inside the Robotics Manufacturing Hub facility

Much of this work is completed using the ARM Institute’s headquarters as a neutral ground for exploration and prototyping, giving manufacturers access to equipment before they commit to installing any system.

This facility is modular, adaptable, and multi-use, with OEM diversity to directly meet each manufacturer’s individual needs. ARM Institute engineers work directly in the lab and interface between suppliers and manufacturers to act in the SMM’s best interest and ensure that the work will address the specific challenges the company is facing.

Below is a brief overview of the equipment available through the Robotics Manufacturing Hub and application areas that can be addressed using this equipment:

Collaborative robots:

• Universal Robots (UR) 5e
• Yaskawa HC10
• FANUC CRX-10 Ai/L
• FANUC CRX-20 Ai/L

The cobots can be configured for the following applications:

• Small part handling
• Pick and place
• Vision-guided grasping for pick-and-place applications
• Machine tending
• Process tasks including gluing and dispensing
• Inspection with Faro ARM Quantum with Laser line probe and CMM
• Inspection with Cognex 2D imaging
• Inspection with Cognex 3D imaging

Industrial robots

• Epson VT6L
• Yaskawa GP-88
• Yaskawa GP-180
• Yaskawa Weld Cell with positioner

The industrial robots can be configured for the following applications

• Large part handling
• Large part palletizing
• Large part pick and place
• Force controlled grinding and polishing
• Welding

Get involved with the Robotics Manufacturing Hub

Small and midsize manufacturers in the Pittsburgh region can get a free automation assessment and use the Robotics Manufacturing Hub at no cost, thanks to funding from the Southwestern Pennsylvania Region’s Build Back Better Regional Challenge Award. Now is a great time to get started with the hub, as the ARM Institute is looking to work with more manufacturers.

In the future, the ARM Institute hopes to expand these services to manufacturers beyond this region and encourages those with interest in using or housing these services to reach out. In addition, the ARM Institute’s member ecosystem can use the Robotics Manufacturing Hub as a benefit of membership.

According to the ARM Institute’s “Future of Work” study released last week, industry trends include keeping people in the loop and the need for organizations to learn how to use data as artificial intelligence increases in importance. As a result, the institute noted that manufacturers and training centers must develop programs to help workers develop the skills needed to stay competitive and adapt to new technologies.

U.S. manufacturing resiliency is the cornerstone of our national security. The ARM Institute’s Robotics Manufacturing Hub addresses a critical need in helping to provide SMMs with the resources that they need to explore and implement automation, enhancing their competitiveness and benefiting the full manufacturing ecosystem.

About the author

Larry Sweet last year became director of engineering at the Advanced Robotics for Manufacturing (ARM) Institute in Pittsburgh. He has experience in bringing emerging technologies into production by increasing their Technology Readiness Level, concurrent with improvements in factory floor processes and workforce skills.

Sweet was previously the director for worldwide robotics deployment at Amazon Robotics, leading technology transition and system integration for all internally developed automation into Amazon’s global network. He has also held senior manufacturing and technology roles at Symbotic, the Frito-Lay, United Technologies, ABB, FANUC, and GE. Sweet spoke at the 2024 Robotics Summit & Expo in May.

Editor’s note: This article is syndicated from The Robot Report sibling site Engineering.com.

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In Episode 153 of The Robot Report Podcast, editors Steve Crowe and Mike Oitzman discuss the news of the week. Our featured guest on the show this week is Sankalp Arora, co-founder and CEO of Gather AI. We catch up with Sankalp to learn how his company‘s drone inventory management product is evolving.

The second featured interview is with Jake Hall, the “Manufacturing Millennial,” and Scott Sizemore, director of commercial marketing at motor provider ElectroCraft.

Show timeline

• 5:45: News
• 25:20: Interview with Sankalp Arora, co-founder and CEO of Gather AI
• 58:59: Interview by Jake Hall, the Manufacturing Millennial, with Scott Sizemore, director of commercial marketing at ElectroCraft

Register now.

In the news this week

1. Investor Dean Drako acquires Cobalt Robotics
   • Cobalt Robotics has been acquired by investor Dean Drako, and the name of the security robot firm has been changed to Cobalt AI to more accurately represent the company’s direction and the products it offers.
   • Drako is the founder and CEO of Eagle Eye Networks, in addition to a number of other enterprises and side projects. Cobalt AI fits closest to the Eagle Eye Smart Video Surveillance portfolio.
2. Waymo expands its service area 
   • Robotaxi developer Waymo announced that it’s expanding its service area in Phoenix. The company has added 90 square miles to what was already its largest service area in Metro Phoenix. Waymo’s service now covers 315 square miles of the Valley.
   • In addition, Zoox announced that it will begin testing in Austin and Miami, the fourth and fifth public testing locations for the Amazon subsidiary.
3. OpenAI is restarting its robotics research group
   • OpenAI, which is best known for ChatGPT, is restarting its robotics research group. The San Francisco-based company has been a pioneer in generative artificial intelligence and is returning to robotics after a three-year break.
   • The reboot comes after the company shut down its robotics group in July 2021. That shutdown was prior to all of the interest in generative AI after OpenAI released ChatGPT to the world.
4. See this disc golf disc-throwing robot:

The post Gathering warehouse inventory data — plus an update from ElectroCraft appeared first on The Robot Report.

Organization: Universal Robots
Country: Denmark
Website: https://www.universal-robots.com/
Year Founded: 2005
Number of Employees: 500+
Innovation Class: Technology, Product & Services

Universal Robots A/S has been the world’s leading developer of collaborative robot arms for a number of years. In 2023, the Teradyne subsidiary generated $375 million in revenue. Teradyne has said that its robotics portfolio, which also includes Energid (motion planning software) and Mobile Industrial Robots (autonomous mobile robots) has penetrated less than 5% of its market opportunity.

Odense, Denmark-based Universal Robots continued to diversify its cobot lineup in 2023 with the introduction of the UR30. With a 30 kg (66.13 lb.) lifting capacity, 1,300 mm (51.2 in.) reach, and weight of 63.5 kg (139.9 lb.), the UR30 can tend larger machines, palletize heavy products, and support high-torque screw driving.

Built on the same architecture as the UR20, the UR30 cobot arm offers more payload capacity in a compact footprint. Anders Billesø Beck, vice president of strategy and innovation at Universal Robots, told The Robot Report that the UR30 was in development for more than a year before it was introduced. He said that, despite the popularity of the UR20, some customers wanted a robot with a smaller footprint and a higher payload capacity.

The UR30 offers six degrees of freedom and a new “steady mode” that the company said opens up the cobot to different screwdriving applications, including in the automotive industry.

The diversification of its product line should enable Universal Robots to maintain its position atop the cobot arm market. While the UR30 isn’t the first collaborative robot to offer a 30 kg payload, it comes with UR’s top-notch global support, industry-leading accessories, training, and service programs. This continues to make UR a true one-stop shop for a user’s collaborative robotics needs.

Register now.

Explore the RBR50 Robotics Innovation Awards 2024.

RBR50 Robotics Innovation Awards 2024

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NVIDIA CEO Jensen Huang and Foxconn CEO Young Liu celebrate their cooperation. | Source: Foxconn

Hon Hai Technology Group, better known as Foxconn, this week said they plan to jointly build an advanced computing center in Kaohsiung, Taiwan. At the core of the center will be the NVIDIA Blackwell platform. The companies made the announcement at Computex 2024. 

NVIDIA said the cutting-edge computing center will be anchored by the super chip GB200 servers and consist of a total of 64 racks and 4,608 GPUs. The electronics manufacturer will contribute its production scale and said it expects to complete the center by 2026. 

The companies said their latest collaboration demonstrates their commitment to building servers to drive artificial intelligence, electric vehicles (EVs), smart factories, smart cities, robotics, and more. 

“A new era of computing has dawned, fueled by surging global demand for generative AI data centers,” stated Jensen Huang, founder and CEO of NVIDIA. “Foxconn stands at the forefront as a leading supplier of NVIDIA computing and a trailblazer in the application of generative AI in manufacturing and robotics.”

“Leveraging NVIDIA Omniverse and Isaac robotics platforms, Foxconn is harnessing cutting-edge AI and digital twin technologies to construct their advanced computing center in Kaohsiung,” he added.

Cooperation continues for Foxconn with new superchip 

This isn’t the first time Foxconn and NVIDIA have collaborated. The company has worked closely with NVIDIA on various product development projects. NVIDIA said Foxconn has excellent vertical integration capabilities and is a vital partner for the new GB200 Grace Blackwell Superchip. 

The superchip connects two NVIDIA B200 Tensor Core GPUs to the NVIDIA Grace CPU over a 900GB/s ultra-low-power NVLink chip-to-chip interconnect. The company said that for the highest AI performance, GB200-powered systems can be connected with the NVIDIA Quantum-X800 InfiniBand and Spectrum-X800 Ethernet platforms.

Register now.

NVIDIA and Foxconn plan for the facility

The partners said that NVIDIA’s AI technology will drive Foxconn’s three smart platforms: Smart Manufacturing, Smart EV, and Smart City. The new facility will use NVIDIA Omniverse to create digital twins for these platforms.

Foxconn plans to use image-recognition technology combined with its autonomous mobile robots (AMRs) to provide optimal capacity utilization in smart manufacturing. The companies said they will also take on production-line planning, which will encompass the existing manufacturing of AI servers and electric vehicle assembly plants. 

Foxconn subsidiary Foxtron’s Qiaotou automotive manufacturing facility will be one of Foxconn’s benchmark AI factories. Currently under construction, the site will use digital twins connected to cloud technologies. The company also hopes to collaborate between virtual and physical production lines.

In addition, the facility is set up with digital real-time monitoring to ensure high-quality manufacturing of an electric bus. 

NVIDIA and Foxconn plan to collaborate on future electric vehicle models designed by Foxconn. Currently, the company is negotiating projects with traditional European and American automakers. The partners also said they plan to develop a “cabin-driving-in-one” smart travel system. 

The post NVIDIA, Foxconn to build advanced computing center in Taiwan appeared first on The Robot Report.

Operators use OmniCore V400XT to control a large robot with Robot Studio. Source: ABB Robotics

Thanks to advances in cloud computing, perception technology, and artificial intelligence, industrial and other robots are becoming smarter and more capable. ABB Robotics today launched its next-generation OmniCore platform, which can now control most of its automation line.

“For our customers, automation is a strategic requirement as they seek greater flexibility, simplicity, and efficiency in response to the global megatrends of labor shortages, uncertainty, and the need to operate more sustainably,” said Sami Atiya, president of ABB’s Robotics & Discrete Automation Business Area. “Through our development of advanced mechatronics, AI, and vision systems, our robots are more accessible, more capable, more flexible, and more mobile than ever.”

“But increasingly, they must also work seamlessly together, with us, and each other to take on more tasks in more places,” he added. “This is why we are launching OmniCore, a new milestone in our 50-year history in robotics; a unique, single control architecture – one platform, and one language that integrates our complete range of leading hardware and software.”

Three out of four European companies struggle to find workers for jobs such as welding and fulfillment, noted Atiya. He added that more than 2.1 million U.S. manufacturing jobs will be unfilled by 2030, and businesses need supply chain resilience. In response, Atiya said, OmniCore will provide greater simplicity and flexibility to ABB’s customers.

ABB Robotics, which has offices in Zurich; Vasteras, Sweden; and Auburn Hills, Mich., noted that OmniCore is the product of more than $170 million in investment. The unit of ABB Group called it “a step change to a modular and futureproof control architecture that will enable the full integration of AI, sensor, cloud, and edge computing systems to create the most advanced and autonomous robotic applications.”

While ABB has offered OmniCore since 2018, its plan was always to make it its unified control platform, explained Marc Segura, division president of ABB Robotics. “Now we are in our pivotal moment where we are launching it to the cover almost our entire robotics portfolio,” he told The Robot Report.

Register now.

OmniCore offers speed and accuracy

ABB Robotics said OmniCore delivers robot path accuracy at a level of less than 0.6 mm, and it can control the motion of multiple robots running at speeds of up to 1,600 mm per second (3.5 mph). This builds on ABB’s experience with automotive manufacturing. It also opens opportunities for precision automation in areas such as arc welding, assembly of mobile phone displays, gluing, and laser cutting.

“Our automotive customers are extremely competent and helped push the boundaries of what is possible,” Segura said. “OmniCore also complies with and exceeds the most stringent cybersecurity standard and is future-proof for AI and digitalization.”

He claimed that the updated platform enables its robots to operate up to 25% faster and to consume up to 20% less energy compared with its previous controller. It is open to peripherals including sensors, as well as external devices such as dispensers or welding tools, for numerous processes. It also supports up to 100 safety configurations.

Platform covers hardware, software ecosystem

OmniCore is built on a scalable, modular control architecture that offers a wide array of functions, making it suitable for new industries embracing automation, such as biotechnology and construction, said ABB. It also includes more than 1,000 hardware and software features to help customers design, operate, maintain, and optimize operations.

OmniCore is the top level of a software stack that includes the RobotWare operating system and Robot Studio for simulation and design, said Segura. He cited software features such as OptiFact for managing data, Absolute Accuracy, and PickMaster Twin, as well as hardware options spanning from external axis and vision systems to fieldbuses.

“The OmniCore difference is its ability to manage motion, sensors, and application equipment in a single holistic unified system,” he said. “Our new, next-generation platform is more than a controller. It is the backbone of value creation, which includes a complete, integrated software ecosystem.”

“For example, OmniCore enables automotive manufacturers to increase production speed, offering tremendous competitive advantage, increasing press-tending production from 12 to 15 strokes per minute to produce 900 parts per hour,” Segura said. “Some of these applications are now available even as pre-integrated configurations, enabling our systems integrators to reduce commissioning times even further.”

“Software and AI are paramount for us at ABB,” Atiya said. “We have more than 100 projects ongoing to bring AI into our products and for our own productivity.”

He noted that AI enables inspection of welds 20 times faster than with humans, and up to 1,400 picks per hour with its robots. Atiya predicted that generative AI such as ChatGPT will broaden accessibility of robotics.

ABB says OmniCore offers seven benefits for robotics deployment and management. Source: ABB Robotics

ABB plans for compatibility across its robots

ABB said its history of robotics innovation began with “the world’s first microprocessor-controlled robot” in 1974. It launched the RobotStudio software in 1998 and acquired Sevensense in 2024 to bring industry-leading AI-based navigation technology to its autonomous mobile robots (AMRs) purchased with ASTI in 2021.

OmniCore replaces ABB Robotics’ IRC5 controller, which will be phased out in June 2026. The company plans to continue to support its customers with spare parts and services through the remaining lifetime of robots using it. Is new hardware needed to upgrade?

Existing users need only to make some minimal re-engineering for connectivity, wiring, and the customized user interface on the FlexPendant, replied Segura. No additional equipment or training is needed, but online and in-person training are available.

“We are still compliant with all the sensors used on IRC5 and have added more opportunities on the OmniCore platform,” Segura said. 

In addition to managing motion, sensors, and application equipment, OmniCore will be able to manage ABB’s collaborative robots, acknowledged Segura. “We also plan to run all our AMRs and mobile manipulators to run on OmniCore in the near future,” he said. 

After the “Fanta challenge” in 2009, which showed three robots working together, ABB demonstrated three robot arms moving around with champagne glasses to show off OmniCore’s precise motion control for production and safety purposes.

OmniCore is now available, and ABB is taking orders. The company is hosting a virtual conference for the new OmniCore platform at 10:00 CEST (4:00 a.m. EDT) on June 4, 2024. It will be available to those who register after the launch event.

The post ABB releases OmniCore platform for control across its robotics line appeared first on The Robot Report.

MAP is a cloud-based command center that can design and manage automated manufacturing workcells. | Source: Vention

Vention Inc. yesterday announced a collaboration with NVIDIA Corp. to bring industrial automation to small and midsize manufacturers. The companies said they plan to use NVIDIA’s artificial intelligence and accelerated computing to advance cloud robotics. 

The partners said they will use AI to create near-accurate digital twins significantly faster and more efficiently. With this technology, manufacturers can efficiently test their projects before they invest, according to Vention and NVIDIA.

The companies said they will jointly develop generative designs for robot cells, co-pilot programming, physics-based simulation, and autonomous robots. 

“The Vention ecosystem with NVIDIA’s robotics technology and AI expertise will help bring pivotal innovation to the manufacturing renaissance and overall industry,” stated Etienne Lacroix, founder and CEO of Vention. “Now, even the most complex use cases can become achievable for small and medium[-size] manufacturers.”

Vention to simplify MAP experience with AI

Vention said its Manufacturing Automation Platform (MAP) allows clients to manage industrial robots directly from their Web browsers. The Montreal-based company said MAP draws on a proprietary dataset of several hundred thousand workcell designs created since its founding in 2016.

The announcement marks a year of collaboration with NVIDIA to apply AI to industrial automation projects. Vention said it intends to use AI to simplify the user experience in the cloud and on the edge.

Register now.

NVIDIA to help bring AI to the forefront of manufacturing

NVIDIA said its technology, combined with Vention’s modular hardware and plug-and-play motion control, will bring cutting-edge AI to the forefront of manufacturing. The companies said they aim to widen access to industrial automation for small and midsize manufacturers.

“Vention’s cloud-based robotics platform, powered by NVIDIA AI, will empower industrial equipment manufacturing companies everywhere to seamlessly design, deploy, and operate robot cells, helping drive the industry forward,” stated Deepu Talla, vice president of robotics and edge computing at NVIDIA.

Vention said it is already known for its user-friendly software products and interface, and it expects to announce a number of new products resulting from this collaboration in Q3 of 2024.

This isn’t the first time NVIDIA and Vention have worked together. Vention — along with Solomon, Techman Robot, and Yaskawa –are among the companies using NVIDIA’s Isaac Manipulator for building AI-based robotic arms. 

Vention also recently announced a partnership with Flexxbotics to support robot-driven manufacturing. The companies said their combined offering for robotic workcell digitalization in next-generation machining environments is now available.

The post Vention, NVIDIA partner to bring automation and AI to small manufacturers appeared first on The Robot Report.

Adapta has developed robots for specific use cases. Source: Adapta Robotics

Starting a robotics company is always challenging, as inventors and entrepreneurs scramble to get access to capital and tap the local talent pool. However, identifying the right applications and markets is a good place to begin, according to the co-founders of Adapta Robotics & Engineering SRL. 

The Bucharest, Romania-based company said it specializes in addressing challenges in settings where traditional automation has fallen short and in use cases that have been overlooked. Adapta’s model includes a one-time robot purchase fee, plus annual license and maintenance fees.

In 2017, the company’s founders developed the first prototype of MATT, a delta robot for device testing, at rinf.tech with European Union support. In 2021, they branded Adapta and developed the Effective Retail Intelligent Scanner, or ERIS, for scanning items on store shelves. In 2022, Adapta became an independent brand.

Mihai Craciunescu, co-founder and CEO, and Diana Baicu, co-founder and lead robotics engineer of Adapta Robotics, spoke with The Robot Report about the company’s approach to designing and customizing robots for applications that were previously difficult to automate.

Adapta Robotics started with competition team

What is the origin of Adapta Robotics?

Craciunescu: Cristian Dobre, Diana, and I started the company in 2015, but we had been a group in the University Politehnica of Bucharest, the largest technical university in Romania, starting in 2012. Our goal was to create robots for competitions, and we participated in competitions from Europe to Turkey to China.

We won most of them, and we’ve built line-following robots, sumo robots, and self-driving cars in a small scale for Continental. We then said, “OK, what’s next?” We had to choose between pure research in academia or starting a robotics company, and we wanted the more applied side of robotics, based on our success in those challenges.

How did you determine what tasks or applications to try to automate? As we saw at R-24 and other events, there are already a lot of robots out there, from disinfection to materials handling.

Craciunescu: Our first idea, the MATT testing robot, came totally by chance. We were exposed to a U.S. manufacturer that did its software development and testing in Romania before pushing updates to its whole fleet of mobile phones. Phones in the Asian market were a testing ground for it, and all of its software testing processes were automated.

During one test, the screen went blank, but behind the scenes, the processor was still doing the right tasks. The company didn’t catch it, and millions of phones went blank. Knowing about this issue and having the robotics experience we did, we said, “Why don’t we build a robot to test these phones?”

Then, we slowly saw similar needs in other industries like automotive manufacturing. Infotainment systems need to be tested, and automakers want to make sure everything works as intended. Many other use cases derive from that.

We identified the problems and clients, and then we did a bit of market research. There were a couple of competitors, but they were very expensive and had limited capabilities.

How did you arrive at inventory with ERIS?

Craciunescu: We had a client with a couple of issues in its stores. One, some products had labels showing the wrong prices.

Another was that [the retailer] knew from its systems that it had a certain amount of products in stock, but it did not know if those products were on the shelf or in the warehouse somewhere. If they’re not on the shelf, that means lost opportunities.

The company was aware of the solutions on the market, including inventory robots from the States, but those were too expensive for the task it wanted to do. And, if you scan a shelf with an autonomous robot, and you have a report that 20 labels are wrong, you still need a human to manually replace the labels.

The company didn’t care about the autonomous part; it just wanted the problem to be fixed, so we have a scanner on a pushcart. We focused on reading the labels correctly, detecting the products that are out of stock or soon will be, and creating a report on just those three features.

We’re also exploring other functionalities like planogram compliance, making sure the products are placed where they’re supposed to be, while checking if you have multiple labels of the same product displayed on the shelf. But that was the main idea: Create a relatively cheap solution to scan the shelf and give you an audit.

Adapta founders, from left: Cristian Dobre, Mihai Craciunescu, and Diana Baicu. Source: Adapta Robotics

Know thy customers

Were you developing these systems for specific customers, or did you already have broader applications in mind? Did Adapta Robotics develop them with multiple customers at once, or did you start with one customer and then branch out?

Craciunescu: It was mixed. As an engineer, you can design all kinds of robots. Our approach is to try to solve problems that are specific to a certain industry.

Having the client tell us what they need is the most valuable feedback. We could think of different solutions in our lab, but when you are doing that in real life, you can quickly see what things to focus on.

It’s very important to have a client in the loop when you design something. Ideally, you should have more than one, but as we got started, we needed at least one to can use, let’s say, the first version of the robots. It can see what doesn’t work, and then you can improve on that. After you have a prototype, then you can look around in the market.

Baicu: When we’re getting this information from clients and designing a product, we try to make something more general that can be easily customized afterwards. You don’t want it customized from the beginning because that limits other possibilities, even for the development for that customer.

But then you need first customers that are patient, right? They have to be willing to work with you and understand that not everything’s going to work right away.

Craciunescu: That would be the ideal setup. Some clients were really pushy, and it was up to us to deliver. They can understand that something doesn’t work, but we had to fix it as soon as possible. We had quite a bit of pressure.

The MATT delta robot for product testing. Source: Adapta Robotics

Co-founders share lessons learned

The robotics development process is rarely a straight path. What are some of the lessons that you learned or surprises along the way?

Baicu: We know this from when we were building competition robots, but it became even more clear [with Adapta Robotics]. It’s about the design choices overall. … You need to have the right components and architectures from the beginning, at least with durability and scalability in mind, because otherwise, it will be very complicated to modify everything rather than just thinking about it from the beginning.

Of course, there’s a balance between how far you can go in these choices. Very expensive components or very complicated architectures take more time to implement and more money.

When you’re sourcing components, whether it’s sensors or actuators, do you have preferred partners? How did you identify what would work best, given your and your customers’ priorities?

Craciunescu: It’s an iterative process. Let’s take ERIS as an example. Initially, we made an educated guess about the best-in-class cameras we needed.

When we actually connected them to the computer, we saw that they were on USB 3.0. We had the right cameras, but the communication protocol made the processor waste a lot of time converting the serial information to actual pictures and data metrics you could use.

We wanted that processor to run other things, so the next step was to find some cameras on another protocol. We then looked at different distributors and so on.

Another aspect we did not have experience with was, for example, cameras to measure the distances. Our approach was to buy depth cameras from all the major manufacturers and test them internally. We had a couple of criteria — we knew we wanted to look at shelves that were up to 1 m in depth and knew the distances from the robot to the shelves.

We also looked at the company maturity, or if they could provide the cameras 10 years from now. If we’re happy with all these smaller decisions, we’ll pull the trigger.

If you know from prior experience what’s the right solution for you, that’s fine, but most of the time, you need tests to validate the right path. This makes R&D quite expensive, but sometimes, you don’t have the luxury to buy all the solutions out there.

The ERIS inventory-scanning system works with human associates. Source: Adapta Robotics

When to focus on integration and simulation

On the software side, Adapta Robotics’ customers may use different systems. How much work does integration involve?

Baicu: It’s a significant part of what we do. There’s a focus from the beginning on our side to create the software infrastructure and the intelligence as well, meaning the computer vision and algorithms, or machine learning and AI. It’s a process that needs to be supported.

First of all, there are the updates to improve or fix bugs, and at the same time, we maintain the algorithmic part with new data sets, examples, or retraining if needed.

How much do you rely on simulation for training and deployments?

Craciunescu: We try not to rely too much on simulation. We do some — for example, for mechanical stress testing. But we don’t go into the details like kinematics. We do what makes sense from an engineering point of view, as we want to build an actual product.

You can focus a lot on simulation, and that can be a trap because you can make the most beautiful simulations in the world and not have a product.

Baicu: At the same time, you can transpose simulations into real-life situations. The simulation is an idealized environment, so you have to introduce noise or variations, but it will never be the real world. Sometimes, it can be very complicated if you put too much effort on the simulation side.

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Adapta gives a glimpse of its roadmap

What is Adapta Robotics planning for this year?

Craciunescu: MATT is designed to be flexible and for multiple use cases. This year, we’re looking at specialized versions of MATT for different industries, like refurbishment, automotive, and medical.

It’s currently used in those industries with add-ons, but there are not models specifically designed for each industry, which could help the selling process.

Are you focusing more on productizing or re-engineering your technology? For instance, MATT’s software suite now works with a six degree-of-freedom robot arm.

Baicu: A bit of both. We now have clients and know their needs. Maybe we just present it differently or add some features that make the product easier to set up and use. Sometimes, it’s about creating new add-ons or complementary solutions that can respond to the needs in that field of activity.

Craciunescu: With ERIS, we already have a client that’s mostly in the logistics space and requires things like detecting of barcodes. It’s similar to retail but a different application. We’re exploring ways of reusing parts of the hardware and software that we’ve developed.

Are you in the midst of fundraising? Are you looking to expand to new markets internationally?

Craciunescu: Yes. We’re in the process of raising capital and are in a due diligence phase. We’re currently at 10 highly skilled professionals, but capital would allow us to be more aggressive in markets such as automotive.

Currently, 50% of our clients are in the U.S., and the rest are Western Europe. We have a couple of clients in India and Brazil as well.

At R-24, we discussed the Danish robotics scene. What is the industry like in Romania?

Craciunescu: Denmark is an outlier, and it’s doing very well. The European market in general doesn’t encourage R&D, which is very cash-intensive. If you look across Europe, robotics requires funding from the EU and from each individual state.

There are other robotics companies in Romania, and we have a lot of talent locally. We sometimes find out about one another at events outside of Romania.

Baicu: Romania is quite well-developed on the IT or software development side. It’s fairly complicated to have a discussion for what the needs are for a company that does hardware.

With the rise of AI, we need to have a deeper consideration for what we are putting our efforts into. We’re now seeing a bit of a shift, and are seeing a better attitude toward manufacturing and hardware.

Craciunescu: The brain drain really affects us. As a young student willing to learn about robotics, I had no mentors. That’s a problem for the medical industry as well and society as a whole.

Right now, we’re trying at Adapta to provide a space for new students to come and learn from professionals. We had the option of going abroad but decided to build something locally. Being part of the EU, we can basically scale up anywhere we want.

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