THE ROBOT REPORT_DESIGN WORLD_SEPTEMBER 2021 by WTWH Media LLC

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

INSIDE: • Novanta acquisition a win-win for ATI employees ....................................................................... 58 • Metallic glass gears up for collaborative robots .............. 62

How Atlas runs, flips &

• Designing a durable cobot arm joint .................................. 68 • Quadruped learns to adapt to changing terrain in real time ................................................................ 72

• Tips for choosing your robot’s motors ............................... 88

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The Robot Report

Novanta acquisition

a win-win for ATI employees ATI offers an Employee Stock Ownership Plan, a federally-qualified ERISA benefit plan that makes employees owners in the company.

| AdobeStock

Steve Crowe | Editorial Director, The Robot Report

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Less than one week a er announcing it’s acquiring Schneider Electric Motion USA for $115 million in cash, Novanta said it’s acquiring ATI Industrial Automation for $172 million in cash. The price could increase if ATI hits certain financial goals in 2021. The acquisition is expected to close in Q3 2021. Founded in 1989, ATI is a leading developer of end-of-arm tooling, including robotic changing systems, force/torque sensors, and collision sensors for industrial, collaborative, and medical robotic systems. Raleigh, North Carolinabased ATI has 350-plus employees. In January 2021, for example, ATI released a slew of end-of-arm tooling kits for FANUC’s CRX Series cobot arms. Novanta said acquiring ATI expands its presence in robotics, adds end-of-arm tooling to its product lineup, increases its customer base, and adds 60 patents to its already strong IP portfolio. According to Novanta, ATI is expected to generate more than $70 million in sales in 2021. That means the sales price to Novanta is about 2.5x. “ATI is a fantastic business with proprietary intellectual property in attractive and growing markets. The business adds intelligent technology solutions and expands Novanta’s position in mission critical robotic applications, such as electric vehicle production, medical robotics, and collaborative robotics,” said Matthijs Glastra, CEO and chairman of Novanta. “In addition, the transaction creates a

ATI Industrial Automation is a leading developer of end-of-arm tooling products, including these tool changers. | ATI Industrial Automation

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The Robot Report nearly $250 million Precision Motion Segment with significant engineering competency to further accelerate our growth.” “We are excited to join Novanta at this stage of our development. We expect the combination of competencies and cultures to create better opportunities for our customers and employees,” said

a ERISA retirement account. After the acquisition closes, the employees will gain performance stock units in Novanta —so employee ownership continues. ESOP’s role in ATI’s sale Little said ATI wasn’t looking to be acquired. However, when an organization with an ESOP receives an unsolicited

“We are excited to join Novanta at this stage of our development. We expect the combination of competencies and cultures to create better opportunities for our customers and employees.” — Bob Little, CEO and co-founder, ATI Bob Little, CEO and co-founder, ATI. “We feel confident our shared values, our passion for innovation, and our deep application knowledge will create stronger partnerships with our customers to help us accelerate our strategic goals.” Acquisition a win-win for ATI employees It turns out the deal is a win-win for most ATI employees, not just the cofounders and higher-ups. In 2012, ATI established an Employee Stock Ownership Plan (ESOP). An ESOP is a federally-qualified ERISA benefit plan that makes employees owners in the company. More than 300 of ATI’s employees are based in North Carolina. All U.S.-based ATI employees that put in a minimum of 1,000 hours of work in the calendar year (six months for a fulltime employee) earn shares in the ATI ESOP. The more time you have worked at ATI, the more shares you own. Non-U.S. employees are not qualified for the ESOP since the program is a U.S. federal plan. “An ESOP is a fantastic tool for employees to have ownership,” said Little. “I only wish the program benefited everyone outside of the U.S.” After the acquisition is complete, the ESOP shares will be traded to Novanta for cash, which is a publicly-traded company. ESOP owners will have their shares cashed out and transferred into

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offer to be acquired, and that offer is fair, the company has to review the offer. “You can’t just throw the offer in the trash,” he said. “There needs to be a reason to throw it away.” ATI received a valid, unsolicited offer in 2019. That offer, Little said, wasn’t from Novanta. But the offer caused ATI to open its eyes and understand that companies wanted to acquire it. “We must have talked to 20-plus companies that were interested in potentially buying us,” Little said. “Being an ESOP, we wanted to make sure that people get the best value and we talk to the right companies, if there’s an acquisition. Most of the offers were unsolicited – they heard through the grapevine that ATI could be acquired.” “When Novanta came to ATI to examine our capability, I was very excited,” said Little. “I was extremely impressed with Novanta’s technology, and since ATI is known for their robotic technology, I saw a clear fit.”

growing or shrinking? We have a forecast of our growth, and it’s pretty substantial over the next several years. I’m focused not on what ATI can do in the next five years, but what the entire industry can do in the next five years.” One thing ATI certainly has working in its favor is that it’s not tied to one particular robot or application. “We go where robots go. That is why we have products all over the world and in automotive plants, aerospace facilities, 3D machines, and on Mars. They all have robots.” “If the robot market isn’t growing, it’s tough for us to grow. But when it is growing, it’s easy for us to grow,” Little said. “I’ve been studying this market for a long time. We reached the bottom of the barrel in 2020, and the robot market has been growing astronomically over the last year. I expect this to continue, not without some dips, but overall the robot market will climb at a really nice rate. “We know the reason why. Automation has become so much more important in the horrifying labor pool that we’re in. We can’t get enough workers, and it’s only going to get worse because of the enormous pressure to make things locally. When you make it local, you need to use the local workforce. And if you can’t hire the local workforce, you need to automate. Expect very strong robot sales in the next several years.” Little said ATI will maintain its name, branding, facilities and strategy going forward. “We are flush with two great companies,” he said. “Nothing changes our goals here and what we want to accomplish. We’re still pushing our strategy. That’s why Novanta bought us. You’ll see new product development that Novanta can help with. You’ll see improvements, but our core values customers love us for will not change.” RR

What the future holds for ATI Novanta’s cost of acquiring ATI could increase if ATI hits certain financial benchmarks. “The acquisition price was not too high or too low. It was on the mark,” Little said. “It’s amazing the ups and downs the robotics market has gone through in the last few years. Is the robot market

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Metallic glass gears up for collaborative robots Bulk metallic glass could reduce the prices of cobots and lead to advanced 3D printed metals. Mike DiCicco | Spinoff

Where are the robot assistants we were promised? For all the space that robots have occupied in the popular imagination for the last hundred years — and although the number of real-world robots has been growing for decades — most people’s interactions with them remain limited to a hands ee vacuum or child’s smart toy. There are two main reasons for this, according to Glenn Garrett, chief technology officer of NASA spinoff company Amorphology – cost and safety. Most automated machinery is still only affordable to large manufacturers that can make major investments and expect long-term savings. And while robots take up more and more of the factory floor, they are generally segregated om their human colleagues due to safety concerns — largely oblivious to their surroundings, they are strong and dangerously clumsy. Collaborative robots In the mid-1990s, two Northwestern University professors patented an alternative concept under a new term — cobots (or collaborative robots). Compared to

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NASA’s Curiosity rover spends about three hours heating up lubricants for its gears each time it sets out across Mars. To help future rovers save time and energy, NASA invested in bulk metallic glass for gears that require no lubrication. | NASA

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Most metallic glass alloys form a hard, smooth surface. This gives metallic glass gears a long lifetime without the need for liquid lubricants, making them appealing for NASA robotics that operate in cold environments, where lubricants need to be warmed before operations. | Amorphology

traditional industrial robots, collaborative robots, which are designed to cooperate with humans, would be smaller, smarter, more responsive, and more aware, with tighter self-control and better mannered all around. Too costly In the years since, leaps in artificial intelligence and sensors have made these “friendlier” robots a reality. Unfortunately, cost still limits their widespread adoption. According to Garrett, the largest cost drivers for robots are not always the advanced software and sensors. Instead, it often comes down to some of the most rudimentary machine components — gears, which Garrett estimates account for at least half the cost of robotic arms. Pasadena, California-based

Amorphology hopes to drop the price of cobots with advances originally made for robots that were never intended for human interaction – NASA’s planetary rovers. Rovers adapt to Martian climate Gears on NASA’s rovers, like most gears on Earth, are made of steel, which is both strong and wear resistant. But steel gears need liquid lubrication, and oils do not work well in frigid environments like the lunar or Martian surface. According to Doug Hofmann, principal scientist of the Materials Development and Manufacturing Technology group at NASA’s Jet Propulsion Laboratory (JPL), it is for this reason that NASA’s Curiosity rover spends about three hours warming up lubricants every time it prepares to

Flexsplines are thin, flexible, cupshaped gears integral to strain wave gears common in robotics. They’re typically cut, ground, and drilled from steel billets in a process that is long and costly. The flexspline on the right was injection molded from metallic glass in a cheaper, simpler process. | Amorphology

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start rolling. This process uses up about a quarter of the discretionary energy that could otherwise be used for science. With an eye toward solving this and other materials-related issues, in 2010, JPL hired Hofmann, then a research scientist at California Institute of Technology (Caltech) with a background in materials science and engineering. NASA funded a new metallurgy facility at the Jet Propulsion Laboratory to explore alternatives for gears and develop new metal alloys. Bulk metallic glass From his days at Caltech, which manages JPL, Hofmann was familiar with an emerging class of specially engineered materials called bulk metallic glass, also known as amorphous metals. These are metal alloys that can be rapidly cooled from liquid to solid before their atoms form the crystalline lattice structure that is common to all other metals. Instead, the atoms are randomly arranged like those of glass, giving the materials properties of both glass and metal. Depending on their constituent elements — often including zirconium, titanium, and copper — metal alloys can be very strong, and because they are not crystalline, they are elastic. Most compositions also form a hard, smooth ceramic oxide surface, and these properties together afford gears made of some amorphous metals a long lifetime with no lubrication. According to Hofmann, it is the unique properties metallic glass alloys that makes them attractive to NASA. Metallic glass gears do not require liquid lubricants. Metallic glass gears can also operate in temperatures below minus 290 degrees Fahrenheit without requiring a heating source. Affordable robot parts Amorphous metals have another property that makes them attractive for gears on Earth. The alloys used to make metallic glass have low melting temperatures. Most high-strength metals have high melting points. They cannot be cast with molds because, in molten form, they would simply melt the mold. And steel

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The Robot Report needs to be rolled or forged to strengthen it, which also precludes molding. So, gears typically start as steel billets that are ‘machined’ — cut, ground, milled, and drilled — into their final shape. Tiny gears, like those for small cobots, are especially challenging — and costly. The low melting point of alloys used to make metallic glass, together with their native strength, and the fact that their volume hardly changes upon solidifying, makes bulk metallic glasses easy to use in injection molding. Injection molding can dramatically reduce the cost of making parts like gears. Flexsplines The most difficult, expensive gear component to machine from a steel block is one of the most common in robotic arms — the flexspline. Flexsplines are extremely thin-walled, flexible cups with a toothed rim. Flexplines are the centerpiece of what is known as a strain wave gear assembly. Strain wave gears provide better precision, higher torque, and lower backlash than other gear sets. This eliminates positioning errors which would be compounded in a robotic limb with multiple joints. According to Hoffman, it is injection molding of strain wave gears with amorphous metals that promises the greatest savings. Injection molding costs about half as much as machining strain wave gears from steel. Amorphology’s business plan Molding small, high-performance planetary and strain wave gears became the central business plan for Amorphology, which Hofmann cofounded in 2014. Through Caltech, the company licensed several patents for technology he had developed for NASA. Meanwhile, Hofmann and colleagues continued pursuing new materials for spacecraft at both the metallurgy lab and JPL’s Additive Manufacturing Center. A number of patents and technologies led Hofmann to found a second spinoff company focused on using amorphous metals in coatings, 3D printing, and other non-gear-related applications. Both were backed by the same venture capital group, and in 2020 they

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A strain wave gear converts the fast, low-torque rotation of an engine into slow, precise, forceful motion. As the oblong wave generator at the center spins, it deforms the flexspline around it, shown in red, which engages with the teeth of a fixed outer spline. The interaction causes the flexspline to rotate in the opposite direction of the wave generator, moving only two teeth for each turn of the motor. | Jahobr, CCO 1.0

merged under the Amorphology name, combining about 30 patents and patent applications for the technology from JPL. A market beyond Mars Also in 2020, the merged company finished its move into a new, 13,000-square-foot manufacturing facility where about 15 people now work, mostly making and testing prototype pieces for small gear assemblies for several customers. Amorphology’s first and largest customer is one of the world’s foremost manufacturers of strain wave gears. In addition, at least one other customer has hired the company to coat consumer electronics parts with metallic glass, making them more durable, indicating another market with immediate potential. Hofmann noted that gears that can operate without lubrication are also of interest to businesses like food manufacturing, where lubricants can become contaminants. Meanwhile, many of the company’s other patents for JPL technology — all licensed from Caltech – are probably still years away from commercialization,

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although they are in fields that are gaining heavy interest. Among these are new alloys and advanced metal 3D printing technologies, from thermal spray additive manufacturing to ultrasonic welding. NASA technology transfer NASA has a long history of transferring technology to the private sector, and Amorphology is not the first company to commercialize innovations in bulk metallic glass from JPL and Caltech. But Garrett notes that creating a startup based on new materials is notoriously difficult. If lubrication-free gears or lowcost flexsplines find a long-term market. “That would be a huge step towards sustained commercial success for bulk metallic glass,” he said. RR

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Designing

a durable cobot arm joint The design had to meet industry-leading cobot requirements, including high levels of functional safety, high load-bearing capacity with increased arm speed. David Dumoulin | TE Connectivity

Collaborative robots (cobots) represent one of the fastest growing segments in industrial automation, increasing by around 11% year-over-year. While cobots enhance efficiency in the workplace, designing robot components, especially robot arms, is not an easy task. From the need to operate in harsh environments and small spaces to oftentimes unique customized solutions, robotic arms present an engineering challenge. A major robotics company came to an engineering team at TE Connectivity with a big request — to help optimize the design for its next generation of cobots. The design had to meet industry-leading cobot requirements including high levels of functional safety, high load-bearing capacity with increased arm speed, and a lightweight design while still being compact and safe and capable of complex functionality. In addition to these requirements, this specific application needed to ensure additional temperature stability. The joint was located near a motor, subjecting its components to frequent changes in temperature. Therefore, the solution needed to minimize thermal sensitivity to maintain a high level of accuracy.

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To meet the customer’s requirements of temperature stability, increased accuracy and complex functionality, TE Connectivity designed an arm joint with the use of its durable torque sensor. Designing a durable arm joint Robotic arm joints are particularly difficult to design. Aside from temperature stability, the joint is often subject to extreme axial loading, tilting movements and force. A major challenge is ensuring sensors maintain accurate measurements without becoming subject to torque. Additionally, the arm joint often operates in a compact space, which means components must be durable enough to withstand high repetition and torque while working. THE ROBOT REPORT

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Typically, the arm joint consists of a torque sensor, a motor drive or position sensor, a gear unit or gear drive, a power converter for the electric motor and power supplies. The number of components alone increases the complexity. However, this particular project took the challenge one step further by requiring all the cables for these components to be fed through one hole 8 - 10 mm in diameter. A microfused torque sensor To meet all the challenges and opportunities of this cobot, TE used a combination of torque sensors, additional connectors and cable assemblies. The robot’s arm design met the OEM’s need for high load-bearing www.therobotreport.com

capacity by offering overload capabilities made possible with microfused technology. The torque sensor solution measures the deformation of a diaphragm under external pressure using highly sensitive silicon strain gauges in a bridge configuration. Using microfused technology, silicon is bonded onto stainless steel using glass. This creates a reliable and stable bond, well suited for the application’s thermoregulatory needs. The bond also transfers strain from the steel into the silicon, ensuring more accurate torque measurements over long-term use. The microfused technology produced repeated survivability rates at 200% and structural failure rates at 500% of load. September 2021

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The Robot Report Prioritizing safety Another important feature of the sensor solution was dual redundancy. TE’s torque sensors use electrically segregated channels in their gauging. Two data channels are fed through a single chip, which also has segregated channels, thus preserving the integrity of the independent data outputs. This enables two separate measurements om different locations on a single structure, increasing accuracy, confidence and safety. Dual redundancy also allows for crosschecking. As the cobot operates, the machine compares the independent measurements om the data channels and stops operating if the two measurements are not within a small window of variability, further improving safety and reliability. This specific torque sensor solution was also engineered to reduce cross-load errors. By controlling the steel geometry and its specific location as well as the dimensions of the sensing region, TE was able to further enhance dependability and safety.

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Connectors and cables To ensure reliability for this application, low deflection (or high stiffness) is required in the cables as the torque is measured by the sensor. TE used connectors and cable assemblies throughout the cobot arm to reinforce functional safety to meet the OEM’s needs. To streamline and strengthen the solution, TE assembled all the components together on each sub-functional unit of the cobot. By working with the same manufacturer for components, TE engineered the internal connections and communications systems to work together om joint to joint, adding an additional level of reliability to the project. In addition, each TE component is shielded to withstand changes in vibration, shock, temperature and more. TE components were also used as a base connector in the endof-arm tool interface, where the DC power, ethernet, sensor element and brake unit are all connected. Designing the next generation of cobots is not a small task. However, with a focus on reliability, safety and seamless integration, TE Connectivity developed a unique torque sensor solution to meet this OEM’s demands — yet another example in how cross-functional expertise can help create the human/machine hybrid workforce of tomorrow. RR

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•• •• •• •• •• •• •• •• •• •• The Robot Report

•• ••

Researchers enabled this A1 quadruped from Unitree Robotics to traverse sand, mud, hiking trails, tall grass and dirt piles without falling. | Source: Facebook AI

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•• ••

•• •• •

Quadruped learns to adapt to changing terrain in real time

Rapid Motor Adaptation uses end-to-end learning all the way, even directly outputting joint positions without relying on predefined leg motions or other control primitives. Jitendra Malik | Director of Research | Facebook AI

Humans can walk with relative ease over rocks, through mud, up and down hills, on thick carpets, and across bouncy trampolines. We can do so with tired muscles or twisted ankles and while carrying objects of all shapes, sizes, and weights. To accomplish this, we constantly make near-instantaneous adjustments to the changing conditions in our bodies and beneath our feet. To be similarly successful in the real world, walking robots also must adapt to whatever surfaces they encounter, whatever objects they carry, and whatever condition they are in — even if they’ve never been exposed to those conditions before. And to avoid falling and potentially suffering damage, these adjustments must happen in actions of a second. Researchers om Facebook AI, UC Berkeley, and Carnegie Mellon University’s School of Computer Science recently introduced Rapid Motor Adaptation (RMA), a breakthrough that enables legged robots to adapt intelligently in real time to challenging, unfamiliar THE ROBOT REPORT

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new terrain and circumstances. RMA uses a novel combination of two policies, both learned entirely in simulation — a base policy trained through reinforcement learning (RL) and an adaptation module trained using supervised learning. Importantly, with RMA the robot demonstrates an aptitude fundamental to all intelligent agents — the ability to adapt to factors in its environment, such as the weight of a backpack suddenly thrust on it or the amount of iction on a new surface, without depending on any visual input at all. Until now, legged robots have either been fully hand-coded for the environments they will inhabit or taught to navigate their environments through a combination of hand-coding and learning techniques. RMA is a learning-based system to enable a legged robot to adapt to its environment om scratch by exploring and interacting with the world.

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•• •• •

The Robot Report

The only way to adjust to all the variations in the real world is to teach robots to adapt. The researchers said tests demonstrate that an RMA-enabled robot outperforms alternative systems when walking over different surfaces, slopes, and obstacles, and when given different payloads to carry. This requires going beyond even sophisticated hand-coding, because it is difficult or impossible to preprogram a robot to adjust to the full range of real-world conditions, whether it’s a different type of rug, a deeper mud puddle, or a bouncier trampoline. Moreover, to work reliably, robots must be able to adjust not only to carrying different loads but also to expected wear and tear, like a dent on the bottom of its foot, a slightly worn-down part, or the countless other unpredictable changes that happen in the real world. Because its ability is based entirely on what it encounters, an RMA-enabled robot can adjust to situations programmers never even considered. Not just what robots can do but how they do it Improvements in hand-coding can boost a robot’s performance within a controlled environment, but the only way to truly adjust to the infinite variations found

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| Source: Facebook AI

in the real world is to teach robots to actually adapt, similar to how people learn. Giving robots this ability to adapt to changing real-world conditions requires teaching them through millions of repetitions, and the best way to do this is not in the real world, where they could get damaged or worn down while learning, but in simulation. RMA uses end-to-end learning all the way, even directly outputting joint positions without relying on predefined leg motions or other control primitives. However, a number of challenges emerge when these skills are first learned in simulation and then deployed in the real world. The physical robot and its model in the simulator are often different in small but important ways. There might be a slight latency between a control signal being sent and the actuator moving, for example, or a scuff on a foot that makes it less slippery than before, or the angle of a joint might be off by a hundredth of a degree. The physical world also presents intricacies that a simulator, which is modeled on rigid bodies moving in free space, cannot accurately capture.

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Surfaces like a mattress or a puddle can deform on contact. An environment that’s fairly standardized in simulation becomes much more varied and complex in the real world, moreso when one factors the multitude of terrains that can exist in both indoor and outdoor spaces. And of course, factors in the real world are never static, so one real-world environment that a legged robot is able to master can be completely different from another. Train in simulation, deploy in real world RMA overcomes these challenges by using two distinct subsystems: a base policy and an adaptation module. The base policy is learned in simulation with RL, using carefully curated information about different environments (like the amount of friction and the weight and shape of the payload). We set different variables — simulating more slippery or less slippery ground or the grade of an incline — so it learns the right controls for different conditions, and we encode info about those variables as “extrinsics.” We can’t simply deploy the robot with only this base policy, because we THE ROBOT REPORT

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2 Conceptual rendering of the multi-jointed robotic arm of a surgical system.

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The Robot Report

Researchers evaluated RMA in out-ofdistribution setups in the real world, comparing RMA to A1’s controller. | Source: Facebook AI

Improvements in handcoding can boost a robot’s performance within a controlled environment, but the only way to truly adjust to the infinite variations found in the real world is to teach robots to actually adapt, similar to how people learn.

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don’t know the actual extrinsics it will encounter out in the real world. So we rely on information that the robot teaches itself about its surroundings — information based on its most recent body movement. We know that the discrepancies between a joint’s actual movement and the expected movement from a command is dependent on these extrinsics. For example, sudden leg obstructions stop the robot’s legs but also reveal information about the ground height around it. Similarly, on a soft surface the leg will extend farther as the foot sinks in, whereas on a hard surface it’ll stop sooner. Since we know the actual extrinsics the robot encounters in simulation, we can use supervised learning to train the adaptation module to predict them from the recent history of the robot’s state. Adapting nearly instantaneously With this combination of a base policy and an adaptation module, the robot can adapt to new conditions in fractions of a second. Robots trained with prior RL-based approaches require several minutes, and sometimes human intervention, to adjust to new conditions, rendering them impractical in the real world. When the RMA-enabled robot is deployed, the base policy and adaptation module work hand in hand www.therobotreport.com

and asynchronously — the base policy running at a faster speed, the adaptation module running much slower — to enable the robot to perform robust and adaptive locomotion without any fine-tuning. Running both policies asynchronously and at substantially different frequencies also helps deploy RMA with a small onboard computer, as is the case with our robot. The small base policy can keep the robot walking at a high frequency, while the bigger adaptation module can send the extrinsics vector at a low frequency when it’s ready. Running both policies asynchronously also adds robustness to somewhat unpredictable hardware speeds and timing. Our experiments have shown that the RMA-enabled robot successfully walks across several challenging environments, outperforming a non-RMA deployment and equaling or bettering the handcoded controllers used in a Unitree quadruped. We executed all our realworld deployments with the same policy without any simulation calibration or real-world fine-tuning. The robot was able to walk on sand, in mud, on hiking trails, in tall grass, and over a dirt pile without a single failure in all our trials. The robot successfully walked down steps along a hiking trail in 70% of the trials. It successfully navigated a cement pile and a pile of pebbles in 80% of the trials, despite never seeing the unstable or sinking ground, obstructive vegetation, or steps during training. It also maintained its height with a high success rate when moving with a 12 kg payload, which amounted to 100% of its body weight. THE ROBOT REPORT

9/3/21 1:58 PM

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The Robot Report Building many forms of more adaptable AI RMA is an exciting advancement for robotics that could enable real-world deployment of new, highly effective, and adaptable walking robots. This work also shows how advancements in AI can transform the field of robotics, enhancing the capabilities of robots while also making those improvements more scalable to new conditions and applications. Methods that rely purely on learning potentially have the capability to work with much cheaper, inaccurate hardware, which would substantially bring down the cost of robots in the future. Increased efficiencies and reduced costs may mean that RMA-enabled robots could one day serve in myriad capacities, such as assistants in search and rescue operations, particularly in areas that are too dangerous or impractical for humans.

More broadly, we hope our work with RMA will help researchers build AI that can adapt in real time to unforeseen, rapidly changing, and highly complex conditions. Beyond robotics, RMA points the way to building AI systems that can adapt to many difficult challenges in real time by leveraging data on the fly to understand the context in which a particular algorithm operates. This is a broad, longterm challenge that will require progress in many subfields beyond RL. But we are excited to see how the AI research community builds on our work with RMA — both in robotics and beyond. RR

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THE ROBOT REPORT

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From Customer Concept to Complete OEM Sensor Solution

HBK is your partner to design single and multi-component sensors for use in robotic surgical and industrial equipment measuring system forces. Whether it’s a multi-axis measurement on a joint, force feedback on an actuator, or grip control on a manipulator, HBK will design and manufacture highly customized solutions without requiring you to make any significant modifications to your existing parts.

CHNOLOG Y TE

Learn more on: www.hbm.com/oemsensors

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The Robot Report

How Atlas

runs, ﬂips & vaults How perception and adaptability enable Atlas to perform varied, high-energy behaviors like parkour.

Pat Marion | Boston Dynamics

What does it take for a robot to run, flip, vault, and leap like an athlete? Creating these high-energy demonstrations is a fun challenge, but our technical goals go beyond just creating a flashy performance. On the Atlas project, we use parkour as an experimental theme to study problems related to rapid behavior creation, dynamic locomotion, and connections between perception and control that allow the robot to adapt – quite literally – on the fly. Perception for parkour Robot perception algorithms are used to convert data om sensors like cameras and lidar into something useful for decision making and planning physical actions. While Atlas uses IMUs, joint positions, and force sensors to control its body motion and feel the ground for balance, it requires perception to identi and navigate obstacles.

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THE ROBOT REPORT

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The Robot Report

Figure 1: A rendering of Atlas with perception outputs

In order to execute an extended parkour course, we give the robot a high-level map that includes where we want it to go and what stunts it should do along the way.

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Atlas uses a time-of-flight depth camera to generate point clouds of the environment at 15 frames per second. The point cloud is a large collection of range measurements. Atlas’ perception software extracts surfaces from this point cloud using an algorithm called multi-plane segmentation. The output of this algorithm is fed into a mapping system that builds models of the different objects that Atlas sees with its camera. Figure 1 shows what Atlas sees and how that perception is used to plan actions. In the top left is the infrared image captured by the depth camera. The white points in the main image form the point cloud. Orange outlines mark the detected rectangular faces of parkour obstacles, which are tracked over time from the sensor observations. These detected faces are then used for planning specific behaviors. For example, the green footsteps represent a future plan of where to jump and jog next. In order to execute an extended parkour course, we give the robot a high-level map that includes where we want it to go and what stunts it should do along the way. This map is not an exact geometric match for the real course; it is an approximate description containing obstacle templates and annotated actions. Atlas uses this sparse

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information to navigate the course, but uses live perception data to fill in the details. For example, Atlas knows to look for a box to jump on, and if the box is moved 0.5 meters to the side then Atlas will find it there and jump there. If the box is moved too far away then the system won’t find it and will come to a stop. We also use 3D visualization tools that show what the robot is seeing and planning as it navigates the parkour obstacle course. Actively tracked objects are drawn in green and fade from green to purple as they go out of view of the robot’s perception sensors. The tracking system continuously estimates the poses of objects in the world and the navigation system plans the green footsteps relative to those objects using information from the map. Behavior libraries Each of the moves you see Atlas perform during a parkour routine is derived from a template created ahead of time using trajectory optimization. Creating a library of these templates allows us to keep adding new capabilities to the robot by adding new trajectories to the library. Given planned targets from perception, the robot chooses the behaviors from the library that match the given targets as closely as possible.

THE ROBOT REPORT

9/3/21 2:06 PM

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The Robot Report

Atlas vaults over a balance beam at Boston Dynamics’ Waltham headquarters.

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| Source: Boston Dynamics

Designing behaviors offline via trajectory optimization allows our engineers to explore the limits of the robot’s capabilities interactively ahead of time and reduce the amount of computation we have to do on the robot. For example, the details of how exactly the robot coordinates its limbs to launch and tuck for a backflip can have a major impact on success due to physical constraints like actuation limits. Leveraging offline optimization allows us to capture important constraints like this at design time and adapt them online using a single, general purpose controller. Model-predictive control Having identified the boxes, ramps, or barriers in front of the robot and planned a sequence of maneuvers to get over them, the remaining challenge is filling in all of the details needed for the robot to reliably carry out the plan. Atlas’ controller is what’s known as a model-predictive controller (MPC) because it uses a model of the robot’s dynamics to predict how its motion will evolve into the future. The controller www.therobotreport.com

works by solving an optimization that computes the best thing to do right now to produce the best possible motion over time. As we described above, each template in our behavior library gives the controller information about what a good solution looks like. The controller adjusts details like force, posture, and behavior timing to cope with differences in the environment geometry, foot slips, or other real-time factors. Having a controller that is able to deviate significantly from template motions simplifies the behavior creation process, since it means that we don’t have to have behavior templates that match every possible scenario the robot will encounter. For example, jumping off of a 52cm platform isn’t that different from a 40cm one, and we can trust MPC to figure out the details. The predictive property of MPC also allows Atlas to see across behavior boundaries. For example, knowing that a jump is followed by a backflip, the controller can automatically create smooth transitions from one move to another. This again simplifies the THE ROBOT REPORT

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The Robot Report The controller adjusts details like force, posture, and behavior timing to cope with differences in the environment geometry, foot slips, or other realtime factors. Having a controller that is able to deviate significantly from template motions simplifies the behavior creation process, since it means that we don’t have to have behavior templates that match every possible scenario the robot will encounter.

behavior creation problem since we need not account for all possible sequences of behaviors ahead of time. There are of course limits to the innovation we can expect from MPC. For example, attempting to transition to a backflip from a fast forward jogging motion wouldn’t work. In general, we have to strike a balance between controller complexity and behavior library size. Building a foundation for the future Our work on parkour has given us a strong understanding of how to create and control a wide range of dynamic behavior on Atlas (also including dance). But more importantly, it created the opportunity to design an extensible software system that will grow with our team as Atlas gains new abilities to perceive and change its environment. We’re excited to continue building on this foundation as we expand the scope of what Atlas can do. RR About the Author Pat Marion is a senior robotics engineer at Boston Dynamics where he leads perception software development for Atlas. Pat first started working with Atlas in 2013 as a member of the MIT DARPA Robotics Challenge Team. Pat has a Masters in Computer Science from MIT and has previously worked on self driving cars, high performance computing, and scientific visualization.

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The Robot Report

Tips for

choosing your robot’s motors

This guide will simplify your motor selection process.

The Robot Report Staff

For hardware startups, picking motors for your robot isn’t a walk in the park. There are many parameters to consider before picking an actuator or motor, and there is no one-stop choice. Pretty much everything depends on the type of robot you’re going to build. Even a er finalizing all the specifications, you still have to keep some non-tech factors in mind like price, delivery time, and supplier’s credibility. Estimating all these things may seem a bit overwhelming—and it is. The guide here sets out to simpli the motor selection process.

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| AdobeStock

THE ROBOT REPORT

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| AdobeStock

The Robot Report

For hardware startups, picking motors for your robot isn’t a walk in the park. There are many parameters to consider before picking an actuator or motor, and there is no one-stop choice.

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Before choosing a motor Before you set your eyes on a particular motor, you need to understand what exactly your robotic application requires. To do so, go through this checklist below: • What is the size of your application? • How will the drive fit? • What kind of tasks will your robot perform? • Do you need standard voltage or industrial voltage? • How much power will the motor consume? • Will your application be plugged into the wall outlet? • Do you want the motor to operate at a specific speed? • What torque will your application require? • Do you need a high-precision motor? • What about noise? Do you want the robot to operate as quietly as possible? • Is there any specific thermal environment? • What will the duty and life cycle of your application be? www.therobotreport.com

With the checklist in hand, it’s easier to put down some ideas of what you’re looking for in a motor. It isn’t all-encompassing, since every robotic application is different, but it will help you understand your basic motor requirements. Now, it’s time to learn what motor options you have. Types of motors in robotic applications There are three main drive types to breathe life into your robot: hydraulic, pneumatic, and electric. Here is a closer look at each type. Hydraulic motors If you need a robot with great weight-lifting ability, hydraulic motors are your best pick. Hydraulic motors use fluid to drive the actuator. A special pump helps the fluid create pressure in the pressure line connected to the hydraulic motor, and the drive then converts fluid pressure into a mechanical one. THE ROBOT REPORT

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The Robot Report

These drives are highly efficient and ensure smooth motion management. These are the main reasons why hydraulic motors are used for industrial robots. Speaking of flaws, they are costly to purchase and maintain. Hydraulic motors also constantly consume energy - not to mention risks of fluid leaks. Pneumatic motors Aspiring to build a pick-and-place application? Perhaps this engine is your perfect match. Pneumatic motors function through compressed air energy. The air compressed by

It’s really hard to make a decision. The most important thing is to get a clear understanding of what your robot needs. You’re picking the very heart of your application, so you’d better focus on the list of requirements for your prototype.

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www.therobotreport.com

the compressor enters the pneumatic lines and then goes to the pneumatic motor. These engines are simple to use and less sensitive to ambient temperature changes. They are also cheaper than a hydraulic motor. Unfortunately, they are also less efficient. Another con of pneumatic motors pertains to possible heating and cooling of the gas in the compressors, which can lead to several rather unpleasant issues. Electric motors When it comes to robotics, electric motors are the most sought-after drives. Their mode of action is clear as day: they convert electrical energy into mechanical. These engines are usually small and lightweight yet powerful enough to activate any robot. An electric drive is also the most environmentoriented solution. Electric motors are the most popular pick among because their prices are affordable and the selection range is extensive. THE ROBOT REPORT

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The Robot Report To avoid unnecessary confusion, we’ll discuss only the most well-known subtypes of electric motors: • AC motors (synchronous and asynchronous) • DC motors (brushed and brushless) • Steppers • Servos

fields—the coil is energized, and the opposite poles of the rotor and stator get attracted to each other. Brushless DC engines are more expensive and harder to grasp, but the price is worth it. They don’t wear off as quickly as brushed motors, are less noisy, and produce great output.

Let’s get a closer look at each of these engines.

Steppers The special thing about steppers is that they rotate differently, in steps, with each step being part of a complete turn. Robot technicians love these motors for their precise position control, longer lifetime, reliability, and greater lowspeed torque. They are also rather cheap and can be used for a range of robotic applications. As for the disadvantages, you may find a stepper a noisy and inefficient solution—especially in comparison with servo motors.

AC Motors AC motors run on an alternating current. You can find these engines mostly in industrial applications since they require being plugged in, and their sizes can be impressive. Most of them aren’t a convenient option for mobile robotics, although there are exceptions. AC motors can be synchronous and asynchronous. Synchronous AC devices have a rotor that rotates synchronously with an oscillating field or current. These motors are highly efficient, simple to regulate, and are used for applications where precise sustained speed is needed. In an asynchronous AC engine, a rotating magnetic field is formed by an alternating current of the stator. They typically weigh less than their synchronous counterparts and are much more compact. However, they also have shortcomings. Asynchronous motors can’t keep the stable rotational speed and overheat under a heavy load. DC Motors DC motors are perfect for mobile robots and collaborative robots because they run on a direct current. Such an engine may need a gearhead to increase torque in industrial use. There are two main groups of DC engines: brushed and brushless. Brushed DC motors are one of the most affordable options a startup can pick. Using brushes to deliver current, these engines are the cheapest and simplest motors you can find. However, they aren’t that efficient and have a short lifespan: you have to replace brushes once they wear off. They can also be extremely noisy, so you can’t use them, for instance, for medical robots. Brushless DC motors are another story. This drive’s operating principle is based on the interaction of magnetic

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Servo Motors Servo motors are high-power electromechanical motors that move on a signal to a certain position and stay put until the next signal. Servos use a feedback mechanism to fix positioning errors. So, if some force exerts pressure on the actuator and changes its position, the servo motor will apply force in the opposite direction to make it right. This feature made servo motors a solid option for everyone who needs high positioning accuracy for their robots. Servo motors can be costly and they require an experienced hand, but they get more and more popular among manufacturers and inspire them to build new solutions. The Bottom Line On their quest to find the best motor, robot manufacturers can feel like kids in a candy store. It’s really hard to make a decision. The most important thing is to get a clear understanding of what your robot needs. You’re picking the very heart of your application, so you’d better focus on the list of requirements for your prototype. RR

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9/10/21 11:53 AM

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ADVANCED Motion Controls Miniaturized servo drives with all the features, power, and performance of bigger drives FlexPro® digital servo drives are designed for high power, small size, and the best available servo motor control. Their small size along with distributed control makes it easy to install them wherever they are needed, including tight integrations like motor casings and robot joints. Their high power density alleviates complications for engineers regarding space and weight that usually come with larger drives. The “mini” footprint operates from 20-90 VDC, with a continuous current rating of 50 amps and a peak rating of 100 amps. The “micro” footprint operates from 10-55 VDC, with continuous current ratings as high as 45 amps and peak as high as 50 amps. ADVANCED Motion Controls 3805 Calle Tecate Camarillo, CA 93012 | USA www.a-m-c.com 1-805-389-1935

CGI Inc. Advanced Products for Robotics and Automation At CGI we serve a wide array of industries including medical, robotics, aerospace, defense, semiconductor, industrial automation, motion control, and many others. Our core business is manufacturing precision motion control solutions. CGI’s diverse customer base and wide range of applications have earned us a reputation for quality, reliability, and flexibility. One of the distinct competitive advantages we are able to provide our customers is an engineering team that is knowledgeable and easy to work with. CGI is certified to ISO9001 and ISO13485 quality management systems. In addition, we are FDA and AS9100 compliant. Our unique quality control environment is weaved into the fabric of our manufacturing facility. We work daily with customers who demand both precision and rapid turnarounds.

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

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Robotics Robotics THE ROBOT REPORT

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Fully Integrated Speed Controller, within 6.2 mm The FAULHABER BXT Flat brushless DC servo motor family has grown; now available in all sizes with a diametercompliant, integrated speed controller. With an additional attachment length of just 6.2 mm, the combination of the BXT H motors with the integrated speed controller is the ideal solution for space-confined applications, particularly if speeds need to be controlled precisely, and high torques are also required. The default factory pre-configuration, along with the Motion Manager software allows for quick and easy commissioning of the system. Typical applications include medical devices, pumps, hand-held instruments, optics systems, robotics & surgical end-effectors.

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FESTO Customize KDFP Quarter-Turn Actuators With Ease To fit your unique application requirements, Festo KDFP quarter-turn actuators are available with many features and accessories including pilot valves, sensor boxes, position indicators and mounting adapters. Choose from a wide range of sizes, torques (10–2,300 Newton-meters) and swivel angles to 90 or 180 degrees. You can order KDFP quarter-turn actuators using our online configurator tool, which makes it easy to find, select, size and order the right unit for your application. This tool also provides access to all prices, delivery times, data sheets and 2D and 3D CAD data in many native and neutral formats.

Festo Corporation 1377 Motor Parkway Suite 310 Islandia, NY 11749 Phone: 1-800-993-3786 Web: www.festo.com e-mail: customer.service.us@festo.com

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Robotics Robotics

FUTEK We make innovation possible FUTEK Advanced Sensor Technology specializes in creating inventive sensor solutions for today’s leading tech innovators: • Load cells • Torque sensors • Pressure sensors • Multi-axis sensors • Instruments • Software Our end-to-end measurement products and services include sensors, amplifiers, and calibration, allowing you to streamline and optimize your system and achieve better results at a lower cost than legacy solutions. All our products are made in the USA. To learn more, visit www.futek.com.

FUTEK Advanced Sensor Technology, Inc. 10 Thomas Irvine, CA 92618 USA www.futek.com +1 (949) 465-0900

GAM GAM GPL: The New Standard in Zero-Backlash Gearboxes GAM’s GPL Series Robotic Planetary Gearbox combines the lowest backlash and high tilting rigidity with vibration-free operation for smooth, controlled motion in robotics and motion control.

• Backlash ≤ 0.6 arcsec (≤ 0.1 arcmin) is 10x better than cycloidal gearboxes

• Backlash does not increase over the 20,000 hours of service live – no • • • •

adjustment necessary Precise, smooth path control and positioning allows for vibration-free continuous coordinated motion Lower cost replacement for direct drive motors with equal or better performance 7 sizes, up to 7000 Nm torque Configurations including solid or hollow flange output, component or fully enclosed with motor mount.

The GAM GPL series robotic planetary gearbox offers a unique level of precision and performance unseen in other gearboxes on the market today!

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GAM 901 E Business Center Drive Mount Prospect, IL 60056 888.GAM.7117 | 847.649.2500 www.gamweb.com info@gamweb.com

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Robotics Robotics

Harmonic Drive Actuator + Integrated Servo Drive Ideal for use in robotics, the RSF miniature actuator is extremely compact and delivers high torque with exceptional accuracy and repeatability. This evolutionary product eliminates the need for an external drive and greatly improves wiring. Since it communicates via CANopen, only 4 conductors are needed: CANH, CANL, +24VDC, 0VDC.

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• Actuator + Integrated Servo Drive utilizing CANopen communication conforming to DS402 and DS301 • 24VDC Nominal +7 to 30VDC Supply Voltage Range • Single Axis BLDC Motor Controller/Driver with CAN & TTL-UART Interface • Single Cable with only 4 conductors needed: CANH, CANL, +24VDC, 0VDC • 14bit (16384 cpr) resolution motor encoder • Zero Backlash

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

Harmonic Drive is a registered trademark of Harmonic Drive Systems

Hottinger Brüel and Kjaer HBK provides cutting edge custom sensor solutions for robotic OEMs. We work with leading OEM manufacturers as to solve their most challenging requirements. As one of the largest manufacturers of strain gauges and electronics, our global engineering competency center enables us to design and manufacture highly customized solutions. We are your partner to design single and multi-component sensors for use in robotic surgical and industrial equipment measuring system forces. Whether it’s a multiaxis measurement on a joint, force feedback on an actuator, or grip control on a manipulator, HBK will design and manufacture highly customized solutions without requiring you to make any significant modifications to your existing parts. If you’re in need of a high volume custom sensor, whether large or small, and you don’t want to make any significant changes to your existing system, then we are the right partner for you.

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September 2021

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Robotics Robotics

maxon Motorizing an AGV Today’s AGVs must be compact and functional robots which are able to move vertically and carry heavy loads. These AGVs cannot fail, and so the choice of their motorization is crucial. There are 5 key points to consider when motorizing an AGV. 1. Choose compact motorization where possible - Drives must fit into restricted spaces, as they are sometimes integrated into existing trucks. A small footprint is critical for applications in logistics. 2. Focus on ease of use – select a plug-and-play solution. 3. Opt for fast delivery of your motor solution 4. Base the design on modularity - Not all AGVs do the same job and therefore having the flexibility to select a solution to match needed specifications is essential. 5. Prioritize safety – select motor options with integrated sensors. maxon’s IDX motor has a diameter of only 56 mm, its performance is equivalent to that of a motor with a footprint 25% larger. The IDX motorization thus combines performance in a compact size and ideal for AGVs. Go to Drive.tech for more details. Visit www.maxongroup.us for more maxon solutions.

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Robotics Robotics

OMS Motion, Inc. OMS Motion has been successfully producing motion controls for more than 35 years. Single axis integrated controls with drives as well as complete multi-axis controllers that can coordinate and synchronize up to 10-axes on a single controller. OMS products are used in numerous markets worldwide, including semiconductor equipment, lab automation, life sciences, factory automation, large- and smallscale research facilities/projects, and others. OMS controllers are very versatile and capable. Founded in the early 80’s OMS developed patented technology that provides advantages in the motion control industry. In the mid 90’s OMS was acquired by a public company with a focus on medical devices. Then in early 2017 OMS separated from the public company, regaining its focus on motion control. OMS has earned a strong reputation for reliable and quality motion control products and is trusted throughout industries worldwide. OMS Motion, Inc. 15201 NW Greenbriar, Suite B1 Beaverton, OR 97006 www.OMSmotion.com 800-707-8111

NEW AksIM-2TM rotary absolute kit encoders offer outstanding performance – to 20-bits with no hysteresis

Renishaw associate company RLS d.o.o Introduces an improved second generation of AksIMTM absolute rotary encoders widely used in many humanoid, medical and collaborative (Cobot) applications, where hysteresis, large through holes, low profile, reliability and repeatability are fundamental. The additional benefits of AksIM-2TM encoders are: • Full range of sizes • Onboard eccentricity calibration • Multiturn capability • Extended operating temperature and pressure ranges

THE ROBOT REPORT

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www.therobotreport.com

Contact Info: 1001 Wesemann Drive West Dundee, IL 60118 Website: www.renishaw.com Phone: 847.286.9953 Email: usa@renishaw.com

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Robotics

SILICON SENSING Compact, rugged motion sensing for any task In operation on the factory floor, in the fields, on the roads, in the air and under water, Silicon Sensing’s DMU11 inertial measurement unit (IMU) delivers complete motion sensing in three-dimensional space. This is a compact, precise, six-degrees-of-freedom (6-DOF) device ideal for any motion control or stabilisation task. Low cost and able to fit in the smallest space, it delivers market-leading performance that is calibrated over its full rated temperature range. All Silicon Sensing MEMS gyroscopes, accelerometers & inertial systems deliver precise, rugged, ultra-reliable inertial sensing.

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

Fastener Engineering This area has long been one of the most read and sought after by our engineering audience! From screws to bolts and adhesives to springs, these critical but often overlooked components are the key to every successful design. FastenerEngineering.com will serve readers in the mechanical design engineering space, providing news, product developments, application stories, technical how-to articles, and analysis of engineering trends. This site will focus on key issues facing the engineering markets around fastener technology, along with technical background on selected components.

Engineering September 2019

A supplement of Design World

covering nuts, bolts, rivets, screws, u-clips, eye bolts, washers and more.

ADDITIONAL RESOURCES: • Special print section in select issues of Design World • Fastener Engineering monthly newsletter

LEARN MORE AT: FASTENERENGINEERING.COM 102

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THE ROBOT REPORT

9/3/21 2:27 PM

OCTOBER 5 @ 11AM Design, Development and Simulation Tools for Robotics Development

NOVEMBER 16 @ 11AM Introduction to Autonomous Mobile Robots sponsored by Cornerstone, 6 River Systems, Mouser Electronics