Goodbye to the hydraulic version of Atlas and hello to the electric model designed for commercialization. That’s the message from Boston Dynamics Inc., which yesterday retired the older version of its humanoid robot after 15 years of development and today showed a preview of its successor.

“The next generation of the Atlas program builds on decades of research and furthers our commitment to delivering the most capable, useful mobile robots solving the toughest challenges in the industry today: with Spot, with Stretch, and now with Atlas,” said the company in a blog post. Spot is a quadruped used in facilities inspection and other tasks, and Stretch is designed to unload trucks.

Boston Dynamics began with humanoids by sawing one of its pneumatically powered quadrupeds in half back in 2009. By 2016, the Waltham, Mass.-based company showed that its robot could walk, open a door, and maintain its balance while being shoved by a person holding a hockey stick, all without a tether.

Roboticists continued to improve Atlas, giving it a smaller form factor and more sensors, training its artificial intelligence, and enabling it to do increasingly impressive feats. They ranged from parkour and dancing to taking tools through a mock construction site.

In fact, it was that demonstration of Atlas manipulating a plank, picking up a bag of tools, and taking it to a worker that earned Boston Dynamics an RBR50 Robotics Innovation Award. The company will be exhibiting at the RBR50 Showcase at the Robotics Summit & Expo on May 1 and 2.

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Boston Dynamics evolves with the times

As capable as the YouTube darling was, the older version of Atlas still had limitations, both in range of motion and in terms of size and power usage. Boston Dynamics noted that it designed its legged robots to operate in unstructured environments, and it acknowledged that Atlas was initially a research and development project rather than a commercial product.

In the meantime, the company itself changed owners, from Google in 2013 to SoftBank in 2017 and most recently to Hyundai in 2020. Along with those changes came an increasing focus on robots such as Spot and Stretch serving industrial needs. To continue pure research, Hyundai founded the Boston Dynamics AI Institute in 2022.

“The AI Institute recently launched a new version of Spot with an API [application programming interface] designed for researchers,” said Robert Playter, CEO of Boston Dynamics. “We’re talking about how to jointly solve some big challenges — the diversity of manipulation tasks we need to do with this robot [Atlas] is huge, and AI is essential to enabling that generality.”

Playter told The Robot Report that Boston Dynamics needs results within two to three years, while the AI Institute has more of a five-year timeframe.

Robot lessons apply to fleets, new Atlas

“It takes a solid year from a clean sheet to a new robot,” said Playter. “We wanted to know that we could solve essential dexterous manipulation problems before releasing the product.”

Boston Dynamics learned numerous lessons from commercializing Spot and Stretch, he said. It has improved control policies, upgraded actuation, and minimized joint complexity. The new Atlas has three-fingered grippers.

The Orbit fleet management software, which initially applies to indoor deployments of Spot, could also help supervise Stretch and Atlas.

Atlas gets ready for mobile manipulation in industrial settings. Source: Boston Dynamics

“Everything we understood, from the time of launching Spot as a prototype to it being a reliable product deployed in fleets, is going into the new Atlas,” Playter said. “We’re confident AI and Orbit will help enhance behaviors. For instance, by minimizing slipping on surfaces at Anheuser-Busch, we proved that we can develop algorithms and make it reliable.”

“Now, 1,500 robots in our fleet have them running,” he added. “It’s essential for customers like Purina to monitor and manage fleets as a vehicle for collecting data. As we develop and download new capabilities, Orbit becomes a hub for an ecosystem of different robots.”

Safety and autonomy are basic building blocks

Boston Dynamics has considered safe collaboration in its development of the new Atlas. ASTM International is developing safety standards for legged robots.

“We recognized early on that Atlas is going to work in spaces that have people in them,” said Playter. “This sets the bar much higher than lidar with AMRs [autonomous mobile robots].”

“We started thinking about functionally safe 3D vision,” he recalled. “We started with Stretch inside a container, but ultimately, we want it going everywhere in a warehouse. Advanced, functionally safe, remote vision and onboard systems are essential to solving safety.”

While Spot and Atlas are often teleoperated, Playter said this is a necessary step toward greater levels of autonomy.

“Making the robots knowledgeable about different types of objects and how to grasp them, teleoperation is just a tool for providing examples and data to the robot,” he explained. “It’s not a useful way of building intuition, but it’s easier if you can operate robots at a higher and higher level. Like you don’t need to tell Spot where to plant its feet, you don’t want to tell Atlas where to grasp.”

In the new video below, the previous version of Atlas handles automotive parts and real products weighing up to 25 lb. (11.3 kg).

Atlas ready for rivals in the humanoid race

Over the past two years, the number of humanoid robots in development has rapidly grown. It now includes Agility Robotics‘ Digit, Tesla’s Optimus, and Figure AI‘s Figure 01. In the two past weeks alone, Rainbow Robotics, Sanctuary AI, and Mentee Robotics have all made announcements.

Investment has also been flowing to humanoid companies, with 1X Technologies raising $100 million in January, Figure AI raising $675 million in February, and Accenture investing in Sanctuary AI in March.

Humanoid robots have advanced in parallel with generative AI, and Playter said he welcomes the competition.

“There were three seminal events: Boston Dynamics got acquired for $1 billion, interest in Tesla’s robot validated what we’ve done for a long time, and the emergence of new AI holds the promise of generalization of tasks,” he said. “They’ve inspired lots of new players, but having new tech isn’t all you need to have a commercial product. You need to focus on a use case, build a reliable machine, and manufacture it in a way to build a business. We want to avoid a ‘humanoid winter,’ so rollouts have to be real.”

Playter added that practical design and proper implementation of AI will help differentiate robots rather than focusing on making them more human-like. The new version of Atlas demonstrated that point in how it stood up in the video at the top of this article.

“It’s not talking to a robot that moves the needle, but whether you can build a robot that eventually does 500 tasks,” he said. “Anthropomorphism blows things out of perspective. We did not want a human-shaped head for Atlas. We want people to remember it’s a machine and that it can move in ways humans can’t.”

The financial stability of the businesses involved will also be relevant for commercial success, said Playter. 

“It takes sustained investment; these are expensive products to launch,” he noted. “Having products already out helps build momentum.”

Atlas is humanoid — to a point. Source: Boston Dynamics

When will we see the new robot in the wild?

Boston Dynamics will begin testing the all-electric version of Atlas with parent company Hyundai and select partners next year, said Playter.

“We’re beginning in their factory,” he told The Robot Report. “In addition to the target application of a lot of parts movement — a special kind of logistics in automotive production — I think that will evolve as the dexterity of the robots improves over time.”

“We see robots in the workplace as an evolution, a continuum from Spot to Atlas,” asserted Playter. “Each product in the series informs the launch of the next.”

“Industries will have to figure out how to adapt and incorporate humanoids into their facilities,” he said. “We’ll actually see robots in the wild in factories beginning next year. We want a diversity of tasks.”

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igus relies on AI-supported low-cost robotics, smart maintenance, and AI-based online tools like the igusGO app to get customer applications ready for Industry 4.0. | Source: igus

igus GmbH will be introducing igusGO, an AI-powered app, alongside a series of smart sensor technologies at Hannover Messe. The company said it designed its latest sensor technologies “to streamline maintenance and optimize production processes for the lubrication-free industry of tomorrow.”

The Cologne, Germany-based company said igusGO is the centerpiece of its innovation. The app uses artificial intelligence to instantly identify optimization opportunities for designers using motion plastics. 

The app simplifies the selection process without the need for traditional catalog browsing, according to igus. The company said the app reflects its commitment to enhancing operational reliability and cost-efficiency across various applications, from heavy-duty machinery to everyday devices. 

“Our aim with igusGO and our suite of smart products is to navigate the vast potential of motion plastics with unprecedented efficiency and transparency,” stated Tobias Vogel, CEO of plain bearings and linear technology at igus.

Michael Blass, CEO of E-Chain Systems, added that innovations such as superwise, a digital service for comprehensive maintenance insights, can bolster competitiveness during challenging times. 

“By merging our innovative products with digital services, we’re demonstrating how our motion plastics can significantly enhance a wide array of applications, driving them towards a more sustainable and technologically advanced future,” he said.

The benefits of polymer bearings

igus cited its collaboration with RWTH Aachen University as an example of the economic and ecological advantages that its polymer bearings offer. They could result in potential savings of up to $14.9 million (€14 million) annually. 

Polymer bearings can also provide substantial CO₂ reductions, as exemplified by Heineken Brazil’s savings of 396.8 lb. (180 kg) of CO₂ equivalents per year through the switch to polymer bearings, said igus. 

igus also offers affordable, precise automation

igus also offers low-cost automation. The Rumford, R.I.-based company has introduced user-friendly robotics with AI-based voice and gesture control, exemplified by the ReBeL collaborative robot and its plug-and-play capabilities.

The company won a 2024 RBR50 Robotics Innovation Award for its $2,760 finger gripper for the cobot. igus said these advancements are complemented by its RBTX online marketplace, which facilitates access to compatible accessories and promotes an inclusive approach to automation for companies of all sizes. 

Earlier this year, igus launched a double-shaft stepper motor for its drylin linear technology. The company said the double-shaft design allows for precise control over linear motion, enabling a range of automation, transfer-station, and format-adjustment applications.

Editor’s note: At the Robotics Summit & Expo, which will be held in Boston, igus will exhibit at Booth 414. The company will also participate in a session on “Democratizing Automation” at 2:45 p.m. EDT on Wednesday, May 1. Register now to attend.

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Kiwibot will add intellectual property from AUTO Mobility Solutions to its delivery robot portfolio. Source: Kiwibot

Consolidation among mobile robot providers is not limited to warehouses. Kiwibot today announced that it has acquired AUTO Mobility Solutions Co.

“This strategic collaboration marks a significant milestone in both companies’ journeys towards innovation and safeguarding privacy in the robotics industry, particularly for intelligent robots sourced from China and deployed in the Western markets,” Kiwibot stated.

“The acquisition of AUTO is a game-changer for us, bringing a wealth of technological innovation and a strong patent portfolio that will significantly enhance our cybersecurity measures for AI-powered robotics,” asserted Felipe Chavez, founder and CEO of Kiwibot. “This move not only strengthens our position in the market, but also connects the manufacturing expertise from Asia with the AI development in the West securely.”

Kiwibot develops delivery robots

Berkeley, Calif.-based Kiwibot has developed autonomous robots using artificial intelligence. The company claimed that it is a market leader of robotic deliveries on U.S. college campuses.

Since 2017, Kiwibot said it has successfully deployed robots across the U.S., Dubai, and Saudi Arabia. In 2020, it raised pre-seed funding and was an early guest on The Robot Report Podcast. It raised $10 million for deliveries as a service (DaaS) in December 2023.

“Kiwibot is actively exploring opportunities to expand our robotic delivery services beyond college campuses,” Chavez told The Robot Report. “We will soon announce customers in two different categories.”

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AUTO brings cybersecurity expertise

“Becoming a part of Kiwibot opens up new avenues for our technologies and patents,” noted Sming Liao, CEO of AUTO Mobility Solutions. “Together, we are poised to redefine the landscape of autonomous delivery services, ensuring greater security and efficiency.”

The Taipei, Taiwan-based company was incubated by ALi Corp. and develops integrated circuit (IC) chips for AI, self-driving vehicles, robotics, the Internet of Things (IoT), and cybersecurity. Its systems feature advanced path planning, positioning, and obstacle-avoidance technology.

AUTO Mobility Solutions has built a patent portfolio in AI, IoT, and cybersecurity in Taipei. Source: Kiwibot

AUTO said its team will add more than 100 licensed patents to Kiwibot’s offerings.

“Our decision to join forces was solidified after recognizing the complementary nature of our technologies and the potential for a synergistic relationship,” said Chavez. “One of our investors from Taiwan introduced us, and we started the relationship as a customer for a custom cybersecurity chip.”

“The acquisition strategically positions us to bolster our cybersecurity infrastructure, especially considering the rising interest in AI and its associated vulnerabilities,” he added. “Together, Kiwibot and AUTO are looking to develop enhanced capabilities in autonomous navigation, AI-powered decision making, and advanced cybersecurity measures.”

Acquisition to expand global presence

The companies also said the acquisition will help the merged entity deliver leading systems globally and meet the evolving needs of both businesses and consumers.

“AUTO’s established presence in Taiwan and Shenzhen [China] will play a crucial role in helping Kiwibot navigate geopolitical and supply chain challenges,” explained Chavez. “Their expertise and strategic locations will aid in diversifying our supply chain and providing stability in our manufacturing and development processes, ensuring Kiwibot’s continued growth and scalability.”

Felipe Chavez, CEO of Kiwibot (left), and Sming Liao, CEO of AUTO (right). Source: Kiwibot

Kiwibot is still evaluating consolidation and rebranding, he told The Robot Report.

“The Taipei team will maintain a high degree of autonomy to leverage their specialized expertise and local knowledge effectively. While we are unified in our mission and strategy, we recognize the importance of fostering innovation through autonomous operations,” Chavez said. “We are currently evaluating how best to integrate our brands to reflect our unified strength while honoring the established identity and contributions of AUTO’s team.”

What are Kiwibot’s plans for the near future?

“Looking forward, Kiwibot’s roadmap includes the continuous improvement of our autonomous delivery robots, the expansion of our service areas, and the integration of AUTO’s technological advancement,” Chavez replied. “We are committed to pioneering the future of robotic services and ensuring a seamless and secure experience for our users. Stay tuned for exciting updates as we progress on this journey.”

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Agility Arc is a cloud-based platform for managing fleets of humanoids. Source: Agility Robotics

Agility Robotics made a couple of strategic moves this week as it continues to commercialize its Digit humanoid. Let’s start with the good news.

Agility is partnering with Manhattan Associates, a global leader in supply chain and omnichannel commerce. There are a lot of warehouse management systems (WMS) on the market, but as one source told The Robot Report, Manhattan Associates is “the standard bearer when it comes to large 3PL operations.”

Agility is joining the Manhattan Value Partner (MVP) program and the Manhattan Automation Network for warehouse automation providers. Manhattan and Agility will integrate Digit and Agility Arc, the company’s new fleet management software introduced at MODEX 2024, with the Manhattan Active Warehouse Management solution.

WMS integration an important step for Digit

Integrating new tools with existing systems can be challenging for warehouse operators. Ensuring compatibility with the industry-leading WMS is an important first step for Digit.

“Digit is already the world’s only bipedal robot currently delivering useful work for customers, increasing productivity and safety while helping workers with difficult and repetitive tasks in warehouse and manufacturing operations,” stated Peggy Johnson, CEO of Agility Robotics. “We’re thrilled to partner with Manhattan to streamline adoption of Agility’s solutions into existing best practices and bring Digit to more warehouses around the world.”

Manhattan Associates said Agility is the first humanoid to join both the MVP and the Manhattan Automation Network. Manhattan has similar partnerships with Exotec, a provider of automated storage and retrieval systems (ASRS) and Locus Robotics, the leading developer of autonomous mobile robots (AMRs).

“Companies are under enormous pressure to deliver more products faster and more efficiently, while facing massive and growing labor shortages,” said Eric Lamphier, senior director of alliances for Manhattan Associates. “Innovative robotics solutions, like Digit, can help fill those gaps, connecting islands of automation and improving operational efficiency.”

“We’re proud to be the first WMS provider to partner with a humanoid robotics provider,” he added. “Together, Agility and Manhattan are making it easy for customers to integrate cutting-edge technology, like Digit and Agility Arc, into their warehouse workflows.”

Agility Arc is a new cloud-based platform designed to give customers better control and insight into their Digit humanoids. Users can monitor the status and performance of each Digit, create workcells and workflows, and assign new tasks to the robots.

Agility Robotics also now offers a few accessories for the Arc platform, including a charging dock, a control pendant, and a workcell that comes with guarding, e-stops, monitored entrances, and more. Since there are no safety standards yet for humanoids, these robots will need to be caged off as they initially make their way into the world.

Agility Robotics lays off staff

Now for the bad news. Agility laid off an unspecified number of employees yesterday. Now-former employees posted about the layoffs on social media, and The Robot Report confirmed the reduction in staff. The company sent the following statement:

“As part of Agility’s ongoing efforts to structure the company for success, we have parted ways with a small number of employees that were not central to core product development and commercialization. At the same time, we are focused on meeting the extraordinary demand for bipedal robots across industrial use cases. That means ramping up production of Digit while continuing to win top-tier global customers, and adding new roles that meet these goals. We believe today’s actions will allow us to focus on the areas that drive productization, commercialization, and production of Digit.”

Johnson was named CEO of Agility Robotics one month ago. The veteran technology leader most recently served as CEO of Magic Leap, which produces augmented reality headsets. She led the company’s shift from consumer to enterprise and helped recapitalize the company.

Before Magic Leap, Johnson spent six years as executive vice president of business development at Microsoft. She reported directly to CEO Satya Nadella and was responsible for driving strategic partnerships and transactions to accelerate growth for the company and its customers.

Agility Robotics co-founder Damion Shelton, who served as CEO since the company’s founding in 2015, is now the company’s president and part of Johnson’s leadership team.

Humanoid robot race continues to accelerate

As we’ve said repeatedly over the past year, the humanoid race is heating up. And moves like this partnership with Manhattan, coupled with its fleet management system, show that Agility is the humanoid developer most ready to take on real-world work. The company has piloted its Digit humanoid with Amazon and GXO Logistics.

There are several other humanoid developers entering early pilots with customers. Figure recently raised $675 million and is working with BMW. And Apptronik is working with Mercedes-Benz.

Of course, all these humanoids still need to prove their reliability. NVIDIA is trying to help with its new foundation model for humanoids, called GR00T, that is designed to bring robotics and embodied AI together.

Accenture is also getting in on the action. Last week, it announced a strategic investment in Sanctuary AI, which is developing the Phoenix humanoid. The amount of the funding was not disclosed.

“AI-powered humanoid robots are essential to reinventing work and supporting human workers as labor shortage is becoming an issue in many countries and industries,” said Accenture.

You can learn more about the state of humanoids at the Robotics Summit & Expo, which takes place May 1-2 in Boston and is produced by The Robot Report and parent company WTWH Media.

Jonathan Hurst, co-founder and chief robot officer of Agility Robotics, will deliver a keynote called “Humanoid Robots Get to Work.” It will explore the technological breakthroughs propelling humanoids like Digit into real-world use cases. Attendees can learn about the ongoing challenges and opportunities and will go inside Digit’s first pilots.

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Digital transformation is becoming a major concern for engineers across industries. Source: Adobe Stock

Over the past year, I’ve spent a lot of time speaking with manufacturers about their digital transformation projects. They all have very different stories to tell because their application needs are distinct. But whether it’s a food manufacturer, a beverage producer, an automaker or a machine builder, they all have one thing in common: The need for community.

Turns out, digital transformation can be a lonely road where engineers are given a directive to “go digital,” and then left on their own to figure it out.

This exact scenario is happening at a large consumer packaged goods (CPG) company that makes many things, including toothpaste and dish detergent. An individual in charge of plant systems told me that he needs help sorting out where to start, what technologies to use, and who to involve in the process.

“Having a connection with people to bounce ideas off, or just understand what others have done to solve common digital transformation problems, would be helpful,” he said.

Attendees of Design World’s first annual Digital Transformation Forum, happening May 1-2, 2024 in Boston, will get that personal storytelling from some major manufacturers. Two of those in attendance include Sikorsky Lockheed Martin and ALTA Refrigeration, both sharing technology implementations that solve engineering and business problems while optimizing the way they work.

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Sikorsky’s digital transformation story

Sikorsky makes commercial and military aircraft, including the best-in-class Black Hawk helicopter. It needed to correct years of manually setting thresholds that have contributed to alert fatigue on operators. The company needed a way to streamline actionable alerts in a busy production environment.

Together with technology partner Strategic Maintenance Solutions, Sikorsky built a machine learning tool that automates the threshold-setting process for industrial metric data and delivers the right information to the right user at the right time. One of the key takeaways from this session is that you don’t have to be a data scientist to take action and find value with AI tools.

ALTA Refrigeration will outline a very different scenario that includes the adoption of an edge control architecture and the message queuing telemetry transport (MQTT) machine-to-machine communication protocol to completely change its business model.

The company has been designing and installing refrigeration systems across the U.S. for more than 45 years. For a long time, they were large, custom-designed systems that used a central machine room to deliver refrigerant to various facility areas through long, overhead piping runs.

Now, with modular refrigeration control units, ALTA can monitor its entire install base in minutes and energy usage per unit. When an alarm occurs, the system creates an interactive timeline of events. Using data analytics with remote monitoring improves serviceability, scalability, customer support, and operational efficiency.

Connect with the engineering community

Those are just two examples of the presentations at this live event. Attendees will also be able to interact with thought leaders from Intellic Integration, MIT, Deloitte, Siemens, PTC, and more. Networking is encouraged via a welcome reception and a mix and mingle with attendees from the two co-located events, the Robotics Summit & Expo and DeviceTalks Boston, to provide ample opportunity to meet engineers from other industries.

You can freely exchange ideas and make new connections at this forum. More importantly, it’s the start of your new digital transformation community. If you’re an engineer, technology decision-maker or an executive on a journey to modernize manufacturing, you need to be here.

The inspiration from your peers can lead to new ideas for your organization and, ultimately, innovation that will make your organization more competitive in the market.

Editor’s note: This article is syndicated from Design World, a sibling site to The Robot Report, and the Digital Transformation Forum is co-located with the Robotics Summit & Expo. Registration is now open.

About the author

Stephanie Neil is an executive editor at WTWH Media specializing in digital transformation, automation, AI, analytics, IoT, cybersecurity, robotics, simulation, and workforce issues. She shares the end-user perspective on the business value of operations processes.

Neil previously worked at CPG Next, OEM Magazine, and Automation World. She is based in Scituate, Mass.

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SwRI Workbench for Offline Robotics Development allows manufacturing engineers to independently use complex robotics and simplifies motion planning for seasoned developers. Source: Southwest Research Institute

An industry push for more automation is advancing the Robot Operating System, or ROS, beyond the academic and manufacturing domains into agriculture, automotive, retail, healthcare and more. Various forecasts project that the open-source advanced robotics market will grow more than 10% annually between 2024 and 2029.

These trends are motivating for robotics engineers at Southwest Research Institute (SwRI) and our colleagues at the ROS-Industrial Consortium and supporting industries. We also recognize that the usability of robotics software is still an impediment to even higher levels of adoption.

Over the years, the ROS-I Consortium has held frequent roadmapping sessions with a wide variety of end users and ROS developers to address ease of use and continuing education. The identified need is a lower barrier of entry for non-programmers (or entry-level developers) to harness the power of tools in the ROS ecosystem, but in a way that aligns with industry adoption of digital thread and Industry 4.0 strategies.

The traditional ROS workflow is software programming-intense, requiring developers deeply familiar with available ROS libraries and tools. Even experienced developers within the ROS-I ecosystem and beyond may spend significant time — days to weeks — on the initial setup and configuration of a ROS application.

Listening to the voice of our own developers, our diverse stakeholders, and consortium members, we heard the need for easier access to the ROS motion-planning tools, while maintaining a tie back to the CAD ecosystem where the products to be worked on are conceived and maintained.

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SWORD is a graphical toolkit for robotics developers

The Southwest Research Institute is launching the SwRI Workbench for Offline Robotics Development (SWORD) featuring a graphical toolkit for developing and testing advanced robotic motion-planning applications.

SWORD is implemented as a plugin to the open-source FreeCAD application, allowing users to integrate robotics capabilities into a cross-platform CAD environment. It provides a graphical interface to many powerful motion-planning libraries.

The goal is to bring ROS to a manufacturing/industrial audience in a way that is more approachable and resides in an environment that is familiar. Most manufacturing engineers are competent with CAD and understand their processes, often doing various forms of programs on process-oriented systems.

SWORD seeks to bring advanced motion-planning capability to this audience enabling to set up their systems and take advantage of these more advanced tools in their operational environments. Through the first Beta test, the team at SwRI has collected feedback from end users and is nearing the release the first version of SWORD. SWORD currently offers the capabilities below:

Environment modeling

• Create workcell model (robot, fixtures, end-of-arm tooling); see Figure 1 below.

  • Use CAD modeling tools or import existing CAD/mesh models

  • Use Convex Hull and Decomposition tools to generate collision geometry

• Import and export URDF (Unified Robotics Description Format) files

• Manipulate robot position

  • Joint Sliders to control individual joint positions

  • TCP Dragger to simulate movement using various IK solver

Figure 1: An example of URDF creation and evaluation in SWORD. Click here to enlarge. Source: Southwest Research Institute

Command language

• Define robot motion using either Cartesian or Joint waypoints

  • Currently waypoints must be manually defined, but import and CAD-generated waypoints are planned for an upcoming release.

• Specify different move segment types (joint/cartesian) and motion groups

• Insert supplementary commands (I/O, delays, etc.)

Motion planning

• Generate motion plan using a variety of Tesseract-supported path planners

  • Currently uses default Profiles (configuration) for each planner, but profile editing is planned for an upcoming release.

• Create custom planning pipelines for application-specific behavior; see Figure 2 below.

• Compute the Allowed Collision Matrix

  • Currently no way to review or adjust the results, but this functionality is planned for an upcoming release.

• Review computed motion trajectory

SWORD is officially released, and seats are available. You can request a trial version to understand if it is right for your organization. If you are interested in a trial license, or want to learn more or get a guided tour from SwRI, please contact Jeremy Zoss or Matt Robinson.

Figure 2: Setting up a motion planning pipeline for testing and evaluation in SWORD. Click here to enlarge. Source: Southwest Research Institute

About the author and the Southwest Research Institute

Matthew Robinson is program manager for ROS-Industrial Consortium Americas at the Southwest Research Institute. He was previously research team leader and a graduate fellow at the Edison Welding Institute. Robinson has participated in RoboBusiness Direct and has an M.S.W.E. from The Ohio State University.

Since 1947, the nonprofit SwRI in San Antonio, Texas, has taken a multidisciplinary approach to research and development for government and industry clients.

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3PL expert Sean Pineau will share his insights into automation and AI in the warehouse. Source: Locus Robotics

Artificial intelligence promises to revolutionize robotics and industries including supply chain and logistics. For all of the hype around generative AI, robotics developers, integrators, and warehouse operators need to separate the facts from fiction. At the 2024 Robotics Summit & Expo, Locus Robotics will offer some help in demystifying AI in the warehouse.

Sean Pineau, head of third-party logistics (3PL) segments at Locus Robotics, will present a session on “AI in the Warehouse: What You Really Need to Know” at 1:45 p.m. ET on Wednesday, May 1. He will discuss the considerations and potential benefits and impacts of implementing AI in the warehouse.

Pineau will also explain what “embodied AI” is, what is and is not AI, and how warehouse managers can optimize their operations with AI and robotics.

Sean Pineau, Locus Robotics

Speaker to discuss robots and AI in the warehouse

Pineau has a decade’s experience in leadership roles in the materials handling industry. He said his time at Dematic and Crown Equipment Corp. provided a deep understanding of automation.

In 2021, Pineau became an account executive focusing on the retail vertical market at Locus Robotics. The Wilmington, Mass.-based company is a leading provider of autonomous mobile robots (AMRs).

In recognition of his results-driven approach, relentless dedication, and strategic acumen, Locus recently appointed Pineau as head of 3PL segments.

About the Robotics Summit & Expo

The 2024 Robotics Summit & Expo will be the largest ever, according to WTWH Media, which also produces Mobile Robot Guide and The Robot Report. The event will be at the Boston Convention and Exhibition Center on May 1 and 2.

It will include up to 5,000 attendees, more than 200 exhibitors, various networking opportunities, a Women in Robotics breakfast, a career fair, an engineering theater, a startup showcase, and more!

New to the summit is the RBR50 Robotics Innovation Awards Gala. It will include a cocktail hour, a plated dinner, photo opportunities, and the chance to hear from the Robot of the Year, Startup of the Year, and Application of the Year winners.

Each RBR50 winner will receive two complimentary tickets to the Robotics Summit and RBR50 gala. A limited number of tickets is available to attendees, but they’re selling fast!

The Robotics Summit will be co-located with DeviceTalks, an event focused on medical devices, and the inaugural Digital Transformation Forum. Registration is now open for the event.

Learn from Agility Robotics, Amazon, Disney, Teradyne and many more.

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Delta exhibited its data center and other technologies at NVIDIA GTC 2024. Source: Delta Electronics

SAN JOSE, Calif. — Artificial intelligence and robotics both devour power, but simulation, next-generation processors, and good product design can mitigate the draw. At NVIDIA Corp.’s GTC event last week, Delta Electronics Inc. demonstrated how its digital twin platform, developed on NVIDIA Omniverse, can help enhance smart manufacturing capabilities.

“We’ve partnered with NVIDIA on energy-efficient designs to support AI,” Franziskus Gehle, general manager of the Power Solutions business unit at Delta, told The Robot Report. “We’ve co-developed 5.5 kW designs for 98% efficiency.”

The Taipei, Taiwan-based company explained how its technologies can benefit industrial automation and warehouse operations. Delta also showed its ORV3 AI server infrastructure product and DC converters and other technologies designed to support graphics processing unit (GPU) operations.

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Delta designs simulation to manage automation

Founded in 1971, Delta Electronics said it is a global leader in switching power supplies and thermal management products. The company’s portfolio includes systems for industrial automation, building automation, telecommunications power, data center infrastructure, electric vehicle charging, renewable energy, and energy storage and display.

Delta added that its energy-efficient products can support sustainable development. The company has sales offices, research and development centers, and factories at nearly 200 locations around the world. It provides articulated robot arms, SCARA robots, and robot controllers with integrated servo drives.

“Since 1995, Delta has supplied automation components, and it now offers a full product line,” said Claire Ou, senior principal for strategic marketing in the Power and System business group at Delta. “We’ve used NVIDIA simulation for our customers and ourselves, for machine tools and semiconductors.”

“Because Delta has a lot of factories around the world, it’s best to do test runs to fine-tune our hardware and software before implementation,” she told The Robot Report. “Our solutions can monitor and manage warehouses and factories for maximum productivity.”

In addition, Delta has developed its own standalone simulation software in addition to NVIDIA Omniverse, and it can integrate data from both. In the past, automation designers, manufacturers, and users worked with different tools, but customers are now optimistic about easier collaboration, said Ou.

“In 2012, Industry 4.0 was about digitalizing manufacturing,” she noted. “Since then, our management and monitoring systems have been integrated into global factories. We’re also working with data for construction and smart buildings.”

NVIDIA partners for digital twins to manage power

“We are honored to be the only power and thermal management solutions provider at NVIDIA GTC 2024, where we will showcase the NVIDIA Omniverse-powered digital twin we have developed, which underscores our superior expertise in next-generation electronics manufacturing,” stated Mark Ko, vice chairman of Delta Electronics. “We look forward to helping transcend the boundaries of energy efficiency in the AI realm using the latest technologies.”

Delta has deployed its power management technology to leading cloud solution providers (CSPs) and AI developers such as Meta (parent of Facebook), Microsoft, and Amazon Web Services, noted Gehle.

“Our customers have doubled their power requirements in the past six months rather than in years,” he said. “All of their road maps anticipate a significant increase in power demand, so they need management in place for next-generation GPUs and power-hungry generative AI.”

“We used digital twins and Omniverse to design and pre-qualify our products worldwide,” Gehle explained. “It’s important that our data center plans are aligned with those of our customers.”

At GTC, Delta presented an integrated Open Rack Version 3 (ORV3) system for AI server infrastructure with server power supplies boasting energy efficiency as high as 97.5%. It also included SD-WAN, Common Redundant Power Supply Units (CRPS) with 54Vdc output, ORV3 18kW/33kW HPR Power Shelves, a Battery Backup Unit (BBU), a Mini UPS, and a liquid cooling system.

In addition, the company showed its portfolio of DC/DC converters, power chokes, and 3D Vapor Chambers for GPU operations.

“The new era of AI-powered manufacturing is marked by digital twins and synthetic data, which can enhance efficiency and productivity before actual production begins,” said Rev Lebaredian, vice president of Omniverse and simulation technology at NVIDIA, in a release.

“By developing its digital platform on NVIDIA Omniverse, Delta can virtually link specific production lines and aggregate data from a diverse range of equipment and systems to create a digital twin of its operations,” he said. “And with NVIDIA Isaac Sim, it can generate synthetic data to train its computer models to achieve 90% accuracy.”

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Viam is a tool for developing software that comes with the cloud services necessary to prototype and build robots quickly. | Source: Viam

Viam, which offers a software platform for smart machines, yesterday announced that it has raised $45 million in Series B funding. This latest round brings the company’s total funding to date to $87 million.

Eliot Horowitz, co-founder and former chief technology officer of MongoDB, founded Viam in 2020. The New York-based company said the latest investment will enable it to accelerate enterprise partnerships, drive commercial innovation, and further develop its open-source platform.

“This investment affirms Viam’s commitment to innovation and strengthens our vision to empower developers with intuitive, powerful, and flexible tools that help transform the way software powers hardware,” stated Eliot Horowitz, founder and CEO, Viam. “Whether you’re in IoT [Internet of Things], robotics, smart home, or industrial automation, we’re empowering the next generation of startups, developers, and enterprises to move quickly and build better.”

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Viam provides platform for scalable development

Despite recent advances in artificial intelligence and machine learning and the prevalence of cloud and edge computing, software made to manage hardware has only made moderate gains, according to Viam.

This kind of software has been stymied by proprietary systems specific to individual machines, sensors, and equipment, the company asserted. This has led to complex constraints that frustrate developers, impede growth, and stifle progress, it said. 

Horowitz has experience in enterprise cloud computing from MongoDB, which is a source-available, cross-platform, secure, high-availability cloud database solution. That company said it is integrated into a number of enterprise applications used every day by millions of people.

Horowitz said he established Viam with the intent of establishing a similar platform for robotics development. He foresaw the need for software based on safe and performant cloud-computing principles as robotics progressed from point solutions to connected swarms of mobile robots and cloud-monitored systems.

Viam is a modular, interoperable, and open-source software platform that works across all hardware and any fleet of machines. In addition, its open architecture can remove costly and complex barriers to working with physical devices, the company claimed.

All of these features can speed up developer velocity and democratize access to open data. Viam added that this data can be used to inform AI and accelerate innovation in critical sectors such as industrial manufacturing, energy, and climate. 

Startup to invest in partnerships

Viam’s platform became generally available in May 2023. Since then, the company said it has been working with global enterprises and startups of all sizes to substantially accelerate time to market, decrease risks, increase developer velocity, improve operational efficiency, and craft modern end-user experiences.

Viam said it can help improve customer satisfaction and deliver increased revenue. Its Series B round included participation from previous investors Union Square Ventures and Battery Ventures. 

“Viam’s open architecture represents a paradigm shift that will bring the promises of robotics to the devices we use every day,” said Albert Wenger, partner at Union Square Ventures, in a release. “We’re thrilled to continue partnering with Viam in this exciting next chapter.”

This funding followed Viam’s announcement that it is working with the Whale and Vessel Safety Taskforce (WAVS). The partners will establish an open-source data-collection program and AI system for North Atlantic Right Whale conservation efforts.

They said the project showcases how the platform can be used for open data to drive collaboration and transparency. It will also demonstrate how Viam brings AI and actuation to the edge.

In addition, the company works with industrial, automation, and innovation teams to keep machines running smoothly on the edge. Viam said it’s working to enable device-to-cloud data pipelines to help manufacturers with real-time data monitoring, predictive maintenance, and remote diagnostics. 

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NVIDIA CEO Jensen Huang (left) with the Apollo humanoid robot. Source: Apptronik

SAN JOSE, Calif. — Among the highlights of GTC this week was the convergence of artificial intelligence and humanoid robotics. Apptronik Inc. announced that it working to integrate its Apollo humanoid robot with Project GR00T, NVIDIA Corp.’s new general-purpose foundation model for robot learning.

“The world is designed for humans — so it makes sense that humanoid robots are the type of robot best equipped to navigate, adapt, and interact with it,” said the Austin, Texas-based company. “Furthermore, humanoid robots comprise the ideal hardware for learning general-purpose skills by observing human demonstrations.”

“The combination of Apollo and Project GR00T will enable developers to take text, video, and human demonstrations as task prompts, learn generalizable skills like coordination and dexterity, and generate actions as output on the robot hardware,” Apptronik asserted. “Instead of simply repeating the actions in the training data, Apollo will recognize the environment and predict what to do next to achieve its goal.”

Apptronik said it is working to make possible a future where humanoid robots improve how people live and work. In his GTC keynote, NVIDIA CEO Jensen Huang included an example of this type of learning. He showed how Apollo, through its integration with the GR00T foundation models, learned how to autonomously operate a juicer and serve juice.

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Apptronik iterates humanoid robot design

Apptronik spun out of the Human Centered Robotics Lab at the University of Texas at Austin in 2016. The company‘s stated mission is to use innovative technology for the betterment of society. It added that Apollo is the culmination of the design and development of 10 robots designed to work in environments designed for people.

Those robots ranged from industrial robot arms and exoskeletons to bipedal mobility platforms, as well as extensive work on NASA Valkyrie. In August 2023, Apptronik launched Apollo, which it designed for friendly interaction, mass manufacturability, and safety.

The company claimed that its design provides scalability, cost, power efficiency, manufacturability, and supply chain resilience. Apollo uses linear actuators rather than rotary ones, copying how human muscles work.

The robot’s force-control architecture is intended to maintain safe arm movement around people, similar to a collaborative robot in comparison with an industrial robot arm. Apollo’s modular design allows its humanoid upper body to be deployed on legs, a wheeled base, or a pedestal so it can operate in whichever form is best suited to a given task, said Apptronik.

Apollo’s hot swappable batteries, each with a four-hour runtime, eliminate the need for a plug-in charge, the company added. This gives it more operational time than other humanoid robots, it asserted.

“Apollo represents a novel approach to humanoid robot design and is purpose-built to break through the technological and performance ceilings that have prevented past generations of humanoid robots from making a significant impact,” said Apptronik. “This allows for a new level of function, efficiency, and scale, along with a force-control architecture that makes it possible for Apollo to operate side by side with people and perform useful tasks.”

NVIDIA Project GR00T gives Apollo agility

Apollo’s main computing system includes onboard NVIDIA Jetson AGX Orin and Jetson Orin NX modules. They enable the AI-powered robot to efficiently use models such as the new GR00T foundation models to perform a wide variety of tasks, while its humanoid form allows it to learn from human demonstrations, said Apptronik and NVIDIA.

The integration of NVIDIA’s hardware and software with Apollo will help Apptronic accelerate skill development for general-purpose robots, the companies noted. Apptronik plans to rely on NVIDIA’s AI portfolio for humanoid robots, including GR00T, Isaac Lab, and the OSMO compute orchestration service announced at GTC.

“Generative AI is currently used to generate text, images, and video,” stated Jeff Cardenas, co-founder and CEO of Apptronik. “The next frontier is to leverage these AI tools to generate intelligent humanoid robot behavior.”

“In addition to our internal efforts, our collaboration with NVIDIA will combine the superior hardware design of our Apollo humanoid robot with NVIDIA-powered multimodal learning from demonstration – particularly video demonstration,” he explained. “We believe this combination has the potential to change the world and benefit all of humanity.”

Last week, Apptronik announced that Mercedes-Benz was testing Apollo for automotive manufacturing applications.

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SAFELOG’s mobile robots can operate in a range of warehouse and factory settings using Opteran Mind. | Source: SAFELOG

Opteran Technologies this week announced at LogiMAT a partnership with SAFELOG GmbH, a manufacturer of order-picking and transportation robots for warehouses and factories. SAFELOG will integrate its mobile robots with Opteran Mind, a general-purpose autonomy product.

“We are delighted to announce our partnership with SAFELOG, as this is another significant milestone on our path to commercializing Opteran Mind,” stated David Rajan, co-founder and CEO of Opteran Technologies.

“We are seeing a rapid take up of our technology across the U.S., Japan, and Europe, so today’s agreement with SAFELOG underlines why our technology is best in class for localization and mapping for mobile robots,” he added. “It also shows that while ‘natural intelligence’ is unique in the market, our inputs and outputs are standard, making Opteran Mind a simple and attractive solution to integrate with existing mobile robots.”

The companies said the multi-year agreement will enable SAFELOG to address the urgent need for greater productivity from autonomous mobile robots (AMRs) operating in hazardous and dusty environments. Opteran claimed that its technology can enable AMRs to handle dynamic lighting and ever-changing obstacles without GPS.

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SAFELOG aims to reduce failure rates

Markt Schwaben, Germany-based SAFELOG said it is developing a new generation of mobile robots that combine robustness and efficiency. A key objective of its project with Opteran is to reduce robot failure rates because of localization errors with existing 2D and 3D lidar, as well as with visual simultaneous localization and mapping (vSLAM).

Another challenge to productivity is when hundreds of automated guided vehicles (AGVs) operate together in a warehouse setting because each installation requires an infrastructure consisting of magnetic tracks and QR code reflectors. This can increase commissioning time and operating costs.

Opteran said its localization software enables new projects to be activated quickly and efficiently without additional infrastructure. 

“There are a lot of challenges for existing autonomy solutions to overcome in the complex conditions of a warehouse, so we have been amazed by what Opteran Mind can achieve,” said Michael Reicheicher, managing director of SAFELOG, in a release. “Opteran’s technology performs significantly better in our mobile robots, which will be hugely beneficial for our customers. Natural Intelligence, their approach to AI, offers a robust technology that we are confident will differentiate our AMRs in the global market.”

Opteran Mind promises navigation breakthrough

Opteran Mind is based on 10 years of research into insect brains. The company, which has facilities in London and Sheffield in the U.K. and Boston in the U.S., said it reverse-engineered natural brain algorithms. 

“Fundamentally, nature does navigation more efficiently than robots,” said Opteran Technologies. By replicating nature’s approach in a model that the company calls “natural intelligence,” it said it has delivered a “dramatic breakthrough.”

Opteran estimated that its system could cost less than $160 running on a Sony and ARM Core and using Sony IMX219 cameras and RK4566 ARM chips. In comparison, current systems can range in cost from $8,400 for a 2D lidar setup to $27,000 for a 3D lidar setup, it said.

Opteran and SAFELOG demonstrated their collaboration at LogiMAT in Stuttgart, Germany. They showed a SAFELOG mobile robot using Opteran Mind, which they said could increase adaptability and minimize downtime.

The partners said Opteran Mind can be embedded in ground-based robots and aerial drones for a wide variety of applications, from logistics and warehouse distribution to oil and gas inspection, mining, and autonomous vehicles.

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NVIDIA CEO Jenson Huang ended his GTC 2024 keynote backed by life size images of all of the various humanoids in development and powered by the Jetson Orin computer. | Credit: Eugene Demaitre

SAN JOSE, Calif. — The NVIDIA GTC 2024 keynote kicked off like a rock concert yesterday at the SAP Arena. More than 15,000 attendees filled the arena in anticipation of CEO Jensen Huang’s annual presentation of the latest product news from NVIDIA.

To build the excitement, the waiting crowd was mesmerized by an interactive and real-time generative art display running live on the main stage screen, driven by the prompts of artist Refik Anadol Dustio.

New foundation for humanoid robotics

The big news from the robotics side of the house is that NVIDIA launched a new general-purpose foundation model for humanoid robots called Project GR00T. This new model is designed to bring robotics and embodied AI together while enabling the robots to understand natural language and emulate movements by observing human actions.

Project GR00T training model. | Credit: NVIDIA

GR00T stands for “Generalist Robot 00 Technology,” and with the race for humanoid robotics heating up, this new technology is intended to help accelerate development. GR00T is a large multimodal model (LMM) providing robotics developers with a generative AI platform to begin the implementation of large language models (LLMs).

“Building foundation models for general humanoid robots is one of the most exciting problems to solve in AI today,” said Huang. “The enabling technologies are coming together for leading roboticists around the world to take giant leaps towards artificial general robotics.”

GR00T uses the new Jetson Thor

As part of its robotics announcements, NVIDIA unveiled Jetson Thor for humanoid robots, based on the NVIDIA Thor system-on-a-chip (SoC). Significant upgrades to the NVIDIA Isaac robotics platform include generative AI foundation models and tools for simulation and AI workflow infrastructure.

The Thor SoC includes a next-generation GPU based on NVIDIA Blackwell architecture with a transformer engine delivering 800 teraflops of 8-bit floating-point AI performance. With an integrated functional safety processor, a high-performance CPU cluster, and 100GB of Ethernet bandwidth, it can simplify design and integration efforts, claimed the company.

Project GR00T, a general-purpose multimodal foundation model for humanoids, enables robots to learn different skills. | Credit: NVIDIA

NVIDIA showed humanoids in development with its technologies from companies including 1X Technologies, Agility Robotics, Apptronik, Boston Dynamics, Figure AI, Fourier Intelligence, Sanctuary AI, Unitree Robotics, and XPENG Robotics.

“We are at an inflection point in history, with human-centric robots like Digit poised to change labor forever,” said Jonathan Hurst, co-founder and chief robot officer at Agility Robotics. “Modern AI will accelerate development, paving the way for robots like Digit to help people in all aspects of daily life.”

“We’re excited to partner with NVIDIA to invest in the computing, simulation tools, machine learning environments, and other necessary infrastructure to enable the dream of robots being a part of daily life,” he said.

NVIDIA updates Isaac simulation platform

The Isaac tools that GR00T uses are capable of creating new foundation models for any robot embodiment in any environment, according to NVIDIA. Among these tools are Isaac Lab for reinforcement learning, and OSMO, a compute orchestration service.

Embodied AI models require massive amounts of real and synthetic data. The new Isaac Lab is a GPU-accelerated, lightweight, performance-optimized application built on Isaac Sim for running thousands of parallel simulations for robot learning.

NVIDIA software — Omniverse, Metropolis, Isaac and cuOpt — combine to create an ‘AI gym’
where robots, AI agents can work out and be evaluated in complex industrial spaces. | Credit: NVIDIA

To scale robot development workloads across heterogeneous compute, OSMO coordinates the data generation, model training, and software/hardware-in-the-loop workflows across distributed environments.

NVIDIA also announced Isaac Manipulator and Isaac Perceptor — a collection of robotics-pretrained models, libraries and reference hardware.

Isaac Manipulator offers dexterity and modular AI capabilities for robotic arms, with a robust collection of foundation models and GPU-accelerated libraries. It can accelerate path planning by up to 80x, and zero-shot perception increases efficiency and throughput, enabling developers to automate a greater number of new robotic tasks, said NVIDIA.

Among early ecosystem partners are Franka Robotics, PickNik Robotics, READY Robotics, Solomon, Universal Robots, a Teradyne company, and Yaskawa.

Isaac Perceptor provides multi-camera, 3D surround-vision capabilities, which are increasingly being used in autonomous mobile robots (AMRs) adopted in manufacturing and fulfillment operations to improve efficiency and worker safety. NVIDIA listed companies such as ArcBest, BYD, and KION Group as partners.

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‘Simulation first’ is the new mantra for NVIDIA

A simulation-first approach is ushering in the next phase of automation. Real-time AI is now a reality in manufacturing, factory logistics, and robotics. These environments are complex, often involving hundreds or thousands of moving parts. Until now, it was a monumental task to simulate all of these moving parts.

NVIDIA has combined software such as Omniverse, Metropolis, Isaac, and cuOpt to create an “AI gym” where robots and AI agents can work out and be evaluated in complex industrial spaces.

Huang demonstrated a digital twin of a 100,000-sq.-ft, warehouse — built using the NVIDIA Omniverse platform for developing and connecting OpenUSD applications — operating as a simulation environment for dozens of digital workers and multiple AMRs, vision AI agents, and sensors.

Each mobile robot, running the NVIDIA Isaac Perceptor multi-sensor stack, can process visual information from six sensors, all simulated in the digital twin.

Image depicting AMR and a manipulator working together to
enable AI-based automation in a warehouse powered by NVIDIA Isaac. | Credit: NVIDIA

At the same time, the NVIDIA Metropolis platform for vision AI can create a single centralized map of worker activity across the entire warehouse, fusing data from 100 simulated ceiling-mounted camera streams with multi-camera tracking. This centralized occupancy map can help inform optimal AMR routes calculated by the NVIDIA cuOpt engine for solving complex routing problems.

cuOpt, an optimization AI microservice, solves complex routing problems with multiple constraints using GPU-accelerated evolutionary algorithms.

All of this happens in real-time, while Isaac Mission Control coordinates the entire fleet using map data and route graphs from cuOpt to send and execute AMR commands.

NVIDIA DRIVE Thor for robot axis

The company also announced NVIDIA DRIVE Thor, which now supersedes NVIDIA DRIVE Orin as a SoC for autonomous driving applications.

Multiple autonomous vehicles are using NVIDA architectures, including robotaxis and autonomous delivery vehicles from companies including Nuro, Xpeng, Weride, Plus, and BYD.

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The Lexium cobot product line, from left to right: RL3, RL5, RL7, and RL12 (not to scale). | Credit: Schneider Electric

Schneider Electric today at MODEX announced the release of two new collaborative robots: the Lexium RL 3 and RL 12, as well as the Lexium RL 18 model coming later this year. From single-axis machines to high-performance, multi-axis cobots, the Lexium line enables high-speed motion and control of up to 130 axes from one processor. This enables precise positioning to help solve manufacturer production, flexibility, and sustainability challenges, said the company.

“As U.S. manufacturing increases, the demand for smart machines is growing, and customers are requiring robots with digital twin capabilities that validate machine performance to help them quickly increase production consistently, efficiently, and sustainably,” stated Christine Bush, leader of the Robotics Center of Excellence at Schneider Electric.

“We are partnering with our customers to understand their challenges and pain points, then responding with complete, customized automation solutions – from power products and HMIs [human-machine interfaces] to PLCs [programmable logic controllers] and robotics – to simplify the process and meet their needs,” she added.

In addition to robots, Schneider Electric said it offers digitally engineered automation from concept to operation and maintenance. The company‘s EcoStruxure architecture connects smart devices, controls, software, and services to enable collaborative data flow from shop-floor to top-floor machine control.

Schneider Electric also said it provides robots using Modicon motion controllers, which combine PLC, motion, and robotics control on a single hardware platform with the EcoStruxure Machine Expert software.

Lexium digital twins offer layout, programming

The Lexium Cobots feature a positioning accuracy of +/- 0.02 mm (+/- 0.00079 in.), as well as a wide range of payloads from 3 to 18 kg (6.6 to 39.6 lb.), coming soon. The cobots range in price from $27,368 to $41,170.

The Lexium Cobot product line is compatible with EcoStruxure Machine Expert Twin, a software suite that creates digital models of real machines. It allows for virtual test strategies and commissioning, as well as shortened factory acceptance testing (FAT).

Digitizing these processes can reduce time-to-market by up to 50% and commissioning time by up to 60%, according to Schneider Electric. A 20% to 40% savings in investment costs can also be realized due to faster time to market, the company claimed.

Robot assembly, installation, and maintenance are faster with increased computational power, open software, and networking, it said. Software and automation work together using a centralized architecture and open-standard programming platform.

In addition to fast deployment, collaborative robots allow for more ergonomic work, easier integration with existing equipment and processes, and consistent output for higher product quality, said Schneider Electric. It also cited the benefit of reduced workplace strain and injuries.

For U.S. manufacturers to stay globally competitive, they must modernize processes by embracing the digitization of Industry 4.0, which includes advances in AI, machine learning, the Internet of Things (IoT), and digital twins, said Schneider Electric. The latest software can help makers develop new ideas quickly, cut down on working time, and meet shifting customer demand, it noted.

As the business world moves toward Industry 5.0, Lexium’s motion and robot solutions will likely change the way things are done and make personalized automated manufacturing possible.

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Cogniteam provides a unified way to develop, deploy, and manage robot fleets. Source: Cogniteam

Real-Time Innovations, or RTI, today announced that Cogniteam has chosen RTI Connext to provide commercially supported communications to its unified cloud-based platform for robot design, development, and testing.

Developers can use Connext, which is based on the Data Distribution Service (DDS) standard, to monitor incoming data in real time from robots to the cloud, said RTI. It promises to improve productivity, as Cogniteam achieved coding translation from the Robot Operating System (ROS) to ROS 2 in one month, compared with the market norm of three to six months, asserted the companies.

“New and exciting tools are emerging in robotics aimed at facilitating interconnectivity of systems and components at the edge and in the cloud,” said Ari Yakir, vice president of research and discovery at Cogniteam, in a release. “Connext did exactly what we needed it to — from adding functionality between libraries to retrieving critical data from the edge device — speeding up our production timeline and advancing robotic platform development.”

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Cogniteam needed tailored communications

Cogniteam provides a low-code development platform, teleoperation capabilities, and a simulation tool for scaling robot fleets. The company, which has offices in Boston and Petach Tikva, Israel, needed a way to achieve communication functionality from ROS to ROS 2 and a seamless way to talk between autonomous systems on land, in the air, or on the sea.

Connext offers both a native DDS and a commercially-supported ROS Middleware Abstraction Interface (RMW) layer, which Cogniteam said  allowed its platform to communicate via the cloud in production and remote settings, providing all of the functionality of getting data and controlling robots.

The company added that it selected Connext so it could be the first to enable support for a wide range of autonomous robots in a unified way via the cloud. RTI’s trusted distribution partner in Israel, Matrix, oversaw the integration process of Connext with Cogniteam’s edge device agent. It also provided on-site technical enablement and support.

Cogniteam partnered with Advantech in December 2023 to accelerate the development of autonomous mobile robots (AMRs) through remote monitoring and management.

RTI provides integration platform for intelligent systems

“Robotics are enabling efficient autonomy and productivity in nearly every vertical,” stated Bob Leigh, senior director of commercial markets at RTI.

Sunnyvale, Calif.-based Real-Time Innovations said RTI Connext users can build intelligent, distributed systems that combine advanced sensing, fast control, and AI algorithms on its software framework. It demonstrated Connext Drive 3.0 for software-defined vehicles at CES 2024.

“Connext includes an open interface and advanced integration capabilities that slash costs across a system’s life cycle, from initial development and integration through ongoing maintenance and upgrades,” added Leigh. “We’re proud to have a long-standing relationship with Cogniteam and we welcome them to our expansive ecosystem of companies choosing Connext as their commercial DDS solution.”

With 2,000 customer designs, RTI said it can help customers get to production. The company claimed that its software runs more than 250 autonomous vehicle programs, supports dozens of advanced driver-assist systems (ADAS) and software-defined architectures, and controls the largest power plants in North America. It also said its platform integrates over 400 major defense programs, drives a new generation of MedTech systems and robotics, and underlies Canada’s air traffic control and NASA’s launch-control systems.

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MIT researchers have applied AI for traffic mitigation to managing multiple warehouse robots. Source: Adobe Stock

Researchers at the Massachusetts Institute of Technology have applied ideas from the use of artificial intelligence to mitigate traffic congestion to tackle robotic path planning in warehouses. The team has developed a deep-learning model that can decongest robots nearly four times faster than typical strong random search methods, according to MIT. 

A typical automated warehouse could have hundreds of mobile robots running to and from their destinations and trying to avoid crashing into one another. Planning all of these simultaneous movements is a difficult problem. It’s so complex that even the best path-finding algorithms can struggle to keep up, said the university researchers.

The scientists built a deep-learning model that encodes warehouse information, including its robots, planned paths, tasks, and obstacles. The model then uses this information to predict the best areas of the warehouse to decongest and improve overall efficiency. 

“We devised a new neural network architecture that is actually suitable for real-time operations at the scale and complexity of these warehouses,” stated Cathy Wu, the Gilbert W. Winslow Career Development Assistant Professor in Civil and Environmental Engineering (CEE) at MIT. “It can encode hundreds of robots in terms of their trajectories, origins, destinations, and relationships with other robots, and it can do this in an efficient manner that reuses computation across groups of robots.”

Wu is also a member of the Laboratory for Information and Decision Systems (LIDS) and the Institute for Data, Systems, and Society (IDSS).

A divide-and-conquer approach to path planning

The MIT team’s technique for the deep-learning model was to divide the warehouse robots into groups. These smaller groups can be decongested faster with traditional algorithms used to coordinate robots than the entire group as a whole. 

This is different from traditional search-based algorithms, which avoid crashes by keeping one robot on its course and replanning the trajectory for the other. These algorithms have an increasingly difficult time coordinating everything as more robots are added. 

“Because the warehouse is operating online, the robots are replanned about every 100 milliseconds,” said Wu. “That means that every second, a robot is replanned 10 times. So these operations need to be very fast.”

To keep up with these operations, the MIT researchers used machine learning to focus the replanning on the most actionable areas of congestion. Here, the researchers saw the most room for improvement when it came to total travel time of robots. This is why they decided to tackle smaller groups of robots at the same time. 

For example, in a warehouse with 800 robots, the network might cut the warehouse floor into smaller groups that contain 40 robots each. Next, it predicts which of these groups has to most potential to improve the overall solution if a search-based solver were used to coordinate the trajectories of robots in that group. 

Once it finds the most promising robot group using a neural network, the system decongests it with a search-based solver. After this, it moves on to the next most promising group.

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How MIT picked the best robots to start with

The MIT team said its neural network can reason about groups of robots efficiently because it captures complicated relationships that exist between individual robots. For example, it can see that even though one robot may be far away from another initially, their paths could still cross at some point during their trips. 

Another advantage the system has is that it streamlines computation by encoding constraints only once, rather than repeating the process for each subproblem. This means that in a warehouse with 800 robots, decongesting 40 robots requires holding the other 760 as constraints. 

Other approaches require reasoning about all 800 robots once per group in each iteration. Instead, the MIT system only requires reasoning about the 800 robots once across all groups in iteration. 

The team tested this technique in several simulated environments, including some set up like warehouses, some with random obstacles, and even maze-like settings that emulate building interiors. By identifying more effective groups to decongest, the learning-based approach decongests the warehouse up to four times faster than strong, non-learning-based approaches, said MIT.

Even when the researchers factored in the additional computational overhead of running the neural network, its approach still solved the problem 3.5 times faster. 

In the future, Wu said she wants to derive simple, rule-based insights from their neural model, since the decisions of the neural network can be opaque and difficult to interpret. Simpler, rule-based methods could also be easier to implement and maintain in actual robotic warehouse settings, she said.

“This approach is based on a novel architecture where convolution and attention mechanisms interact effectively and efficiently,” commented Andrea Lodi, the Andrew H. and Ann R. Tisch Professor at Cornell Tech, and who was not involved with this research. “Impressively, this leads to being able to take into account the spatiotemporal component of the constructed paths without the need of problem-specific feature engineering.”

“The results are outstanding: Not only is it possible to improve on state-of-the-art large neighborhood search methods in terms of quality of the solution and speed, but the model [also] generalizes to unseen cases wonderfully,” she said.

In addition to streamlining warehouse operations, the MIT researchers said their approach could be used in other complex planning tasks, like computer chip design or pipe routing in large buildings. 

Wu, senior author of a paper on this technique, was joined by lead author Zhongxia Yan, a graduate student in electrical engineering and computer science. The work will be presented at the International Conference on Learning Representations. Their work was supported by Amazon and the MIT Amazon Science Hub.

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