November 2018
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2018
Robotics
Handbook
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Contents
2018 • therobotreport.com
•
EDITORIAL
06 _ Jumpstarting the social robotics market C OLLABORATIVE ROBOTICS
08 _ GM cobot pioneer shares lessons to
learn from Rethink Robotics
12 _ Inside Rethink Robotics shutdown D ESIGN & DEVELOPMENT
A CTUATORS/MOTORS/SERVOS
16 _ Simulation paving way for self-driving vehicles
50 _ Solving real-time motion control challenges
20 _ ROS for Windows 10 a win-win
A I/MACHINE LEARNING/ DEEP LEARNING SOFTWARE
24 _ 10 DFx tips to optimize robotics design
56 _ ’No-code’ interface simplifies human-robot interaction
28 _ 9 keys to selecting your robot’s OS
I NDUSTRIAL EXOSKELETONS
32 _ Google Cloud Robotics Platform coming in 2019
60 _ Industrial exoskeletons: new systems, improved
34 _ 5 must-ask questions when developing robots
E ND EFFECTORS/GRIPPERS
M OBILE ROBOTS/MOBILE PLATFORMS
36 _ Q&A: OnRobot GM Kristian Hulgard
64 _ 5 challenges when designing autonomous
C AMERAS/IMAGES/VISION SYSTEMS
40 _ Vision system enables DHL’s fully automated
technologies, increasing adoption
68 _ AGVs vs. AMRs: How to best automate
e-fulfillment robot
44 _ 6-DoF pose estimation trained on synthetic data
navigation systems
material transport
BATTERIES/POWER SOLUTIONS
70 _ Searching for better battery power
S ENSORS/SENSING SYSTEMS
46 _ US Army algorithm locates robots in GPS-denied environments
THE ROBOT REPORT
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DESIGN WORLD
Follow the whole team on twitter @DesignWorld
EDITORIAL
VP, Editorial Director Paul J. Heney pheney@wtwhmedia.com @dw_editor Managing Editor Leslie Langnau llangnau@wtwhmedia.com @dw_3dprinting Executive Editor Leland Teschler lteschler@wtwhmedia.com @dw_leeteschler Senior Editor Miles Budimir mbudimir@wtwhmedia.com @dw_motion Senior Editor Lisa Eitel leitel@wtwhmedia.com @dw_lisaeitel Senior Editor Mary Gannon mgannon@wtwhmedia.com @dw_marygannon Associate Editor Mike Santora msantora@wtwhmedia.com @dw_mikesantora CREATIVE SERVICES
VP, Creative Services Mark Rook mrook@wtwhmedia.com @wtwh_graphics Art Director Matthew Claney mclaney@wtwhmedia.com @wtwh_designer Graphic Designer Allison Washko awashko@wtwhmedia.com @wtwh_allison
Director, Audience Development Bruce Sprague bsprague@wtwhmedia.com
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DIGITAL MEDIA/WEB/ DEVELOPMENT
Web Development Manager B. David Miyares dmiyares@wtwhmedia.com @wtwh_webdave Senior Digital Media Manager Patrick Curran pcurran@wtwhmedia.com @wtwhseopatrick VIDEO SERVICES
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DIGITAL MARKETING
EVENTS
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Events Manager Jen Kolasky jkolasky@wtwhmedia.com @wtwh_jen
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FINANCE
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Controller Brian Korsberg bkorsberg@wtwhmedia.com Accounts Receivable Specialist Jamila Milton jmilton@wtwhmedia.com
Videographer Graham Smith gsmith@wtwhmedia.com PRODUCTION SERVICES EDITORIAL
Customer Service Manager Stephanie Hulett shulett@wtwhmedia.com Customer Service Representative Tracy Powers tpowers@wtwhmedia.com Customer Service Representative JoAnn Martin jmartin@wtwhmedia.com Customer Service Representative Julie Ritchie jritchie@wtwhmedia.com
VP, Robotics and Intelligent Systems Dan Kara dkara@wtwhmedia.com @RobotReportKara Editor Steve Crowe scrowe@wtwhmedia.com @SteveCrowe
2011 - 2018 2014 Winner
WTWH Media, LLC 6555 Carnegie Ave., Suite 300, Cleveland, OH 44103 Ph: 888.543.2447 | FAX: 888.543.2447
Digital Production Manager Reggie Hall rhall@wtwhmedia.com Digital Production Specialist Brian Furda bfurda@wtwhmedia.com
www.therobotreport.com
Medical Design & OUTSOURCING
THE ROBOT REPORT
11/2/18 9:05 AM
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Editorial
Jumpstarting the social robotics market
2018 has been a tough year for social robots for the home. No ifs, ands, or buts about it. The failures of Jibo and Mayfield Robotics, maker of Kuri, have been well-documented by The Robot Report.
Aflac robot duck. | Aflac
However, there are a couple companies that are not so eager to turn the page on 2018 just yet. Anki and Sony recently launched Vector and Aibo, respectively, as they both hope to jumpstart what has to this point been a market that over-promised and under-delivered. Anki started shipping Vector, its follow-up to the wildly successful Cozmo robot, in October, while Sony revived its Aibo robot dog that was originally introduced in 1999. Both companies have had success selling consumer robots. As of August 2018, before Vector was released, Anki said it sold more 1.5 million consumer robots to date. And after quickly selling 20,000 sixth-generation Aibos to Japanese consumers, Sony said in August the robot would be available to US consumers before the holidays. Vector and Aibo are both easy on the eyes, have charming personalities, and are packed with powerful sensors and AI that make them the most sophisticated consumer home robots ever. Sorry, iRobot. But technology features alone cannot prevent these robots from becoming dust-collectors in closets worldwide. Unfortunately, both Anki and Sony are setting unrealistic expectations, much like other social robotics companies before them. Cozmo aspired to be nothing more than a toy. And Cozmo did that well. But when you refer to a robot as being “the robot to live with” and “a living character in your home,” as Anki is doing with Vector, that is where companies get into trouble. Jibo and Mayfield Robotics did the same thing. Sure Vector has a charming personality, gives you fist bumps, dances, recognizes faces, and reports the weather, but the novelty will wear off quickly. Anki did work some magic to keep Vector’s price relatively low at $250, but the same cannot be said for Aibo, which comes in at $2,900 with a three-year cloud subscription plan. Running on a Qualcomm Snapdragon 840 and Amazon’s cloud-based AWS server, Aibo can memorize up to 100 faces, learn an endless stream of new
Sony Aibo robot dog. | Sony
tricks and respond to voice commands. Sony knows Aibo’s hefty price tag will prevent it from being a musthave robot, so perhaps Aibo’s goal is to remind folks that Sony was once the king of consumer electronics. Vector is setting the wrong expectations, Aibo is an overpriced toy, and neither really solve a wide-scale problem. These three mistakes continue to permeate social robotics for the home. We are years away from welcoming social robots into our homes that meet expectations and don’t break the bank. To inspire the hardworking, talented engineers of the world working on companion robots for the home, I suggest looking at the Aflac robot duck, which is a result of a partnership between Aflac and robotics toy company Sproutel. The robot duck is simple from a technological standpoint with just five touch sensors along its cheeks, under the wings, and back. Aibo and Vector are much more sophisticated. The robot duck is designed to help children fighting cancer, and there aren’t many things worse in this world than children fighting cancer. The children battling cancer become the duck’s caretaker, feeding it, bathing it, and even pretending to give it chemotherapy through a tube attached to the duck’s chest. Aflac plans to expand its campaign to hospitals across the US later this year, providing newly diagnosed kids aged 3 to 13 years old with a robotic duck free of charge. Sure the robot duck is free and targets a different market, but this is an example of an amazing use case that many consumer robotics companies miss. Social robotics is forecasted to expand to more than half a billion dollars by 2023, driven largely by the growing demands of the aging-in-place market, which is expected to reach 98 million people in the USA by 2060. Judging by what we have seen so far, it seems that number needs to come back down to Earth. RR
Steve Crowe | Editor The Robot Report
scrowe@wtwhmedia.com
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THE ROBOT REPORT
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Collaborative Robotics
GM cobot pioneer shares lessons to learn from
Rethink Robotics
In the mid-1990s, I led the industry/academia team at General Motors that built the world’s first collaborative robots. It was hard work; most people even in robotics had not heard of a “cobot” (or “intelligent assist devices” (IADs) as we referred to the broader category), knew what it was, much less how it could be useful. Our academic partners-in-crime, Northwestern Professors Michael Peshkin and Ed Colgate, founded Cobotics, Inc. (renamed CoMoCo, for Collaborative Motion Control, Inc.), the first startup in the cobot By Prasad Akella market, in 1996 while UC Berkeley Professor Hami Founder & CEO, Drishti Kazerooni went on to found Berkeley Bionics, renamed Ekso Bionics, later on). By the time I left to head back to the Valley and co-found the social networking pioneer Spoke Software, the word was out. Vendors like Fanuc, ABB, Gorbel and Stanley were producing early versions of product, and companies, including GM and Ford, were beginning to explore the use of cobots of different forms because they could see how useful and valuable this form of collaborative automation was on the factory floor.
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Rethink Robotics’ Baxter (right) and Sawyer collaborative robots. | courtesy of Rethink Robotics
Fast forward a decade, and Esben Østergaard, Kasper Støy and Kristian Kassow founded Universal Robots in 2005, while Rodney Brooks and Ann Whittaker launched Rethink Robotics (then Heartland Robotics) in 2008 – and all previous cobot development efforts paled in comparison. Brooks’ track record and dynamism leant a celebrity power to his company. It’s indisputable how much Baxter and its little brother, Sawyer, changed the landscape and THE ROBOT REPORT
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Despite the benefits that robots can bring to a factory floor, 90 percent of tasks are still done by humans. Machines simply don’t have the dexterity, cognition or adaptability to manage those tasks. www.therobotreport.com
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Collaborative Robotics
Because humans will continue to be an important element of the factory floor for the foreseeable future, true digital transformation relies on helping humans complete tasks better and more efficiently. public dialogue around collaborative robots over the next ten years. That’s what makes the news about Rethink Robotics closing its doors such a shame, but it doesn’t come as a surprise. As I learned first-hand at Spoke, and as anyone who has worked in the startup world knows, it’s a hard road. And even after many successful years, companies can fail. Especially when you’re trying to define a category – to prove the value of a technology that has yet to be seen by the vast majority of your audience – the roadblocks are many, and the folks who emerge as victors are few. Still, there are several takeaways we in the world of manufacturing automation can glean from Rethink’s journey, and use to help drive our own successes to the benefit of everyone in the factory. Humans still run the show, and will for a long time Despite the benefits that robots can bring to a factory floor, 90 percent of tasks are still done by humans. Machines simply don’t have the dexterity, cognition or adaptability to manage those tasks. And that means manufacturers still need people and have a blindspot when it comes to operations and data, unless they can find a better way to measure actions performed by humans. The need for cobots and IADs persists. Augmenting and digitizing human tasks is key, but squarely in Industry 4.0’s blindspot Because humans will continue to be an important element of the factory floor for the foreseeable future, true
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digital transformation relies on helping humans complete tasks better and more efficiently. Whether that comes in the form of cobots (like Rethink) or other emerging technology like computer vision, AI and machine learning, manufacturing technology can’t ignore the human element, and instead must be built on the premise of man AND machine working together, not robots replacing humans. Demand for new ideas in manufacturing is still high As the reaction to Rethink’s exit demonstrates, after four decades of manufacturing’s nuclear winter, the manufacturing community is eager for fresh ideas and innovative thinking in the manufacturing realm. Companies who push the boundaries of what’s possible and drive more in terms of productivity, quality and traceability in the industry are in high demand. New companies, like Drishti, are taking up the yoke of creativity and empowering manufacturers to better understand what’s happening on the factory floor – including the tasks that humans do. There’s an ever-present need for startups to be focused on solving real (manufacturing) problems As I look back in cobot time and compare that with where we are in the world of AI, Frank Chen’s notion of “narrow AI” resonates. The simple thought is that when you are creating a new technology, you want to pick the vectors that promise to have clear and measurable impact on your customers while solving the most critical problems. And, by solving these often narrowly defined problems, you THE ROBOT REPORT
11/2/18 9:11 AM
build a revenue path ahead of you. Viewing Rethink’s products from afar, I always wondered if they traded off generalizability and stiffness for ease of programming and a human-friendly appearance. A point was often made by early adopters who were concerned that they couldn’t accurately position the end effector, even with a relatively small payload, because compliance was introduced into the arm to make it human-safe. Leaving the core task of a cobot – of safely and precisely carrying payloads around – compromised. While the better-versed folks can comment on this hypothesis, what continues to be clear to me is that one has to solve clear and financially impactful problems to be viable. It’s never a happy occasion to see a promising company with pioneering technology fail, especially one where a very dedicated and smart set of people have worked so hard. Luckily, Rethink’s end doesn’t mean the end of innovation in manufacturing, and I look forward to an exciting future for all of stripes of Industry 4.0 startups (including Drishti) that are attempting to help companies harness and evaluate data from tasks their machines and employees execute on the floor. The potential to impact GDP and human lives is incredible. Our thanks and best wishes go to the pioneering team at Rethink, whom I personally applaud for moving the world of cobots forward. RR
THE ROBOT REPORT
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Collaborative Robotics
Inside
Rethink Robotics shutdown
Former Rethink distributors and integrators on what went wrong with the cobot pioneer. Rethink Robotics, the Boston, Mass.-based maker of collaborative robots Baxter and Sawyer, shut down on October 3. The Robot Report first reported the story, confirming the news with Rethink CEO Scott Eckert. Founded in 2008 by former iRobot co-founder Rodney Brooks and Ann Whitaker, Rethink raised $149.5 million in funding, with its last round, an $18 million Series E, coming in August 2017.
By Steve Crowe Editor, The Robot Report
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“I can confirm that unfortunately the news is true, Rethink Robotics closed its doors today,” Eckert wrote via email to The Robot Report. “We were pioneers and innovators in the industry and responsible for the creation of the collaborative robot category, but unfortunately we didn’t quite achieve the market success we had intended. We have been helping our team find new homes and have been overwhelmed with interest. It’s a world-class group of people who will continue to do great things in their next endeavors.” Eckert said a deal for Rethink to be acquired fell through at the last minute. Rethink was short on cash as its sales failed to meet expectations. On Oct. 25, German automation specialist HAHN Group acquired Rethink Robotics’ IP. The HAHN Group will further develop Rethink’s technology, “combining it with German engineering and know-how of industrial applications.” HAHN Robotics, the integration unit of the HAHN Group, already has Sawyer listed as a product on its website, www.therobotreport.com
adding that it is the “exclusive distributor” for the cobot. The HAHN Group news has no impact on Baxter. Formerly known as Heartland Robotics, the company was a cobot pioneer with some of the first products on the market. The two-armed Baxter, introduced in 2012, and one-armed Sawyer, introduced in 2015, were known for their animated faces, red exteriors, and ease of programming. But according to a dozen former Rethink distributors and integrators The Robot Report interviewed following the shutdown, Rethink’s robots were not known for their precision and ability to perform as advertised in industrial environments. Some of those former partners shared their thoughts about what transpired. THE ROBOT REPORT
11/2/18 2:18 PM
Rethink Robotics’ Baxter collaborative robot. A Promising Start The Baxter robot was introduced to media outlets in late 2012. Brooks, a celebrity in the robotics world, was featured on 60 Minutes, in The New York Times and other prominent outlets promoting how robots, like Baxter, could work safely around humans and help revamp manufacturing in the US. CEOs of manufacturing companies immediately fell in love with the concept. By June 2012, before it ever sold a single robot, Rethink had raised $62 million. “I’ve never seen a product get so much publicity,” said Dan O’Brien, owner of Norwood, Mass.-based Gibson Engineering, a distributor and integrator that signed on early with Rethink and stuck with them until the very end. “I fell in love with Rethink in 2010.” West Goshen, Penn.-based ONExia, founded in 1984, was the first regional distributor signed by Rethink and the first to sell a Baxter robot. CEO Greg Selke told The Robot Report that Rethink came out of the gate with the right hopes. “Rethink was keying in on the safety aspect. Up till that time, robots were dangerous,” Selke said. “The idea was to make something safe and friendly, and they did that.” Numatic Engineering, a Sun Valley, Calif.-based integrator founded in 1955, signed on with Rethink in 2013. Numatic president Steve Leach said it initially hoped Rethink would revolutionize the industry. “Rethink was the buzz, and we had hopes their robot was going to be the iPhone of the industrial automation world.” THE ROBOT REPORT
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| courtesy of Rethink Robotics
Rethink Robotics 2008 - Founded as Heartland Robotics 2012 - Changes name to Rethink Robotics in June; launches Baxter in September 2015 - Introduced Sawyer cobot 2018 - Rethink Robotics shuts down on October 3 2018 - HAHN Group acquires Rethink IP on Oct. 25
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Collaborative Robotics
Funding Snapshot According to Crunchbase, Rethink Robotics raised a total of $149.5M in funding over 9 rounds:
Aug. 21, 2008 ................... Series A - $5M Aug. 11, 2009 ................... Series A - $7M Nov. 30, 2010 ................... Series B - $20M June 19, 2012 .................. Series C - $30M Nov. 1, 2013 ..................... Series C - $11.5M Jan. 5, 2015 ..................... Series D - $26.6M April 16, 2015 ................... Series D - $13.4M Jan. 5, 2017 ..................... Series E - $18M Aug. 24, 2017 ................... Series E - $18M
The hype was there. The demand was there. And the concept of robots and humans working together collaboratively was there. So where did things go wrong? Performance issue Baxter and Sawyer both used series elastic actuators (SEAs) in their joints. Brooks licensed the technology from MIT. In a typical actuator, a motor drives a gearbox that turns a joint in a robot arm. Those three elements create rigidity, which leads to speed and precision. When Baxter was introduced, the SEAs were described as follows: “In SEAs, the motor and gearbox drive a spring, and it’s the spring that drives the joint. The spring makes the actuator elastic.” According to all of the sources The Robot Report spoke to, the SEAs were a major reason Baxter and Sawyer were less precise. “The SEAs introduce substantial flexibility in the joints of the robot. That is good for safety, but bad for precision and motion performance,” said Ilian Bonev, co-founder of Mecademic, professor at École de technologie supérieure and holder of the Canada Research Chair in Precision Robotics. “It is extremely difficult to control a flexible manipulator, especially when trying to minimize cycle times. Thus, Rethink probably spent too much effort trying to fix hardware problems through software.”
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By using SEAs, Rethink compromised accuracy and repeatability in favor of safety. “Rethink keyed in on the series elastic actuator,” said Selke. “They thought safety was going to be key to the market. Safety was important for Baxter and Sawyer, of course, but the robots still had to be able to function.” “Most industrial robots sound like highquality mechanisms,” said O’Brien. “But because of the spring-like SEAs, the robots became noise-makers. You took them into a lab and demoed them, and they sounded like a poor mechanism. Even the audible sounds from the robot made people think the robots were not a good mechanism.” The Robot Report reached out to Rethink about the SEAs leading to performance issues. However, Rethink has yet to respond. After setting up demos for potential clients, Leach said questions constantly arose about repeatability. “Baxter wasn’t accurate or smooth,” said Leach. “After customers watched the demo, they lost interest because Baxter was not able to meet their needs. We signed on early, a month before Baxter was released, and thought the software and mechanics would be refined. But they were not.” Lackluster sales Being too early to market is not why Rethink’s sales suffered. Its robots were ultimately plagued by performance issues in industrial environments. It is unclear exactly how many robots Rethink sold, but The Robot Report in September 2015 reported the company “recently passed the 1,000 sales mark.” Most of those were “in the U.S. and a good portion were [sold] to academia.” For comparison, Universal Robots (UR), which was founded in 2005, had sold more than 8,000 cobots by the end of 2015. UR sold more than 3,000 cobots in 2015 alone. Leach said in the first 12 months as a Rethink distributor, Numatic was unable to sell a single robot. Numatic eventually signed on as a UR distributor. Leach said Numatic sold one UR robot in the first week, 18 in the first year, and as we wrap up 2018 Numatic will have over 300 UR robots sold.
www.therobotreport.com
“From the ground up, UR’s firmware and hardware were specifically developed for industrial applications and met the expectations of those customers,” said Leach. “That’s really where Rethink missed the mark, while there was an amazing amount interest, Baxter’s mechanical motion and firmware simply didn’t meet the needs of industrial robot users.” Sources told The Robot Report that Rethink targeted the wrong market with Baxter. Monroe Good, Director of Global Business Development, Corun USA, has the exclusive rights to the 100 remaining Baxter robots in the world. Good told The Robot Report he never tried to sell Baxter to a manufacturer. “I pushed Baxter to people where it fits and pushed people away from it where it didn’t fit. I don’t want someone I sold something to calling me later and saying the product is no good.” Sawyer was supposed to be different. But to no avail. Sawyer was more of the same, just with one less arm and a smaller footprint. Rethink never quite caught up to its PR, sources told The Robot Report. Void left in academic world While Baxter was not well-suited for industrial users, the consensus is it was the ideal solution for universities. “If you’re a university and want to teach people how to program a robot or access other people’s studies, then Baxter is the optimal robot,” said Good. “Everyone in robotics research today either has a Baxter or has a friend with a Baxter,” said Brown University roboticist Stefanie Tellex. “In terms of penetration, it’s the closest thing we’ve had to a common platform for manipulation across different research labs.” Leach said that “Rethink had an innovative product. Schools and universities were good targets for Baxter. If Sawyer was what Rethink introduced from the beginning, Rethink might have been OK.” “Rethink’s robots were not built to solve a specific problem,” said Bruce Welty, founder of Locus Robotics. “It was a roboticist’s robot, not a tool for a job.” Ruzena Bajcsy, Professor of Electrical Engineering and Computer Science at the THE ROBOT REPORT
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University of California, Berkeley told The Robot Report, “this is very sad news and detrimental for education and training the future generation of roboticists. I use them in my course [with 150 students] every week [in] lab sessions.” Health of Cobot Market Many are wondering if the demise of Rethink means the collaborative robotics market is slowing. But the answer is the exact opposite. Small to medium-sized manufacturers are yearning for cobots to help them boost productivity. Rethink was not up for the task, but many other cobot companies are. Cobots currently account for only 3 percent of all robot sales, according to the International Federation of Robotics. But cobots are forecast to have a 34 percent share by 2025 when global spending on robotics is estimated to hit $13 billion. UR, which recently rang the closing bell of the New York Stock Exchange, sold its 25,000 cobot in September 2018. UR claims to have a 60 percent share of the market, but that will be difficult to maintain as new cobot suppliers continue to emerge. Many of these new players are Chinese and Taiwanese vendors that spun out of wellestablished industrial robot companies. Another to watch is Kassow Robots, which launched at Automatica 2018 under the leadership of Kristian Kassow, former co-founder of UR. Cobots have been and will continue to be a great way to help human workers grow accustomed to automation. While more competition means more companies will ultimately suffer the same fate as Rethink, the industry as a whole will continue to excel. “In no way does [Rethink shutting down] slow the development or current user excitement about collaborative robots. We see a strong and growing demand for information on this segment of the market,” said Jeff Burnstein, president of the Associa-tion for Advancing Automation (A3). “While Rethink sadly exits the market, dozens of other companies from around the world are entering the collaborative robot market. And this interest in collaborative robots is fueling global interest in robotics, especially among small- and medium-sized companies. We wish the entire Rethink team the best of luck finding new positions in the industry and thank them for all they’ve done to revolutionize the robotics industry.” RR
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Design & Development
Simulation
paving the way
for self-driving vehicles
Drive.ai credits using open-source stalwart ROS for fleshing out the early concept for its self-driving vehicles. By Mike Santora • Associate Editor, Design World
Real roads have drunk drivers, downed power lines, potholes and many other obstacles. The streets of simulation software, however, are infinitely more forgiving. In this digital proving ground, engineers can safely replay millions of scenarios designed to help them better program the software that operates a self-driving vehicle. Regarding the simulations used to prepare self-driving vehicles for the road, the question is how good is good enough? How transferable are simulated results to the real world? California-based startup Drive.ai is building the “brain” that powers self-driving vehicles. But before that brain takes a self-driving vehicle to the streets, it has a separate simulator that takes things to the screen. To get Drive.ai’s deep learning road-ready without the risks and overhead costs of live vehicles, a simulator handled the first one million miles. Drive.ai modifies the simulated world by switching traffic lights, vehicle placement, and creating algorithmicallycontrolled dynamic agents like pedestrians or cars to see how its AI responds. Drive.ai was founded in 2015 by former graduate students in the Artificial Intelligence Lab at Stanford University. In just three years, the deep learning company has gone from post-graduate dream project to an adaptive, scalable, self-driving vehicle system. And not a moment too soon. With Waymo’s self-driving vehicle pilot launch last summer and recent partnership with Walmart, the proverbial race is on. Fueled by a $77 million funding in four total rounds, Drive.ai has progressed fast enough to launch two pilot programs in Texas this summer. A fleet of Drive.ai’s deep learning-enabled Nissan NV200’s will drive themselves geofenced portion of Frisco and Arlington.
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| photo courtesy of Drive.ai
Simulation has played a key role for many companies developing autonomous vehicles, including Waymo, which often touts the number of simulated miles its fleet has driven. Here’s how simulation helped Drive.ai ramp up so quickly. Simulation vital early on Drive.ai VP of Engineering Kah Seng Tay explained that simulation is most critical in the early stages of development. “If you are trying to get to a certain level of safety for autonomous driving in the real world, there isn’t much time or
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resources and scenarios to validate a solution before you have it out in the real world. We have to make sure we simulate the world, test a lot of software and all the edge cases before we try to deploy these cars on the road.” Edge cases, the out-of-the-ordinary scenarios that AI bungles in live tests, are critical. Even the worst human drivers won’t mistake a bicycle painted on the back of a truck for an actual cyclist. But AI might. This potential AI confusion is why any simulator
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Design & Development relies heavily on real-world data collected by a car’s sensors. The AI is not only driving the car, it’s reporting on itself and providing detailed scenarios for engineers to upload into a simulator. When Drive.ai started, the simulator primarily focused on path-planning concerns. How would the car react to other agents on the road? How does it travel through the road network? As such, Drive.ai engineers simulated what they knew of the mapped world and simulated other agents in that world, making sure its software was able to avoid obstacles and collisions. Drive.ai credits using open-source stalwart ROS for fleshing out the early concept for its self-driving vehicles. “We’d like to acknowledge those we’ve built on top of; like many self-driving companies, our company’s roots were in ROS-based software development,” the company said. Drive.ai DPS middleware The company’s AI analyzes data from vehicle-mounted sensors and cameras. This data acts as fuel to make the simulator more accurate. The simulator gains a better understanding of what the car is going to be seeing, instead of just a thematic representation of objects on the road. “We now can simulate our perception outputs effectively, in addition to motion-planning. And we can decide which area of focus we want to test and simulate in,” said Tay. Drive.ai’s current capabilities are built on its own middleware system named Drive.ai pubsub or DPS. The DPS system logs data like sensor input and generated outputs. These file formats can then be parked and replayed over time. This functionality was critical for accurate real-
world simulation. DPS is deterministic and robust enough to create a virtual world realistic enough to be useful. “We care a lot about the ability to factually replay all these message logs in time, in a synchronized fashion, and in a deterministic way — such that we can recreate what happened in the real world,” said Tay. Tay further commented on the ramifications of early errors. “Imagine if you thought that what happened in the real world was different than what the logs collected and analyzed — and you were developing towards those parameters. Then when you deploy in the real world, things could be drastically different from what you thought you had developed. So, we cared a lot about this reliability. We couldn’t lose any of these messages. It needed to be time synchronized and perfect in a deterministic replay. And we could then use it for simulation.” Testing an edge case Again, one of a simulator’s best tools are data collected and analyzed by self-driving AI software in live tests. In one example, Tay relates the case of a Drive.ai vehicle maneuvering around a delivery truck. The self-driving car was
able to nudge past the parked truck, prompting Tay’s team to create other similar obstacles in simulation but with additional conditions. “We tweaked some perimeters and pushed out the truck by a couple of inches. With some of the dimensions — we tilted the angle of the truck, increased its length and width and at some point, the truck just got too wide. There was no longer room for us to pass by the truck, so we had to stop there …” This being a delivery truck that wasn’t going to move, Tay said that he thinks even a human driver would have likely sought an alternate path; there was no way through. The Drive.ai team wanted to see what their car would do in that situation. They wanted to see if it would try to force its way through and collide or whether it would knowingly stop ahead of time and recognize that it needs to find another route. By incrementally adding complications to scenarios in a simulator, engineers can determine the limits of navigable spaces in the real world. In a simulation environment, engineers get to take real-world data collected from the self-driving software and then apply it within a simulated world without restrictions; in simulation,
Drive.ai was founded in 2015 by former graduate students in the Artificial Intelligence Lab at Stanford University. In just three years, the deep learning company has gone from post-graduate dream project to an adaptive, scalable, self-driving vehicle system. And not a moment too soon. 18
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engineers have infinite scalability software and can speed up scenarios and predictions to test the most critical cases. There’s no way to do that in the real world. “That’s the pivotal point. Realistically, more pragmatically, I’d say it’s not going to be perfect, but do think we’ll always continuously invest in simulations,” Tay said. Limits of simulation Simulation can’t handle everything. Live testing continues to find edge cases that can’t be predicted. These cases can only be experienced, recorded, and then uploaded as a new event in a simulator’s vast scenario library. This, of course, takes time. A fundamental question for companies is “how much time, money, and human capital should we dedicate to a simulation program?” Even the most finely-tuned simulation has fidelity limits. At what point should a company start allocating resources to other departments and what does that balance look like? This push/ pull is familiar throughout companies that rely on simulation for R&D. “It’s not particular to Drive.ai or any other industry. With simulation, there is this challenge of: ‘How much time do you spend investing in making a better simulator versus how much time do you spend doing the real development work that you’re trying to achieve? For us, it’s getting self-driving cars on the road. With limited engineering time, there’s always a tradeoff between how much you want to invest in making this simulator realistic – we call it ‘highfidelity’ – versus, ‘let’s spend actual time doing development like our self-driving algorithms.” Tay said many companies can achieve suitable simulation using less than 50% of their engineering time. While Drive.ai has developers working on algorithms for new edge cases, it’s not the company’s sole focus. For Drive.ai, only a small fraction of its engineering resources go to simulation. The rest is used for protection and motion planning, which Tay considers “the actual pioneering work of self-driving cars.” Drive.ai has logged enough simulated miles to feel confident, but it is not ready to rest on its DPS laurels. Tay said Drive.ai still plans to keep developing its simulator in spite of inherent limitations and other engineering resource needs. RR
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Design & Development
ROS
for Windows 10 a win-win Official ROS support for Windows 10 allows more manageability and security for robotics developers. Under Bill Gates’ leadership in the early 2000s, Microsoft was gung-ho about robotics. Gates predicted in 2007 that robotics would be the next hot field. He had a vision of a robot in every home. Unfortunately, the company’s robotics wheels fell off after Gates left Microsoft in 2008. But it appears Microsoft is looking to correct its mis-steps. Microsoft announced at ROSCon 2018 in Madrid, Spain that it is working with Open Robotics and the ROS Industrial Consortium (ROS-I) to bring the Robot Operating System (ROS) to Windows 10. The ROS developer community has built workarounds for Windows, but official support of ROS Melodic Morenia on Windows 10 should make things a lot easier. By Steve Crowe • Editor, The Robot Report It appears ROS for Windows is an opportunity for Microsoft to further expose its Azure cloud platform, and associated products, to the vast number of ROS developers around the world. The release is being called “experimental” at this point, but be assured Microsoft, Open Robotics, and ROS-I are committed to making this work. “We’re looking forward to bringing the intelligent edge to robotics by bringing advanced features like hardware-accelerated Windows Machine Learning, computer vision, Azure Cognitive Services, Azure IoT cloud services, and other Microsoft technologies to home, education, commercial, and industrial robots,” says Lou Amadio, Microsoft’s
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From left: Chris Wanstrath, Github CEO and co-founder; Satya Nadella, Microsoft CEO; and Nat Friedman, Microsoft corporate vice president, Developer Services. | courtesy Microsoft
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Design & Development A Mars Rover robot simulated on Microsoft Robotics Developer Studio. | courtesy Microsoft
principal software engineer for Windows IoT, who is also on the ROS 2 Technical Steering Committee (see sidebar for more details) that is tasked with determining the development roadmap. Microsoft will host the Windows builds for ROS 1, and shortly ROS 2, as well as provide documentation, development, and deployment solutions for Windows. To date, ROS has been running OS’ such as Linux and an experimental version of MacOS. “As robots have advanced, so have the development tools. We see robotics with artificial intelligence as universally accessible technology to augment human abilities … [and] this development will bring the manageability and security of Windows 10 IoT Enterprise to the innovative ROS ecosystem,” Amadio says.
Microsoft’s robotics history Perhaps you recall Gates’ prediction about robotics being the next hot field. Tandy Trower, currently head of Hoaloha Robotics, steered Gates down the robotics path. The company’s first investment in robotics was Microsoft Robotics Developer Studio (MRDS), which was first released in 2006. It was a robotics development and software package. It was released about one year before Willow Garage announced ROS, but never gained traction. Trower tells The Robot Report he “met
several times with Willow Garage execs, exploring potential areas where we could collaborate. However, their focus at that time was primarily on the development of their PR2 robot.” Microsoft’s robotics efforts fell apart after Gates left in 2008 to focus on his foundation. Trower left one year later after a disagreement with Microsoft execs about the company’s robotics strategy. Three years later in March 2012, the last MRDS update was published. And in 2014, Microsoft’s robotics group officially shut down.
ROS 2 Technical Steering Committee Members Lou Amadio ...................... Microsoft Matt Deminico ................. TARDEC Doug Fulop ....................... Amazon Matt Hansen .................... Intel Seonman Kim .................. LG Electronics Karsten Knese ................ Bosch Dejan Pangercic .............. Apex.AI Matt Spencer ................... Arm Allison Thackston ........... Toyota Research Institute Dirk Thomas .................... Open Robotics Yoonseok Pyo .................. ROBOTIS
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ROS for Windows: embracing open source There was once a time when Microsoft was antiopen source. In 2001, Microsoft’s then-CEO Steve Ballmer said “Linux is a cancer that attaches itself in an intellectual property sense to everything it touches. That’s the way that the license works.” Ironically, many robots run on Linux, but Microsoft’s had a change of heart over the years. It joined the Linux foundation in 2016 and has since become one of the leading contributors to GitHub. In 2016, for example, Microsoft had 16,419 contributors to open-source projects on GitHub, putting it a ahead of Facebook’s 15,682. In fact, Microsoft was contributing to GitHub so often that it went out and purchased the software development platform for $7.5 billion. At the time of the acquisition, GitHub had more than 28 million developers, which are now tied much closer to Microsoft’s development tools. ROS has some popular repositories on GitHub, which is another reason the ROS for Windows news makes sense. Microsoft also partnered with Qualcomm in May 2018 to jointly create a vision AI developer kit. The device, which enables on-device inferencing for AI on the edge, runs on Qualcomm’s Vision Intelligence Platform for on-device edge AI/ compute and takes advantage of Azure Machine Learning. Again, this is part of Microsoft’s plan to embrace the development community and make sure Azure is OS-agnostic and plays nicely with many different platforms. Joining ROS-I Consortium Microsoft is also joining the ROS-I Consortium, whose mission is to extend the advanced capabilities of ROS and robotics to manufacturing environments. Matt Robinson, Program Manager ROS-Industrial Consortium Americas, tells The Robot Report some of ROS-I’s OEM partners have been calling for an official version of ROS for Windows. “Anyone who has worked in a factory or industrial setting knows that most of the tools that run the operation run on Windows, or “boxes,” and a lot of the contemporary tools we use to set up robotic systems today also run on Windows.” “So we see this as a real breakthrough to enable more rapid and broader acceptance. As the announcement details, there is still an understanding that Linux will be a part of the solution, and for specific applications may still be the solution, so working with Microsoft on this latest initiative has been a great experience, and we look forward to future collaborations relating to ROS applications running on Windows 10 IoT and leveraging Azure where it makes sense.” RR THE ROBOT REPORT
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Design Development
10
DFx
tips to optimize
robotics design
The purpose of design for excellence (DFx) is to achieve alignment between the design of a product and production processes - as early as possible. The outcome? Optimized cost and quality while addressing the unique needs of each individual customer.
Cirtronics, a Milford, NH-based contract manufacturer that has worked with some of
the top robotics companies in the world, shares these 10 essential DFx tips for robotics design to help you navigate as you transition from design to manufacturing.
1 Don’t reinvent the wheel As you design new products, keep it simple. Reuse what works. Innovation does not always mean starting from scratch. Robots are inherently complex. Robotics engineers are inherently creative. No matter how tempted you are to start with a clean sheet of electronic paper, build on your past success (and what you learned along the way). Re-use successful designs (cabling, mobility, modularity), components you know you can source, and software architecture that you know works well. By Jim McCall director of engineering & manufacturing Cirtronics
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2 Know your strengths Identify your company’s core competencies. Your robot is more than a machine. It’s your creation. Now what? Many designers want to keep control in-house and build each of their robots themselves to make sure it’s done “right.” How will you scale up manufacturing from prototype to production? How will you handle fulfillment? Is the best use of your resources building production capabilities? Know what you want or need to keep in-house. Innovation? Check. Prototyping? Maybe. Production? Maybe not so much. Whether you decide www.therobotreport.com
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to manufacture in-house or outsource manufacturing, create a manufacturing partner relationship to support the intense collaboration needed for success..
3 Teamwork and synergy Cooperation, communication and collaboration are keys to success. Each company needs different things from manufacturing. As you assess your core strengths, use a partner’s complementary skillset, which includes flexibility and responsiveness. Find a partner who will work with and for you, always keeping your best interests and your specific needs in mind.
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4 Leverage, leverage, leverage Depending on your market, you may benefit from prior experience in navigating FDA regulations or complying with Department of Defense requirements. Capitalizing on an outsourced partners’ strengths and previous experience can help get your product successfully to market. Leverage the expertise, experience and knowledge of your manufacturing partner as early as possible. Take their advice to heart. Beyond prior experience, certifications, regulations and registrations, your manufacturer may offer you access to their broader engineering expertise. Use it. Seek out opportunities to work with them to improve your product design. www.therobotreport.com
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Design Development 5 Design reviews: manufacturablity Move your design toward ease of assembly while maintaining high quality. Have your design team engage as early in the design as possible, with your manufacturing engineers, to make sure your design is efficiently manufacturable. Design with awareness and flexibility. Realize that modifying design early in the process is where the most costs (and headaches) can be avoided. 6 Supply chain expertise and risk mitigation Supply chains - availability of parts, and materials the parts are made from - change. There may be shortages and limitations that could impact availability of the parts on which your design relies. Early in the design process, review your bill of materials against forecasts to identify strategies to ensure uninterrupted sourcing. Include your manufacturer’s supply chain experts in the design reviews - be willing to modify your design to mitigate supply chain risks. 7 Design for testing
Have your test team engage with your manufacturer’s test engineers. Working with test engineers will ensure necessary and appropriate testing, so that you and your customers can feel assured that the quality you promised is being delivered. From flying probes (sounds alien but, trust us, this is important for board validation), to functional testing of mobile robots in actual test tracks, make sure your manufacturer’s capabilities, capacity, and resources are a good match for the kinds of testing your product needs.
Get ahead of the curve. Work with a manufacturer to come up with strategies to handle potential fluctuations in ways that best accommodate your needs.
9 Fulfillment How do you get your product where it needs to go? Fulfillment. Consider working with a manufacturing partner that can ship product to you or directly to your customers. That way, you can spend your resources on the next best product. Verify that your manufacturer can provide the fulfillment service that best matches your needs. 10 DFx is built on successful relationships DFx should include collaborative building, testing, discussions and debates. Capitalizing on each other’s strengths. Being willing to change if necessary. Communicating. Listening. Responding. Transparency. Working together toward mutual success. Holding space for evolution and innovation. Respect. If you think these points sound familiar, you’re right. These are the things that make all great relationships great. A great relationship can make all the difference as you bring your product to market. RR
8 Fluctuations and flexibility Flexibility and scalability are extremely valuable in responding to fluctuations in demand. What if a customer orders 10 or 100 or 1000, and suddenly you need more? Working with a manufacturing partner that has the ability to ramp up quickly and still be lean is important. 26
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www.therobotreport.com
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Experienced Robotics Manufacturing " Cirtronics has worked with us
from the beginning, making sure that every decision and plan was specifically tailored to our needs. Cirtronics deployed resources and proactively contributed their expertise to quickly and effectively transition Ava from design to production – without consuming our valuable engineering talent. " - Marcio Macedo, VP at Ava Robotics
Cirtronics’ DFx Optimizes Transition to Manufacturing
What can we build with you? Cirtronics 11-18_Robotics Hbk.indd 27
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Design & Development
9
keys to selecting your robot’s OS
This year, surgeons at Oxford’s John Radcliffe Hospital used a robot to conduct eye surgery for the first time ever. Tokyo’s Henn Na Hotel implemented multi-lingual robots to help guests check in. The supermarket chain Schnucks tested an aisle-roaming robot named Tally to identify out-of-stock items and verify prices. And Tennibot created the world’s first robotic tennis ball collector.
By Kyle Fazzari software engineer Canonical
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These are just a few examples of how robotics is converging with artificial intelligence and machine learning to become one of the most promising and exciting initiatives in the network of smart, internet-connected devices. IDC projects worldwide robotics spending on hardware, software and services will reach $230.7 billion by 2021. Robots are playing a larger and larger role across almost every industry. However, as with many other initiatives in the wider internet of things (IoT) sector, companies shouldn’t just dive in without a well-crafted technological blueprint from the development stage onward to ensure they are building a highly productive, sustainable, future-proof, and secure robot. The right strategy starts with the right operating system (OS). Unfortunately, the importance of the OS isn’t always obvious until the company is too invested to change it, which can lead to a slew of delays or other issues. The OS that’s perfect for hacking things together may be impossible to maintain once the robot reaches production. Similarly, the build-your-own option means maintaining the entire OS (backporting upstream security updates, etc.) for the lifetime of the robot. The OS choice also can influence a company’s monetization route, support offerings, and security strategy. As companies join the robotics revolution, there are a number of essential OS factors to consider that can help or hinder robot development as it moves from development through to production and maintenance. Here are nine of them. www.therobotreport.com
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A screenshot of Ubuntu. | courtesy Canonical
1 A consistent OS The OS used on the robot during development should also be the one used in production (or at least closely related). There’s a balancing act to be had here – for example, the engineering team will naturally want the OS that best supports whatever they’re developing, but it’s easy to get tunnel vision during development and forget to consider other factors. 2 Software stack compatibility Regardless of other reasons that go into deciding on an OS, selecting one that isn’t compatible with the technology required (libraries, frameworks, etc.) is a recipe for disaster. The engineering team will spin its wheels while competitors hit the market first. Perhaps required libraries are written specifically for certain Linux distributions, or the team has settled on using some middleware to enable faster development. If a potential OS is evaluated with this need in mind, it will help lead to a streamlined development process. 3 Hardware compatibility Hardware compatibility should also be a primary concern, for much the same reason as software: a significant chunk of time will be spent ensuring components THE ROBOT REPORT
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work together before any real progress can be made on the robot itself. For example, it’s not unusual to find hardware that requires drivers only written for specific Linux distributions, or to work with vendors that have limited exposure to Linux in general.
4 Development team familiarity Speed is huge when developing any product. When a team is considering programming language options for a new project, the decision is heavily influenced by the team’s familiarity with said language. This isn’t necessarily because the team is resistant to change, but because they know they can produce higherquality work in less time if they can use a familiar language. A similar consideration must be made when considering robotics OS. If the engineering team isn’t already familiar with it, time to market will be delayed as they learn its ins and outs. 5 Ease of system integration A robot is rarely a standalone device; it often needs to seamlessly interact with other devices. Cloud robotics, speech processing and machine learning are all use cases that can benefit from processing information in a server farm instead of on a resource-constrained robot. If possible, it makes a lot of sense to use the same OS on the robot as in the cloud. It prevents division of domain knowledge, and www.therobotreport.com
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Design & Development The right strategy starts with the right operating system (OS). Unfortunately, the importance of the OS isn’t always obvious until the company is too invested to change it, which can lead to a slew of delays or other issues. keeps processes the same, decreasing development time of both the client and server components.
6 Support availability Every engineer gets to the point where they need some help. Where do they turn? If they need help with the OS, they often turn to the community around that distribution, where more often than not, others are experiencing the same issues. While community support is one of the best things about Linux, it’s never a good idea to rely on it commercially: sometimes no one responds, no one knows, or no one has time to figure it out “right now.” Robotics developers should choose an OS backed up by commercial support options where they can predictably and reliably seek advice and solve problems quickly. 7 Software update process Once a robot starts the move from development to production and maintenance, new factors come into play. A big one is the software update process, since, sadly, it doesn’t take long to find examples of companies that started shipping devices without considering the need to update them. With the rush to get devices to market, it’s not at all rare to find devices with hard-coded credentials, development keys, various security vulnerabilities and no update path. Companies should choose an OS that has this functionality built into it.
OS are typically only supported for a set amount of time. If the supported lifespan of the OS is shorter than the anticipated lifespan of the robot being produced, it will eventually stop getting updates.
9 Ensuring a profitable lifespan Actually shipping and maintaining robots might be the final story for some, but it shouldn’t be, and it certainly isn’t the strategy necessary to retain customers and extend the robot’s lifespan. How does it stay relevant as competitors come out with newer products? One way is by supporting an app store. This isn’t something that will apply to all robotic platforms, but it’s something that should be considered. Depending on the purpose of the robot, one could actually open it up completely, allowing control or sensor use via APIs, and then support a third-party app store of some kind. This can increase the longevity of the robot by essentially allowing third parties to have another vision for it, but this depends on the robot being pretty general-purpose. Even if the robot isn’t generalpurpose, an app store can open up alternative revenue streams, where new functionality can be provided in exchange for a fee, or on a subscription basis.
Author Bio: Kyle Fazzari joined Canonical as a Software Engineer in 2015, where he works on Snaps and Ubuntu Core to help companies bring secure and robust IoT devices to market. Prior to this, Kyle worked as a Roboticist for the US Navy. His background and interests include robotics, embedded systems, and proclaiming that C++ is the only real language..
By keeping these nine factors in mind, companies can successfully seize the huge opportunity that robotics presents. The demand and market potential are there – now it’s just a matter of being ready. RR
8 Long-term support In addition to considering how OS updates are delivered, one must consider for how long those updates will be delivered. Specific versions of an 30
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www.therobotreport.com
THE ROBOT REPORT
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Design & Development
Google Cloud
Robotics Platform
coming in 2019
By Steve Crowe • Editor, The Robot Report
The term “cloud robotics” was first coined in 2010 by James Kuffner, who was working at Google at the time. Google has since teased various cloud robotics efforts, but it appears the Mountain View, Calif.-based tech giant is going full-bore in 2019 with the launch of the Google Cloud Robotics Platform for developers. Details are somewhat scarce at the moment. The Robot Report reached out to Google Cloud for more information, but had not heard back at press time. We also spoke to a couple sources who are familiar with the project, but they are not at liberty to discuss the Google Cloud Robotics Platform yet. But suffice to say the timing is right thanks to the maturing of both the robotics market and Google Cloud’s products. As Sandy Agnos, Brain Corp.’s Director of Global Business Development, put it: “Robotics and the Cloud (RaaS) are like peanut butter and jelly.”
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Here is what we have gathered based on the Google Cloud Robotics Platform website. The platform combines AI, robotics, and the cloud to enable “an open ecosystem of automation solutions that use cloud-connected collaborative robots. Our AI and ML services will make sense of the unpredictable physical world, enabling efficient robotic automation in highly dynamic environments.” With the Google Cloud Robotics Platform, developers will have access to all of Google’s data management and AI capabilities, from Cloud Bigtable to Cloud AutoML, which at press time included beta versions of AutoML Translation, Natural Language, and Vision. Google says its “object intelligence service will provide low-latency object recognition and pose detection which can be used for grasping, automated inventory and more.” The Google Cloud Robotics Platform will also use Google Cartographer, which provides real-time simultaneous localization and mapping (SLAM) in 2D and 3D. Cartographer will continusouly process sensor data from multiple sources and will allow robots to localize in a shared map. Google says “even if your environment changes over time, our spatial intelligence services will analyze your workspaces and can be used to query, track and react to changes in the environment.” Google says its “customers fully own their data, which is always encrypted on our platform. If their plans change, they can take their data with them wherever they go.” Google says the platform will cover foundational needs, including secure and robust connectivity between robots and the cloud. Users will be able to manage and distribute these digital assets with Kubernetes, and can turn to Stackdriver for data logging, monitoring, alerting, and dashboarding. Benefits of cloud robotics Cloud robotics offers many benefits, including the following: Big Data: Access to updated libraries of images, maps, and object/product data Cloud Computing: Access to parallel grid computing on demand for statistical analysis, learning, and motion planning
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Collective Learning: Robots and systems sharing trajectories, control policies, and outcomes Human Computation: Use of crowdsourcing to tap human skills for analyzing images and video, classification, learning, and error recovery. The Cloud can also provide access to datasets, publications, models, benchmarks, and simulation tools, open competitions for designs and systems, and open-source software. Google, Microsoft target robotics developers The timing of the Google Cloud Robotics Platform might be a coincidence, but robotics are reportedly making a comeback at Google. Of course, Google went on a buying spree in 2013 acquiring eight robotics companies, including Boston Dynamics. But things did not end well and Google eventually sold Boston Dynamics to Softbank. Multiple reports indicate Google is working on a rival to the domestic robot Amazon is working on. This could be under the leadership of Ryan Hickman, who in June 2018 returned to Google Brain after he tried to launch a robotics startup called TickTock AI, which was also exploring consumer robotics applications. Hopefully Google’s robotics efforts work out better this time around, but things will not be easy, especially when it comes to winning over robotics developers. Microsoft announced at ROSCon 2018 that it is working with Open Robotics and the ROS Industrial Consortium (ROS-I) to bring the Robot Operating System (ROS) to Windows 10. It appears this move is an opportunity for Microsoft to further expose its Azure cloud platform, and associated products, to the vast number of ROS developers worldwide. The release is being called “experimental” at this point, but be assured Microsoft, Open Robotics, and ROS-I are committed to making this work. “As robots have advanced, so have the development tools. We see robotics with artificial intelligence as universally accessible technology to augment human abilities … [and] this development www.therobotreport.com
will bring the manageability and security of Windows 10 IoT Enterprise to the innovative ROS ecosystem,” says Lou Amadio, Microsoft’s principal software engineer for Windows IoT, who is also on the ROS 2 Technical Steering Committee. This is not the first time Microsoft has focused on robotics developers. It launched in 2006 Microsoft Robotics Developer Studio (MRDS), a development and software package that was released about one year before Willow Garage announced ROS. However, MRDS never gained traction, and the last MRDS update was published in March 2012. Microsoft’s robotics group officially shut down in 2014. Google and Microsoft have both had ups and downs in the robotics industry. Let’s see how both tech giants fare this time around targeting robotics developers. RR
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Design & Development
5
must-ask questions when
developing robots
During his keynote at the Robotics Summit & Showcase, Jabil VP of Global Automation and 3D printing John Dulchinos discussed the challenges robotics companies face while developing commercial class robotics systems. Is your team thinking big picture during early stage planning? Are they looking beyond specific product details to focus on how the product By Mike Santora Associate Editor Design World
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functions in the system at large? Here are five essential questions Dulchinos says you must consider during robotics development. Are you a platform or solutions company? Platform companies create partial solutions to technological challenges that other companies can then integrate their products with to create a consumer level solution. It’s an enticing business model. The initial investment for a platform company is fractional compared to developing a complete, market-ready solution. The challenge is convincing potential partner www.therobotreport.com
THE ROBOT REPORT
11/2/18 10:29 AM
companies that you have a reliable platform already prepared for growth. This partnership recruiting stage requires a substantial investment in business development and marketing. Industrial robot companies are platform companies. Few are solving problems outright. This business can certainly work; it does for many robotics companies. However, Dulchinos says the most successful robotics company create complete solutions. “While the vast majority of robot companies sit on the platform side, the most successful ones sit on the solutions side. If you really want to get funded, it’s about ‘how do you align to a market where you can deliver a solution.’” Are you thinking ecosystem? Dulchinos describes a complete ecosystem solution as a “platform on steroids.” Not a product, ecosystems are interconnected environments involving several players each offering different contributions to achieve a result. Dulchinos uses multinational software company SAP as an example of an ecosystem-focused company. “They have six categories of partners: Business networks, implementation services, platform and infrastructure, channel & SME, innovation, and influence forums & education. When you look at the number of partner companies for each section – this is why a company like SAP can serve a wide range of markets and deliver full, end-to-end solutions.” Thinking beyond product and into the broader ecosystem environment is the best way to enact change within the marketplace. Growth opportunities a greater with an ecosystem than the more one-dimensional single product offering. Who is your real competitor? Say you are an incumbent player in a given market. The growth of your product/solution might look something like this: First, you provide a solution for a customer base. Eventually, you begin to receive feedback from influential power users. This feedback helps you THE ROBOT REPORT
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improve your solution. As you continue to advance your product using this customer feedback, you eventually reach the point where your product eclipses initial markets requirements. As problems go, there are worse spots to be in. But Dulchinos refers to renown Harvard Business School Professor Clayton Christenson’s analysis that this is the point where smaller, more nimble startups look to disrupt the market. “You do a great job serving the power users, but you open the door for some little startup company creating a minimum viable product that serves the very bottom of the market. And then they start to get a little bit better, and a little bit better … until they surpass the baseline of the industry. Pretty soon they’ve disrupted the vast majority of your customer base, and you’re relegated to this further and further, far-reaching part of the market.” Ouch. Cautionary tales include Uber’s disruption of the taxi market, Waymo’s potential disruption of Uber with its autonomous vehicles, and the decline of Kodak. What is your network effect? Network effect is relatively straightforward in the digital space. Users create data, algorithms use that data, and then you refine your service based off that data. This analysis leads to a better overall solution, resulting in more users. All of this, of course, creates more data for you to feed into algorithms – fortifying information accuracy and value. Repeat. This process eventually creates a sort of self-sufficient cycle of productivity. Several blue-chip companies like Google, Facebook, Amazon, and Waze all use this model to develop powerful revenues and profit margins. With a small number of users, this model might not have as much impact. But if you have a billion users, a dataset that comprehensive is a very powerful company asset.
help you evaluate objectives and, more importantly, determine how to monetize the relationship between customers, expenses, and resources — an excellent exercise if you have not already done so. For Dulchinos, robots represent four classic business model opportunities. The first and most classic of all is. “You sell a robot, for a large capital expenditure, you get the money, you may have some services associated … and that’s how you make money. Most of the stuff that goes into manufacturing plants operate by that principle. The problem is, it’s really lumpy. You get a good quarter, it’s great, but then people are digesting it, and you don’t have any sales for a while.” This lack of growth stability has led venture capitalists to begin pushing the second type of business model, subscription-based services. At present, most VC-funded robot startups are moving in this direction. Essentially, you’re renting out your equipment for a monthly fee. To do this, though, you must first have a functioning solution and plenty of money. Under this business model, you have to fund the capital investment and then amortize it as your customers pay the rent on your product. This is a good strategy when playing the long game, but in the short term, upfront costs can be challenging. The third model, made famous by companies like Gillette, HP and Intuitive Surgical, involves locking users into your solution and keeping them long-term. For example, HP provides users with high-margin inkjets that sell for 90% gross margin and then users, ideally, stay with the product in perpetuity. The last business model focuses on data. All major players in the digital economy thrive here – Google, Facebook, Snapchat, etc. Data is harvested and sold for profit. Pinpointing the most effective business model for your product is an essential early-stage decision for maximizing your solution’s potential. RR
What is your business model? Common in the startup community, online business model canvases are an easy way for you to address some classic business interconnects. The canvasses
www.therobotreport.com
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End Effectors-Grippers
Q&A:
OnRobot GM Kristian Hulgard
OnRobot discusses what it looks for in potential acquisitions, the commoditization of cobots, and adding sensing to grippers.
Kristian Hulgard GM, Americas, OnRobot
OnRobot made a major splash with its merger that brought together US-based Perception Robotics, Hungary-based OptoForce, and Denmark-based OnRobot. Under the leadership of CEO Enrico Krog Iversen, OnRobot’s goal is to become the one-stop shop for collaborative end-of-arm tooling.
By Steve Crowe • Editor, The Robot Report
The company has a long way to go, but it’s catching the eyes of many in the industry with its recent moves. In August, OnRobot acquired Denmarkbased startup Purple Robotics, which was founded by former Universal Robots employees who created an electrical-based vacuum gripper, now known as the VG10, that doesn’t require an external air supply. OnRobot also raised a funding round led by Summit Partners, with participation from existing investor The Danish Growth Fund, that should enable it to continue its acquisition streak. The Robot Report caught up with OnRobot’s Kristian Hulgard, GM, Americas, at IMTS 2018. We discussed what OnRobot looks for in potential acquisitions, the commoditization of cobots, adding tactile sensing to grippers and more. One type of gripper missing from OnRobot’s portfolio is one with soft robotics technology? What are your thoughts on the technology? Our strategy, in regard to both acquisitions and development of new products, is to add something new. We want to be sure that when we launch something, it’s something that’s not just another run-of-the-mill product. That’s what we’re showing here at IMTS. Most of the technology is brand new. Without going into detail, if soft robotics technology fit within our vision, that would be something we could potentially look at. But we can’t commit to something in the future yet.
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THE ROBOT REPORT
11/6/18 10:49 AM
OnRobot QC10 Quick Changer. | photo courtesy of OnRobot
What made Purple Robotics an attractive acquisition? I think it’s a genius product. It’s something that’s been missing in the market. It has flexibility. It also has its limitations, but all products do. Through our integrators and customers, we saw that this gripper is a fit for about 90% of the applications out there. History-wise, we also know the guys behind the company. There was never a doubt that the product was of the highest quality. The guys behind the product are very talented.
The VG10 vacuum gripper was developed by Purple Robotics, which OnRobot acquired in August.
How does OnRobot plan to maintain its sales growth? Our growth plan is to get the right partners on board. There are still a few holes in our existing geographically-covered areas, but what is extremely important is that we don’t only focus on Universal Robots. Due to the history of the company, [Universal Robots] was, of course, the first robot brand we were supporting because we knew how it worked and were comfortable with the product. Right now, all our products are compatible with all robot brands. THE ROBOT REPORT
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| photo courtesy of OnRobot
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End Effectors-Grippers As you can see in our booth, we have Fanuc, Kawasaki, KUKA. We’re not married to anybody. We are aiming for the whole spectrum of collaborative robots and that’s definitely the key for the growth that we’re aiming for. We want to go out and make partnerships with all robot brands. What geographical area is seeing the most growth for OnRobot? The US is a big potential market for us and is something we’re focusing on. We showed that by starting our commercial office in Dallas. We have our R&D and production in Los Angeles. But certain countries in Europe tend to be more automation heavy, like Germany. They are a step ahead of everybody. The focus on the US is very high from our side. Our footprint in the US market will be as big as we can make it with local support, technical personnel, and area sales managers. Where would you rank the Danish robotics cluster? Wow, that’s a hard question. Odense has done a lot to follow the robot trend that came out of Universal Robots. We owe a lot to the guys at UR. They started the adventure. What the city and the whole area picked up on is that you have a great university there. The state and the city have introduced programs for people abroad to come and study robot technology at Odense University. That snowball is rolling now, and that’s what you see now with MiR and the recent sale to Teradyne. We have more and more companies coming out of the area. I think every single company has received recognition for what they’re doing. I’m Danish, so you’re preaching to the choir, making me proud. How did you get into robotics and start working for OnRobot? I was working at a manufacturing company. After that I was hired by Universal Robots. I think I was employee number 35. It was a very young company back then. We had to sell the concept of the cobot. I left Universal Robots to chase a dream of living abroad, and I moved to the Middle East for about five years. Then I got back in
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contact with Enrico and, since he owns OnRobot, we found an agreement for me to get back into automation, which I’d been looking to do for quite a while. It’s great to come back now and see that the concept we worked so hard on selling, everybody is in on it now. Everyone knows what a cobot is, everybody knows the benefits of collaborative robots. Now you have to sell, and that’s what we’re doing, how you can add value outside of just the collaborative robot itself. How do you actually add more value to your application? That’s how we see it in your tooling, in the flexibility of using tools for different things. How are collaborative robots becoming easier for the industry to use? You have to recognize that, at some point, the collaborative robot will become a commodity. All the robot brands, they will start being able to do the same thing, right? So what is actually adding value to your application? If you have all the same features and all the same robots, then you need to look at the ecosystem around the robot. What is actually adding value? Here, all our products are multipurpose. The whole mindset about easy installation, flexibility in product, programming is simple – our products have that. Whether your application is high-mix, low-volume or high-volume, low-mix, it doesn’t matter for us. Won’t robotic grippers being commoditized at some point, too? I think that’s the hardest part of having a technology manufacturing company. You need to have some really sharp R&D guys that can come up with new features and new functions in both new and existing products. Since we have the new investment on board, we have this pile of cash now for acquisition purposes. Enrico’s been quite verbal about 8-12 acquisitions in the next two years. That shows that OK, we’re ready to commit to new technologies and products so we keep reinventing ourselves, and keep the ball rolling in terms of giving some new values to our partners.
www.therobotreport.com
What is a trend to watch in robotic grippers? Where I see the most potential in new products is adding some sort of sensing technology. Whether that is tactile, a force-torque sensor or a laser, the future of collaborative tooling is to add intelligence to the tool. Now you don’t only have a gripper that can do this or that, but it gives feedback to the program, which has the freedom of using that information for whatever needs to get solved. Tell us about OnRobot’s new Quick Changer, which was built by Purple Robotics? It’s a click-on, click-off tool changer that goes with all our products and all robot brands. You can change the tool in five seconds, even with the electronic connection, then you’re up and running with a new tool. You can do the preset programming in your collaborative robot and you’re ready to handle other products. Of course, it has its limitations in a sense of people asking, “do you have in and outputs of vacuum going through?” But since it is a collaborative robot, you’re going to be working around a collaborative robot anyway, and you always have just one connector. You don’t need to have the vacuum one that is going through. You don’t need that. You just click it off at the connector and then you’re ready. Will we ever see a gripper as capable as a human hand? I think you have to remember that our market is industrial, so you need to make industrial-grade products. With the handlike grippers we’ve seen so far, it’s probably not going be so useful in industrial settings, but you can get close. It’s all about adding the sense of touch to your grippers so that you can actually follow the curves and feel where you are on the products. That’s why we’re here, to show that you don’t need to have 300 different grippers. Even if you’re just limited to, let’s say 100, then we’ve still come a long way. RR
THE ROBOT REPORT
11/6/18 10:49 AM
Easy Engineering!
Finding the right handling system couldn’t be quicker or easier: Design a handling system in less than 10 minutes with the Handling Guide Online. All systems are delivered fully tested and assembled. Try out the new software tool today! Learn more: www.festo.us/HGO
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11/2/18 10:33 AM
Cameras Imaging Vision System
Vision system
enables DHL’s fully automated fulfillment robot
By The Robot Report Staff
DHL Supply Chain has a broad innovation agenda for its warehouses, including the use of augmented reality, AGVs, robotics and everything in between. One laborintensive task DHL is looking to automate at its warehouse in Beringe, Netherlands is manual picking. To do so, DHL worked with Robomotive, an industrial automation specialist in the Netherlands, to create a state-of-the-art robot cell that performs depalletizing, picking and order-fulfillment functions.
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THE ROBOT REPORT
11/2/18 10:36 AM
With the success of this project in Beringe, Netherlands, DHL is now looking at new applications for this type of robot cell. | DHL Robomotive
At the center of the automated picking cell, which can be run 24/7, is a Yaskawa Motoman MH180-120 industrial robot and a Zivid One 3D color camera. The MH180-120, which is faster than a collaborative robot, usually has a blue color. But DHL ordered a custom version to match the company’s familiar yellow color. The robot has a reach of 3 meters and lifts up to 120 kg. DHL said that with one robot, four pallets and 25m pick front can be reached on a flow rack. At press time, the cell was able to achieve 400 picks per hour, which DHL hopes to increase to 600 picks per hour by further optimizing the robot cell. The key to this application, Robomotive said, is that the picking is done without the need for master data or prior learning of the product. Many times in the logistics industry, Robomotive said, CAD data does not exist for every item or it is inaccurate. Robomotive developed software to separate all types of products without needing prior information. “Deep learning companies say they need 1,000 examples to learn the product. We don’t need any learning.” said Michael Vermeer, CEO and founder of Robomotive. “We have standard geometrical approaches that can detect separate objects and pick them one by one.”
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The robotic system, which took about six months to get up and running after the purchase order in January 2018, scans the location at the time of picking and can identify individual boxes. Learning and master data are not necessary, allowing items to be exchanged easily and quickly. “Manual picking is labor intensive and physically strenuous and has a small chance of errors,” added Sebastiaan Bolt, Site manager of DHL Supply Chain. “This picking robot takes over this repetitive work so that our people can concentrate on more complex tasks. According to Robomotive, DHL’s robotic system has a payback period of about three years when it is used during regular day shifts. If it was used 24/7, however, the return on investment would be even quicker. “Without reprogramming, the items in the flow racks and on the pallets in the picking cell can be replaced by new top sellers, allowing us to respond even more quickly to changes in demand, for example as a result of sales promotions or consumer trends,” said Tjalling de Vries, Innovation lead of DHL Supply Chain.
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Cameras Imaging Vision System
DHL ordered a custom Yaskawa Motoman MH180-120 industrial robot to match its familiar yellow color. | DHL Robomotive 3D vision finding more homes Robomotive comes from the automotive world where it has integrated robots for 20-plus years. About seven years ago, Robomotive started adding 3D vision to industrial robots to make them more flexible like humans. “People have hand-eye coordination, which makes them more flexible,” Vermeer said. “We are trying to mimic that hand-eye coordination with 3D cameras to put robots in more places.” Robomotive has been running similar applications for some time, especially in production environments for bin picking. But DHL wanted a generic solution in a larger area of application in a traditional warehouse with flow racks and pallets. According to the companies involved in this project, it is DHL’s first fully automated e-commerce order picking robot cell. “We are only at the beginning of a far‐reaching robotization in our warehouses, with which we will bring our operations to the next level of efficiency and employee satisfaction,” said Mark Kruysen, Operations Excellence Director, DHL Supply Chain. “With this focus on innovation, we will be able to better serve our customers.”
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Robomotive has tested a lot of cameras, specifically evaluating how they performed with shiny parts, dark parts and in environments with poor lighting conditions. With the success of this project, DHL is now looking at new applications for this type of robot cell. “Every place you need material handling and to replace human hand-eye coordination, a robot with a 3D camera and gripper will be applicable,” said Vermeer. “There is a shortage of hands to do these materials handling jobs, so we are filling in that shortage.” Vermeer said the logistics industry has a lot to learn from the automotive world, where they have robots working for them 24/7. Fortunately for DHL, they have already started the process. RR
www.therobotreport.com
THE ROBOT REPORT
11/2/18 10:37 AM
Cognex Robotic Guidance Solution for UR Robots Cognex® has developed a URCaps™ solution with Universal Robots to guide users through communication and hand eye calibration with UR Robots. The solution is designed for Cognex In-Sight® 2D machine vision systems and leverages Cognex’s world class vision tools for any robot application. The system can be used to: ▪ GUIDE the robot to specific coordinates ▪ INSPECT the part after manipulation ▪ OUTPUT valuable data for downstream analysis
www.cognex.com/URCaps URCaps_Ad.indd 1 Cognex 11-18_Robotics Hbk.indd 43
10/24/2018 4:50:51 PM 11/2/18 10:35 AM
Cameras Imaging Vision System
6-DoF pose estimation trained on synthetic data
By Steve Crowe • Editor, The Robot Report
Knowing the 3D position and orientation of objects, often referred to as 6-DoF pose, is a key component to robots being able to manipulate objects that aren’t in the same place every time. NVIDIA researchers have developed a deep learning system, trained on synthetic data, that can do just that using one RGB camera. NVIDIA said its Deep Object Pose Estimation (DOPE) system, which was introduced at the Conference on Robot Learning (CoRL) in Zurich, Switzerland, is another step toward enabling robots to work effectively in complex environments. Read the paper “Deep Object Pose Estimation for Semantic Robotic Grasping of Household Objects” for more in-depth detail. Stan Birchfield, a Principal Research Scientist at NVIDIA, told The Robot Report that with NVIDIA’s algorithm and a single image, a robot can infer the 3D pose of an object for the purpose of grasping and manipulating it. Synthetic data has the advantage over real data in that it is possible to generate an almost unlimited amount of labeled training data for deep neural networks. “Real data needs to be annotated by hand. It’s very hard for a non-expert to label these images,” Birchfield said. “We’ve been looking at how to train networks with synthetic data only for some time.” One of the key challenges of synthetic data, NVIDIA said, is the ability to bridge the “reality gap” so that networks trained on synthetic data operate correctly with real-world data. NVIDIA said its one-shot deep neural network, albeit on a limited basis, has accomplished that. Using NVIDIA Tesla V100 GPUs on a DGX Station, with the cuDNN-accelerated PyTorch deep learning framework, the researchers trained a deep neural network on
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synthetic data generated by a custom plugin developed by NVIDIA for Unreal Engine, which is publicly available for other researchers. “Specifically, we use a combination of non-photorealistic domain randomized (DR) data and photorealistic data to leverage the strengths of both,” NVIDIA researchers wrote in their paper. “These two types of data complement one another, yielding results that are much better than those achieved by either alone. Synthetic data has an additional advantage in that it avoids overfitting to a particular dataset distribution, thus producing a network that is robust to lighting changes, camera variations, and backgrounds.” Testing NVIDIA’s system The system approaches its grasps in two steps. First, the deep neural network estimates belief maps of 2D keypoints of all the objects in the image coordinate system. Next, peaks from these belief maps are fed to a standard THE ROBOT REPORT
11/2/18 10:39 AM
A Baxter cobot with a Logitech C960 RGB Camera tested NVIDIA’s Deep Object Pose Estimation system. | NVDIA
perspective-n-point (PnP) algorithm to estimate the 6-DoF pose of each object instance. To put its pose estimation system to the test, NVIDIA attached a Logitech C960 RGB camera to the waist of a Baxter two-armed cobot from Rethink Robotics. The Logitech camera was calibrated to the robot base using a standard checkerboard target visible to both the Logitech camera as well as the wrist camera. The parallel jaw gripper moves from an opening of approximately 10 cm to 6 cm, or from 8 cm to 4 cm, depending on the thickness of the rubber tips installed. The researchers used five objects, placed among clutter, in four different locations on a table in front of the robot, in three different orientations at each location. The Baxter robot was instructed to move to a pre-grasp point above the object, then execute a top-down grasp, resulting in 12 trials per object. Of those 12 attempts, here is the number of successful grasps per object: 10 (cracker), 10 (meat), 11 (mustard), 11 (sugar), and 7 (soup). NVIDIA said the round shape of the soup can caused some issues with the top-down grasps. When the researchers repeated the experiment with the can of soup lying on its side, the number of successful grasps increased to 9 of 12 attempts. Rethink Robotics closed its doors on October 3. The IP has since been acquired by HAHN Group, a German automation specialist that will continue to manufacture and sell the Sawyer cobot. We asked Birchfield for his thoughts on the Baxter robot. THE ROBOT REPORT
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“As a researcher, we’ve been very happy with Baxter. It has a large amount of capability for the price,” said Birchfield. “Baxter doesn’t know the company went out of business. But our robotics lab has a variety of robots that will enable us to test different robots going forward.” Next steps for NVIDIA At press time, Birchfield said the system was only trained on those five objects. The researchers are working off the wellknown Yale-CMU-Berkeley (YCB) Object and Model Set, which consists of 77 everyday items. Birchfield said there is no limit to the number of objects the system can detect, but the researchers “took a subset that represents a variety of different sizes and shapes that are easily accessible for people to go to the store and try out.” Birchfield said this system will enable other robotics developers to get a jumpstart on their projects by solving a key part of the perception problem. “Robotics is such a multi-disciplinary field that researchers have a challenge in from of them because of time,” Birchfield said. “Often times with perception, folks will use AR tags to help solve that problem. Our technology will help them get one step closer to the real world without using AR tags.” NVIDIA said the next steps are to increase the number of detectable objects, handle symmetry and incorporate closedloop refinement to increase grasp success. RR
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THE ROBOT REPORT
11/2/18 10:40 AM
Sensors/Sensing Systems
US Army
algorithm locates robots
in GPS-denied environments Scientists at the U.S. Army Research Laboratory (ARL) have developed a novel algorithm that enables localization of humans and robots in areas where GPS is unavailable.
By The Robot Report Staff
According to ARL researchers Gunjan Verma and Dr. Fikadu Dagefu, the Army needs to be able to localize agents operating in physically complex, unknown and infrastructure-poor environments. “This capability is critical to help find dismounted Soldiers and for humans and robotic agents to team together effectively,” Verma said. “In most civilian applications, solutions such as GPS work well for this task, and help us, for example, navigate to a destination via our car.” However, noted the researchers, such solutions are not suitable for the military environment. “For example, an adversary may destroy the infrastructure (e.g., satellites) needed for GPS; alternatively, complex environments (e.g., inside a building) are hard for the GPS signal to penetrate,” Dagefu said. “This is because complex and cluttered environments impede the straight-line propagation of wireless signals.”
Dagefu said that obstacles inside the building, especially when their size is much larger than the wavelength of the wireless signal, weaken the power of the signal (attenuation) and re-direct its flow (called multipath), making a wireless signal very unreliable for communicating information about location. According to the researchers, typical approaches to localization, which use a wireless signal’s power or delay (i.e., how long it takes to reach a target from a source), work well in outdoor scenes with minimal obstacles; however, they perform poorly in obstacle-rich scenes. The team of ARL scientists including Dagefu and Verma developed a novel technique for determining the direction of arrival, or DoA, of a radio frequency signal
U.S. Army Research Laboratory scientists Dr. Fikadu Dagefu (left) and Gunjan Verma (right) pose with one of the robots used to validate a new algorithm they developed, which enables localization of humans and robots indoors or in areas with many obstacles where GPS signals are likely to be unavailable. | U.S. Army/Jhi Scott THE ROBOT REPORT
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VISION IN THE
3RD DIMENSION The modular and ultra-flexible Ensenso X 3D camera system for factory and logistics automation.
Sensors/Sensing Systems source, which is a fundamental enabler of localization. “The proposed technique is robust to multiple scattering effects, unlike existing methods such as those that rely on the phase or time of arrival of the signal to estimate the DoA,” Verma said. “This means even in the presence of occluders that scatter the signal in different directions before it is received by the receiver, the proposed approach can accurately estimate the direction of the source.” The underlying idea is that the gradient of the spatially sampled received signal strength, or RSS, carries information about the source direction. “Extracting the DoA requires a theoretically grounded analysis to obtain a robust estimator in the presence of undesirable propagation phenomena,” Verma said. “For example, large obstacles cause the RSS samples nearby to become highly correlated (so-called “correlated shadowing”). If left uncorrected, this correlation can seriously bias the DoA estimate.” The key invention according to the researchers is an algorithm that statistically models the RSS gradient and controls for spatial outliers and correlations. Importantly, when the signal is extremely noisy, the estimator correctly outputs that no DoA is present, rather than incorrectly estimating an arbitrary direction. The output is an estimated DoA and associated uncertainty. The researchers have validated the approach with several publicly available as well as in-house collected measurement datasets at 40MHz and 2.4GHz bands, as well as data from high fidelity simulations. The technique works in conditions of heavy multi-path in which classical phase or time of arrival based estimates would fail. In addition to not requiring any fixed infrastructure, the proposed technique also does not rely on any prior training data, knowledge about the environment, multiple antennas, or prior calibration between nodes. A journal paper documenting the research has been accepted for publication in the Institute of Electrical and Electronics Engineers Transactions on Vehicular Technology. RR
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11/7/18 8:09 AM
QUANTiC™
digital incremental encoder
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10/9/2018 11:50:22 AM 11/2/18 10:34 AM
Actuators/Motors/Servos
Solving real-time
robot motion control challenges Motion control is the software component of a robotic system that dictates how a robot should move to do tasks that have already been defined. Robot arms move through the action of
By James English president & CTO Energid Technologies
rotating and sliding joints, while mobile robots move through locomotion and steering. Robot tasks, on the other hand, are done with tools (end effectors) on the robot. Tasks may be manipulative, as when using a gripper, or they may be sensory, as when positioning a camera. These two concepts—movement and tasks—are key to addressing advanced applications for robotics. Tools do the work, but joints are controlled The heart of the motion control problem, as illustrated in Figure 1, is that tools do the work, but it is the joints that are controlled. And the relationship between the two is complex. An equation describing the placement of a probe held by a robot arm can take pages and pages of trigonometric functions. And this is the easy direction. Going the other way—calculating the control solution of how to place the joints to get a desired tool position—may not even have an equation. It may only be solvable iteratively.
Figure 1: The challenge in motion control is that the joints are controlled while the tool (or end effector) does the work, and the relationship between the two is complex. 50
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www.therobotreport.com
THE ROBOT REPORT
11/2/18 11:05 AM
Kollmorgen Motion Solutions
play a vital role in a variety of robotics, including collaborative, articulated industrial, surgical and mobile robotics. • High power density to reduce size, weight and complexity • Smooth, precise motion for control and safety • Broad range of size and power • Standard and optimized options to meet specialized requirements
Our expertise makes us a unique motion partner who understands the business and technical needs in robotics. Kollmorgen offers highly configurable products such as the AKM®2G servo motor, AKD®2G servo drive, KBM & TBM frameless motors, and stepper motors & drives. We also offer machine design and manufacturing expertise to optimize your process.
Find out more at www.kollmorgen.com/robotics ©2018 Kollmorgen Corporation. All rights reserved. KM_AD_000337_RevA_EN Specifications are subject to change without notice.
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Actuators/Motors/Servos
Figure 3: Energid’s Actin software controlling a Universal Robots UR5. On the left, sliders allow direct placement of joints. In the center, the robot is illustrated with mouse interaction for tool placement. On the right, collisions to be avoided are configured.
Figure 2: Some robots have more degrees of freedom than the minimum required to do a task. These kinematically redundant robots are powerful but can be hard to control.
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Some robots, like the one shown in Figure 2, have more actuators than the minimum needed for a task (such as grasping a screwdriver). This redundancy empowers a robot but complicates motion control. Think of the human body. With our extra joints, there are many ways to take that old pizza out of the refrigerator—an infinite number in fact—and exploiting the redundancy lets us reach around milk cartons, balance, and move smoothly to reduce joint stress and avoid joint limits. But this takes lots of brainpower. Robots with redundancy benefit from having the potential to move with the same smooth, efficient control, but it takes lots of processing power. Whenever there is more than one way to do something with a robot, the chosen way should have special qualities— maximizing distance from a collision, for example. A path can also improve strength, minimize time, avoid workspace limits, reduce power consumption, and improve accuracy. In practice, the best motion will usually be a combination of these—and other—pure qualities. Motion control must also incorporate constraints. Robot joints have speed and acceleration limits. Actuators have maximum torque or force. Physical parts of the robot cannot overlap in space, and joint limits cannot be exceeded. These are constraints imposed by the physical reality of the robot and the world. The desired tasks, constraints, and www.therobotreport.com
optimizations combine to make robot motion control a challenge. Complexity of control techniques requires real-time processing A variety of mathematical techniques, though, have been developed to address the challenge. Sometimes special-purpose equations are used, but an increasingly common technique is to use the so-called manipulator Jacobian. The Jacobian is a mathematical object that describes tool velocity as a function of joint velocity in a simplified way. It sidesteps the complicated direct calculation of positions. Because it has a simplified form, it is easier to invert to solve the control problem, the only drawback being that it works with velocities rather than positions. Positioning using the Jacobian requires algorithmic feedback techniques. Though the Jacobian can almost always be defined, calculated, and inverted for control, challenges remain. The first is how to select and integrate desired optimizations, both locally and globally. Global control relates to large movements with flexibility in the path so long as the endpoints are correct, while local control relates to precisely defined, usually small, movements. Many robot tasks are performed using a combination of global and local control, and how the optimizations are selected and implemented is an open area.
THE ROBOT REPORT
11/2/18 11:05 AM
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Actuators/Motors/Servos
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Whenever there is more than one way to do something with a robot, the chosen way should have special qualities—maximizing distance from a collision, for example. Managing higher derivatives is also an area for continued improvement, especially for online control. Many robots today generate full paths offline before motion starts. Offline path generation allows the use of the future states of the robot in calculations about earlier states. This helps in limiting the higher derivatives of motion (such as jerk, the derivative of acceleration) that can cause vibration. The drawback, though, is that knowledge is incomplete before motion begins, and once the robot starts on a pre-calculated path, it cannot respond to environmental and userinput changes. More work is needed to optimally control higher derivatives in real time. Playing into this challenge is the speed of calculation of the control algorithms. When applied in real time, speed is critical. A powerful algorithmic approach is to explore multiple alternatives—time step by time step— and choose the best. Faster implementations allow more alternatives and improved control. There is a chasm between algorithm existence on paper or in demonstration and its practical use because making an algorithm usable is itself difficult. Implementations must be robust. Even rare problems must be addressed. The implementation must accommodate inevitable deviations in the robot type, the environment, and tasks. And it must easily integrate with other software. Motion control for practical robotic systems Addressing these challenges today are multiple free, open-source and commercial software packages. Energid Technologies’ Actin, illustrated in Figure 3, is a commercial example. It controls arms in areas such as manufacturing, medical, and energy applications. A prominent example of the use of Actin is in bin picking, where one part at a time must be removed from a random pile of parts. Bin picking requires motion control that is fast and smooth while avoiding collisions with the bin holding the parts and with other parts in the bin. Advanced motion control enables robotic bin picking to be practical. RR
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www.therobotreport.com
THE ROBOT REPORT
11/2/18 11:06 AM
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10/3/18 11:08 3:15 AM PM 11/2/18
AI/Machine Learning/Deep Learning Software
‘No-code’interface simplifies
human-robot interaction Intelligent robot software called “The Wand” lets users tell robots what to do by using gesture and voice commands. Ease of use is a key factor in getting new industries and small and medium-sized companies to adopt automation. Robotics companies are doing a much better job keeping end users in mind when designing products, but for too long that was not the case. Fetch Robotics, Ready Robotics and Waypoint Robotics, among many others, come to mind as companies building their brands around ease of use.
By Steve Crowe • Editor, The Robot Report
Southie Autonomy, albeit lesser known, is another company worth watching. The Boston, Mass.-based startup and MassRobotics resident recently came out of stealth mode. Founded by two former Draper Laboratory employees in 2017, Southie is developing intelligent robot software called “The Wand” that lets users tell robots what to do by using gesture and voice commands. Southie claims no computer skills are required to be able to use The Wand. How The Wand Works The Wand uses a hand-held pointer and a patent-pending platform that combines artificial intelligence (AI) and augmented reality (AR) to remove the complex programming, which most companies that need automation lack inhouse, required to set up robotic workflows.
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THE ROBOT REPORT
11/2/18 11:11 AM
| phot
Part of the Southie Autonomy team (L to R): Summer intern Harish Sampathkumar, co-founder Rahul Chipalkatty, chief operating officer Barbara Finer and co-founder Jay Wong. | courtesy Southie Autonomy
The AR interface uses a projector, which is supplied to users, that displays a menu onto the workspace. In a pick-andplace demo The Robot Report watched, the user selected the “Pick” button on the AR interface and used The Wand to show the robot which object to pick up. The user then selected the “Place” button and tapped the desired location for the item to be placed. The final step is to hit the “Execute” button before the UR3 robot got to work. The Wand’s software comes preloaded with a workflow. Southie co-founder Rahul Chipalkatty says a robot that uses The Wand only has a general understanding of the task at hand. “In a kitting workflow, for example, the robot knows it needs to
THE ROBOT REPORT
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put something in a box in some sort of configuration. You show, with The Wand, where the set of objects is and where they need to go. That gives the robot its goal and constraints. Then, using AI, the robot reasons about how to complete the task, collision-free and precise to 0.5 cm placement. We generalize the task, and the robot figures out the rest.” Chipalkatty and co-founder Jay Wong published 3D vision papers while working at Draper that helped lead them down this path. “We wrap everything into a full-stack system,” Chipalkatty says. “Everything from the human-robot interface to task planning to motion planning and 3D perception is wrapped into a bundle that’s accessible to people.”
www.therobotreport.com
Target Market, Business Model Southie’s initial market focus is kitting as it is a large, growing market in which e-commerce and mass-customization are high-growth drivers. Some of the potential kitting applications its having conversations about include direct-toconsumer medical tests, pre-production custom kits for automotive, pre-packaged procedural trays for use in large hospitals, and personalized consumer packaged goods are examples. The system will be robot-agnostic and, in the future, will be able to carry out more sophisticated workflows. “In order to lower cost and skills requirements, which will lead to greater cobot adoption, both setup
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AI/Machine Learning/Deep Learning Software
A demo of Southie Autonomy’s The Wand performing a pick and place task. The robot is a UR3 with a Robotiq two-finger gripper. | courtesy Southie Autonomy
and infrastructure overhead need to be greatly reduced,” says Andie Zhang, Global Robotics Product Manager for Collaborative Robots, ABB. “Overall productivity will be improved for today’s forward thinkers when they implement flexible systems that involve humans and robots collaborating together.” The plan is to offer The Wand through an annual subscription model for $25,000 per robot. Chipalkatty says that will include vision/AR/AI hardware and pre-loaded workflow software for one application. “This model allows for customers to expand the suite of workflows and usecases to automate. We are targeting the total cost of the system (with cobot) at about $50,000, enabling one-year ROI.”
Southie is currently selling directly to customers. If all goes well, it will turn to systems integrators. How Southie Autonomy was Founded While working at Draper on mobile manipulation applications for the Department of Defense, Chipalkatty and Wong saw a gap in how people interact with robots. “People won’t use robots if they don’t fully understand them. One way to solve that gap is to create communication between the two. We call them autonomous, but no system is really
Company: Southie Autonomy Location: Boston, Mass. Founded: 2017 Affiliation: MassRobotics resident Full-time employees: 6 Funding Raised: $130,000 Product: The Wand intelligent robot software Cost: Annual $25K software subscription fee per robot Value Proposition: 1. Removes complex programming from robotic workflow; 2. Lowers cost of automating high-mix, low-volume applications First Target Market: Kitting
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www.therobotreport.com
autonomous. There’s always a person in charge, somewhere. If that person isn’t happy or satisfied with the performance, then they won’t use the robot.” Chipalkatty and Wong wanted to make robots smarter and easier to use. After impressing ABB with a prototype in August 2015, they were given a YuMi one year later. Chipalkatty left Draper in October 2017, and Wong came aboard full-time two months later. Southie currently has six full-time employees and has raised $130,000 from family, friends and startup competitions. “The value proposition is flexibility and simplicity. Typically a company needs a large volume of products to run through to justify the initial cost of a robot,” says Chipalkatty. “But if anyone can deploy a robot, and it only takes a few minutes to deploy it, now you can start hitting lower volume, smaller batch applications.” Southie believes in the technology acceptance model (TAM): utility and ease of use leads to ubiquity. Chipalkatty says all the key drivers for ubiquity are there for robotics, but what’s missing are ease of use and accessibility. “The interaction between humans and robots needs to be different,” says Chipalkatty. “You and I communicate tasks in a different way and do so efficiently by showing, touching and speaking. Robots can get there, too. And that will drive adoption, much like iOS did for iPhones.” RR
THE ROBOT REPORT
11/2/18 2:33 PM
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11/2/18 11:09 AM
Industrial Exoskeletons
Industrial Exoskeletons: new systems, improved technologies, increasing adoption
The market potential for industrial exoskeletons is enormous, as are the rewards for entrepreneurial solution providers that can aggressively innovate and come to market with solutions that deliver real business value. The exoskeleton sector continues to evolve, and in some sense has begun to ‘normalize’. The medical, business and technical press has long reported on exoskeleton technologies designed for medical rehabilitation and as mobility aids, even though commercial success and large-scale adoption has not yet been realized. Recently, however, reportage, along By Dan Kara VP, Robotics and Intelligent Systems
with focus of a number of medical exoskeleton suppliers, has shifted to a new exo market – industrial exoskeletons. Author’s Note: For this article, the meaning of the word ‘industrial’ has been expanded to include both the Industrial Sector and the Commercial Services Sector. Companies in the Industrial Sector derive their revenue by providing tangible goods, material, and products (i.e. manufacturing, construction, agriculture, mining etc.). The Commercial Services Sector is made up of companies that primarily derive revenue by providing intangible products and services (i.e. logistics, transportation, retail, healthcare, energy etc.). The reason for this swing is straightforward. Exoskeletons designed for supporting manual labor tasks in industrial environments are now commercially available and proving themselves in the field. Sizable companies are trialing systems, research is ongoing, and new enabling technologies specifically designed for the exo market have been recently introduced. Standards and regulatory issues related to the use of exo in industrial settings, while significant, are not nearly as expansive and complex as that of their medical counterparts, and acquisition is not dependent on insurance dollars or soft money sources such as grants. More importantly, the value proposition for the use of exos for industrial work is straightforward and ROI easily calculated (see Value Proposition, below).
Sarcos Robotics’ Guardian XO
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Wearable robots “Exoskeletons” is the collective name given to mechanical devices worn by workers, whose construction mirrors the structure of operator’s limbs, joints, and muscles, works in tandem with them, and is utilized as a capabilities amplifier, or as a fatigue and strain reducer. Body
www.therobotreport.com
THE ROBOT REPORT
11/5/18 3:21 PM
Esko Bionics’ WorkVest
weight support, lift assistance, load maintenance, positioning correction and body stabilization are common capabilities of industrial exo systems. It is useful to think of industrial exoskeletons as wearable robots that exploit the intelligence of human operators, and the strength and endurance of industrial robots. Like traditional robots, they address tasks, especially repetitive tasks that cannot be automated using traditional methods, that are physically demanding. In this sense, exoskeleton technology can be seen as a bridging solution between the extremes of fully manual work and those tasks that demand typical industrial robots. The wearable robotics market is still in its infancy, yet there already exists a number of companies offering compelling exo solutions. All of the products are worn by human operators, but the solutions themselves can differ considerably based on their intended use and supporting technologies. The diversity of currently available commercial exoskeleton solutions is also a reflection of the widely ranging backgrounds and core historical strengths of exoskeleton technologies suppliers. At the highest level, solutions can be distinguished according to their form factor, power requirements and construction material: Arms, upper and lower body – Exo systems come in many forms, including systems that attach at the hip and have weight carried by the exo through to the floor such as Lockheed Martin’s FORTIS THE ROBOT REPORT
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or Noonee’s Chairless Chair which lock in place and act as a seat when needed. Others, such as StrongArm Technologies’ FLx ErgoSkeleton, are upper body systems, while still others assist hands in gripping (Bioservo Technologies’ Ironhand, for example). Powered and unpowered – Most of the commercial exoskeleton solutions make use of some form of battery to power actuation and assistance, although non-traditional power solutions such as compressed air are used by some. Examples of commercial class powered exoskeletons include ATOUN’s Power Assist ARM, Innophys’ Muscle Suit, Cyberdyne’s HAL for Labor Support, RB3D’s HERCULE, Sarcos Robotics’ Guardian XO and Noonee’s Chairless Chair. In contrast to powered exoskeletons, unpowered or ‘passive’ exos increase strength and provide stability through a combination of human guided flexion/ extension and locking mechanisms. Unpowered exos for commercial and industrial use include Ottobock’s Paexo, Levitate Technologies’ AIRFRAME, suitX’s MAX Exoskeleton Suit, StrongArm Technologies’ FLx ErgoSkeleton, Laevo’s Laevo and Lockheed Martin’s Fortis. Rigid and soft - Rigid exos can produce musculoskeletal stress and fatigue due to their weight, as well as the unnatural or constrained movement of the suit. As a result, a number of companies are developing new types www.therobotreport.com
of soft exoskeletons made of soft, lightweight, compliant materials. The systems themselves are powered with soft muscle actuators or compressed air, or use flexion/extension mechanisms. Bioservo Technologies’ Ironhand and Daiya Industry’s Power Assist Glove serve as examples. In a manner to first generation exoskeleton systems, groups developing soft exo systems for military, and even consumer applications, such as Harvard University and Seismic, respectively, are sure to target the industrial sector at some point. Value proposition The business benefits of commercial/industrial exoskeletons are intuitively obvious and some easily quantified. They include increased efficiency and improved productivity. In some instances, exoskeletons can be used in place of industrial robots, eliminating the need for expensive, “full on” automation solutions. Exoskeletons also have the potential of allowing aging workers to continue to perform labor intensive tasks. Today, however, the primary
Hyundai’s Chairless Exoskeleton (H-CEX) November 2018
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Industrial Exoskeletons
maxon motor’s Exoskeleton Drive
Levitate Technologies’ AIRFRAME advantage given for using exoskeletons for industrial work, and the key driver for adoption, is to decrease the number of worker related injuries, and by doing so reducing healthcare and disability costs. Improving worker health has the tangential effect of reducing employee turnover, among other benefits. Adoption and testing Technological advancement in exoskeleton enabling technologies, along with increasing familiarity on the part of businesses with the potential of exos, have resulted in the increased use of exoskeleton technologies in industrial settings. At this time, the manufacturing sector, particularly automotive manufacturing, along with other industries requiring labor intensive work such as the logistics, retail and construction fields, are the leading adopters of exoskeleton technologies. In some cases the exo systems are purchased outright, while many suppliers allow systems to be leased or made available as a service. Adoption rates for exoskeletons can be difficult to quantify with a high degree of accuracy. As is common with other nascent technologies offering significant competitive advantage, reference customers are often unwilling to go public with their exoskeleton use cases. Recently, however, several large, international companies have come forward to openly describe their experiences with exoskeletons. Consider the following:
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Hyundai - In October 2018, Hyundai Motor Group announced they would begin testing their Hyundai Vest Exoskeleton (H-VEX), exo technology that reduces pressure on workers’ neck and back, at a North American Hyundai-KIA factory. This follows the start of trials at the same plant beginning in August 2017 of the Hyundai Chairless Exoskeleton (H-CEX), a knee joint sustainability device that maintains the sitting position of workers. According to Hyundai, both the H-CEX and H-VEX systems are designed to reduce injuries and increase worker efficiency. Ford – Following a pilot program begun in November 2017 with exoskeleton maker Ekso Bionics, Ford announced in August 2018 that the company would be introducing 75 of Ekso’s upper body exoskeletons across 15 automotive plants worldwide. Ford representatives have stated that use of the upper body exoskeletons, which assists employees performing overhead tasks, should reduce the number of repetitive motion injuries. BMW – The BMW assembly plant in South Carolina is currently employing Levitate Technologies’ AIRFRAME unpowered, upper body exoskeleton. The systems are also being trialed at other BMW plants. Levitate representatives claim the AIRFRAME exo lowers exertion levels by up to 80% for tasks involving repetitive arm motion. Lowe’s - In August 2017, Lowe’s Innovation Lab (LIL), the internal research branch of US$65 billion home improvement retailer Lowe’s, began trialing unpowered exoskeletons, ‘exosuits’ in Lowe’s parlance, at the company’s Christiansburg, VA store. The exosuits were developed conjointly by LIL and Virginia Tech’s Assistive Robotics Laboratory (ARL). The testing is being carried out by the Lowe’s stocking staff, who are using the exos for repeatedly lifting and moving heavy objects. Enabling technologies Advances in enabling technologies, especially for actuators, batteries and advanced materials are reducing the costs and increasing the functionality of industrial exoskeleton systems, with speedier and wider adoption the result. www.therobotreport.com
Much of the innovation is driven by technologies targeted to the robotics sector, including those areas where med tech and robotics intersect such as robotic rehabilitation and quality of life systems. Harmonic Drive’s lightweight, brushless FLA Rotary Acutators provides an example, as does the polymer bearings from igus which are used in unpowered exo from Levitate Technologies. The continuing need by the medical device and robotics markets for smaller, lighter and more capable enabling technologies is working in favor of those currently developing exoskeleton products. Providers of technologies used in robotics systems and medical devices have also brought to market component technologies targeted specifially to exoskeleton developers, or have pushed marketing that emphasizes the suitability of items in their existing product lines for use in wearable robots. For example, maxon motor recently introduced a compact, low weight “Exoskeleton Drive” joint actuation unit that consists of a brushless DC motor with inertia optimized rotor and high resolution encoders. Conclusion Decades of exoskeleton research, advancements in enabling technologies, and increased investment, coupled with an intuitive, easily demonstrated value proposition, has resulted in a growing industrial exoskeleton sector. Pilot projects and trials have given way to day-to-day work. New products continue to enter the market. Yet the industrial exoskeleton sector is still in its nascency, and the market opportunity is very large. For example, ABI Research finds that the current total addressable market (TAM) for industrial exoskeletons currently exceeds 2.6 million units. This figure dwarfs the number of systems that companies have brought to market, or will do so in the foreseeable future. The scope of the opportunity far exceeds even the most optimistic projections as to what suppliers can deliver. The conclusion is obvious: the market potential for industrial exoskeletons is enormous, as are the rewards for entrepreneurial solution providers that can aggressively innovate and come to market with workable solutions delivering business value. RR
THE ROBOT REPORT
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Mobile Robots - Mobile Platforms
5
challenges
when creating autonomous navigation systems
Variables impacting autonomous navigation are not limited to physical obstacles.
Increasing the level of navigation autonomy in mobile robots creates tangible business benefits to those companies employing them. But designing an autonomous navigation system is no easy task.
By Mike Santora • Associate Editor, Design World
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San Diego-based Brain Corporation seems to have figured it out, however. The company raised $114 million in mid-2017, led by the Softbank Vision Fund, to continue development of its BrainOS platform that allows robots to autonomously navigate using off-the-shelf hardware and sensors. Savioke recently announced it will integrate BrainOS into its commercial service robots. For years, Savioke built its autonomous navigation stack from scratch using ROS, but that will no longer be the case. “We want to focus on areas where Savioke can be unique, not on areas where we don’t have a competitive advantage,” Savioke founder and CEO Steve Cousins told The Robot Report. “Brain Corp. is doing some interesting stuff that is potentially game-changing in terms of the cost. They’re able to command volume pricing on sensors that we can’t. And they’re engineering things to fit together nicely.” Many robotics developers still want to develop their own autonomous navigation systems, which Brain Corp. understands. To educate robotics developers about the challenges encountered when designing an
www.therobotreport.com
THE ROBOT REPORT
11/2/18 11:02 AM
Brain Corporation’s BrainOS transforms everyday machines into autonomous solutions. autonomous navigation system, Brain Corp director of innovation Paul Behnke and VP of innovation Phil Duffy shared their insights in a webinar titled “Robotics: The Decathlon of Startups.”
that handles these issues with the end-user in mind. The robot must still involve minimal training for operators, no environmental setup, single-shot learning by demonstration, and productivity reporting.
1 Getting the software right “That’s definitely the first problem that comes to mind when you’re thinking about developing robotics for new environments,” Behnke said. Getting the software right is especially challenging for robots that will be autonomously navigating in dynamic environments such as airports, malls, warehouses and other high-traffic workspaces. These areas often have tight spaces and continuously changing obstacles that require complex routes. The challenge is writing software
2 Gathering enough real-world data Variables that impact autonomous navigation are not limited to physical obstacles crowding a robot’s work environment. Feature-less environments, and even time of day, add complexity to autonomous navigation. Many of these types of hurdles are edge cases that do not present themselves until after software has been developed and the robots are tested in a live environment. Edge cases are the punch you don’t see coming. Behnke uses this example: “Being able to navigate in a cluttered, dynamic environment with a lot of people moving around sounds difficult. But, an open gymnasium in a university is just as difficult because there’s a lack of
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Mobile Robots - Mobile Platforms A Savioke Relay robot autonomously navigates a FedEx repair center in Tennessee. | Savioke/FedEx
features. There’s nothing, really, to anchor or tie into when you’re building your map.” Success is contingent upon getting your robot, and the software that runs it, into many different environments early on. Functional autonomous navigation systems are not developed in a lab. Duffy said it’s fine to begin development there to create a demo, or to get funding. But those stages are the limit for a lab environment. “Commercially, it won’t work until you’ve been in a number of scenarios because the problems that you’re going to experience in the wild cannot be replicated in a lab.” You can’t solve or anticipate every edge case your robot will encounter in the real world. Keeping your customer’s employees involved in the installation process and giving them the tools to troubleshoot issues in real-time can improve your robot’s efficiency. Duffy further used examples like a robot mistaking light from a reflective surface as a physical object or infrared heaters disrupting the robot’s path. Essentially, the more edge cases you can solve, the better your navigation solution. Data is king. 3 Creating precision motion control Duffy says the real key to designing a robot with autonomous navigation is creating a system that has precise and accurate motion control. “For a lot of robots, you’re just taking a robot from point A to point B. With Brain Corporation, our initial market launch was these industrial floor care machines, and they need to drive as close THE ROBOT REPORT
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to an edge, as close to a wall, as close to an obstacle as possible to maximize the amount of floor cleaning we provide.” Highly accurate motion control is imperative if you want your robot to be able to handle complex, tight spaces. That’s something you can’t do with a robot that has much larger footprint. Designing a system that is as tight and accurate as possible give you much better capabilities to navigate complex spaces. 4 Reducing false positives Human detection is crucial for expanding end-user applications. If your robot can’t tell a person from a package on the floor, you’ve hamstrung your business before it starts. “If you’re developing your own algorithms, if you are looking for navigation systems to use in your robotics project, then having a system that can recognize humans different to obstacles is essential. Unless you’re going to clear everybody out in the environment the robot works in, which limits the applications, you really need to solve the human element. This is one of the biggest problems you’ll solve,” Duffy said. Being overly cautious, however, also has its problems. Behnke mentions that when Brain Corp ran some initial pilot tests with its floor cleaning machine, the robots were checking, pausing, and analyzing for the sake of safety so often it made humans less comfortable around them. People thought the robots weren’t intelligent, thus making them feel uncomfortable around the robots. It’s critical that you use sensor data from real-world scenarios and virtual environments to reduce false positives. www.therobotreport.com
5 Installation must be simple For your robot to be genuinely scalable, the installation process must be simple, not technical. Many of today’s robots require an engineer for installation into a new environment. The process is simply beyond the skillset of non-technical staff. This indepth and technically complex launch can bottleneck this critical early stage; having an engineer sent on-site to every new customer is not sustainable or scalable. One way to counteract this challenge is to have your customers identify employees who might be capable of taking on installation as a new project. Another is to do some preventative maintenance regarding design. You want your robot to be aesthetically familiar to products your customer’s employees have used before. Make sure the user interface is lean and intuitive. Behnke uses the following example: “We wanted to keep it as simple as possible… As you can see in this screenshot right here, there are only two choices for the user: Choose a route or teach a route.” “And that’s the secret to dealing with non-technical employees that are using these machines. We’ve designed a system that is very easy to use. The user either uses the machine the way they always have and while they are doing that, it creates a map of the space and records the routes, or they set to play.” RR Author Bio: Mike Santora is an Associate Editor for Design World, a sister publication of The Robot Report. He holds a B.A. in Journalism from Bowling Green State University and an MFA in Creative Writing from the University of New Hampshire.
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Mobile Robots - Mobile Platforms
AGVs vs. AMRs:
How to best automate material transport In today’s competitive business environment, companies worldwide continue to look to automation to adapt to fast-changing market demands, optimize productivity and stay ahead of the competition. However, automating material transportation has been a challenge, leaving workers to push carts loaded with materials from one side of a warehouse to another, which can result in production backlogs and idle workers as they wait for assemblies and parts to be delivered. Until recently, traditional automated guided vehicles (AGVs) were the only option for automating internal transportation tasks. AGVs move materials using fixed routes that are guided by permanent wires, magnetic strips, or sensors embedded in the plant floor. These systems, however, are expensive, inflexible, and disruptive for dynamic manufacturing floors. If a company’s processes change, the By Ed Mullen facility must be updated again - and if people or material VP of Sales, Americas temporarily blocks the AGV’s route, it simply stops until the MiR way is cleared. AGVs are now being challenged by more sophisticated, flexible and cost-effective technology: autonomous mobile robots (AMRs). With new sensor and software technologies, these AMRs are ideal for unpredictable or changing production layouts and dynamic work environments. AMRs provide the flexibility, safety, and cost-effectiveness that enable companies of nearly any size to automate and optimize material handling. AMRs vs. AGVs An AMR navigates via sensors, cameras, and sophisticated software built into the robot, without needing external sensors or guides. Once the robot has learned its surroundings by uploading a facility blueprint or by piloting
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the robot around the plant to develop its own map, the robot recognizes its surroundings and can autonomously take the most efficient route to its destination, avoiding obstacles and people. Since companies do not need to alter their facility with wires or sensors, the robot can be integrated within hours with no disruption to production. The AMRs’ autonomous operation also makes them far more flexible than an AGV, which are limited to following a strict route (typically installed in the floor). This means applications are limited, with an AGV performing the same delivery task throughout its service life. On the other hand, AMRs only need simple software adjustments to change their missions. This means the same AMR can perform different tasks in different locations, automatically adjusting to meet changing environments and production requirements. The tasks can be controlled via the robot’s interface or configured by fleet control software for multiple robots THE ROBOT REPORT
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Metro Plastics uses an AMR from MiR to automate the transport of finished goods to quality assurance while jobs are in process. | MiR that automatically prioritize orders and determine the robot that is bestsuited for a given task. Once a mission is determined, employees can focus on high-value work that contributes to company success, not on controlling the robot. The AMRs’ flexibility is crucial for environments that require agility and flexibility if there is a need for modifications to products or the production line. AMRs are highly adaptable for agile production in any size facility. If production cells are moved or new cells or processes are added, a new map of the building can be quickly and easily uploaded or the AMR can re-map onsite, so it can be used immediately for new tasks. This capability gives organizations – like Indianapolis-based injection molding company Metro Plastics – full ownership of the robot and its functions, rather than being constrained by an inflexible AGV infrastructure. Case study: Metro Plastics improves quality, competitiveness Since 1974, Metro Plastics has produced custom plastic injection molded parts and inject mold tooling. In its constant search for more efficient ways to do business to deal with increasing competition and rising costs, Metro Plastics automates anything it can. After researching AGVs for a new building – and determining the cost and impact of implementation was too prohibitive - the company recently implemented an AMR to automate the transport of finished goods to quality assurance while jobs are in process. This has enabled the company to immediately identify and address quality issues, which helps reduce waste and drive competitiveness. According to Metro Plastics President Ken Hahn, the AMR “didn’t need any wires in the concrete. It didn’t need magnet pills or anything else to guide it. It was autonomous, and it was basically about half the cost of the other solutions. It was a no-brainer for us to get it.” With as many as 20 jobs running at a time, boxes of finished products used to stack up at each press until a quality inspector could inspect parts and have them delivered to the warehouse. During busy periods, THE ROBOT REPORT
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boxes and pallets were tripping hazards for workers, and the constant fork truck traffic added to the safety risks. For press operators and quality inspectors, the ergonomics of examining and moving boxes at floor level added to job stress. Metro Plastics initially set up an AMR to loop the production floor, stopping at each press for 30 seconds to allow operators to load finished products as soon as they fill a box. The robot then continues to the quality department in the warehouse, where it automatically docks at its charging station until its next round through the production floor. The robot runs around the clock, Monday through Friday, for four six-hour shifts a day. Hahn notes that product quality improvement is an unexpected benefit of the mobile robot. By delivering products continuously, quality inspectors are able to inspect every box, not just a sampling. If a problem is found, it can be identified and addressed while the parts are being produced, which helps reduce waste. According to Hahn, with the AMRs, he no longer needs to worry about the safety of workers moving around the floor listening to music or looking at their phones while fork trucks drive around pallets and boxes. The collaborative robot senses and automatically maneuvers around obstacles and workers, and has nearly eliminated fork truck traffic, making the production floor safer and cleaner. As companies like Metro Plastics have seen, depending on costly, inflexible technologies isn’t going to help them be competitive, nor can they can continue the unproductive manual transportation of materials. Ultimately, AMRs offer an agile alternative to AGVs, manual delivery or fork lifts, in the case of Metro Plastics, providing flexibility, cost-effectiveness, return on investment, and productivity optimization. RR
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Searching for better
battery power
By The Robot Report Staff
As with any electronic system, power and energy sources represent one of the most challenging areas of robotics research and deployment, especially for mobile robotics. The increasing adoption of drones and autonomous vehicles is fueling the development of new battery technologies that are safe and affordable, with longer cycle lives, robust temperature tolerance, higher energy densities, and relatively low weight. Over the past three decades, lithium-ion batteries, rechargeable batteries that move lithium ions back and forth to charge and discharge, have enabled smaller robots to juice up faster and last longer. X-ray experiments at the Department of Energy’s SLAC National Accelerator Laboratory and Lawrence Berkeley National Laboratory have revealed that the pathways lithium ions take through a common battery material are more complex than previously thought. The results correct more than two decades worth of assumptions about the material and will help improve battery design, potentially leading to a new generation of lithium-ion batteries.
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Battery/Power Solutions When lithium ions flow into the battery’s solid electrode – illustrated here in hexagonal slices – the lithium can rearrange itself, causing the ions to clump together into hot spots that end up shortening the battery lifetime. | Stanford University
An international team of researchers, led by William Chueh, a faculty scientist at SLAC’s Stanford Institute for Materials & Energy Sciences and a Stanford materials science professor, recently published these findings. “Before, it was kind of like a black box,” said Martin Bazant, a professor at the Massachusetts Institute of Technology and another leader of the study. “You could see that the material worked pretty well and certain additives seemed to help, but you couldn’t tell exactly where the lithium ions go in every step of the process. You could only try to develop a theory and work backwards from measurements. With new instruments and measurement techniques, we’re starting to have a more rigorous scientific understanding of how these things actually work.”
failure,” Chueh said. “If lithium can be made to move more slowly on the surface, it will make the battery much more uniform. This is the key to developing higher performance and longer lasting batteries.”
The ‘popcorn effect’ Better understanding of lithium iron phosphate, and other materials like it, could lead to faster-charging, longer-lasting and more durable batteries. But until recently, researchers could only guess at the mechanisms that allow it to work. When lithium-ion batteries charge and discharge, the lithium ions flow from a liquid solution into a solid reservoir. But once in the solid, the lithium can rearrange itself, sometimes causing the lithium iron phosphate to split into two distinct phases, much as oil and water separate when mixed together. This causes what Chueh refers to as a “popcorn effect.” The ions clump together into hot spots that end up shortening the battery lifetime. In this study, researchers used two X-ray techniques to explore the inner workings of lithium-ion batteries. At SLAC’s Stanford Synchrotron Radiation Lightsource (SSRL) they bounced X-rays off a sample of lithium iron phosphate to reveal its atomic and electronic structure, giving them a sense of how the lithium ions were moving about in the material. At Berkeley Lab’s Advanced Light Source (ALS), they used X-ray microscopy to magnify the process, allowing them to map how the concentration of lithium changes over time.
A new frontier in battery engineering Even though lithium iron phosphate has been around for the past two decades, the ability to study it at the nanoscale and during battery operation wasn’t possible until just a couple of years ago. “This explains how such a crucial property of the material has gone unnoticed for so long,” said Yiyang Li, who led the experimental work as a graduate student and postdoctoral fellow at Stanford and SLAC. “With new technologies, there are always new and interesting properties to be discovered about materials that make you think about them a little differently.” This work is one of the first papers to come out of a collaboration between Bazant, Chueh and several other scientists as part of a Toyota Research Institute-funded research center that utilizes theory and machine learning to design and interpret advanced experiments. These most recent findings, Bazant said, create a more complex story that theorists and engineers are going to have to consider in future work. “It further builds the argument that engineering the surfaces of lithium-ion batteries is really the new frontier,” he said. “We have already discovered and developed some of the best bulk materials. And we’ve seen that lithiumion batteries are still progressing at a pretty remarkable pace: They keep getting better and better. This research is enabling the steady advancement of a tried technology that actually works. We’re building on an important bit of knowledge that can be added to the toolkit of battery engineers as they try to develop better materials.”
Swimming upstream Previously, researchers thought that lithium iron phosphate was a one-dimensional conductor, meaning lithium ions are only able to travel in one direction through the bulk of the material, like salmon swimming upstream. But while sifting through their data, the researchers noticed that lithium was moving in a completely different direction on the surface of the material than one would expect based on previous models. It was as if someone had tossed a leaf onto the surface of the stream and discovered that the water was flowing in a completely different direction than the swimming salmon. They worked with Saiful Islam, a chemistry professor at the University of Bath, UK, to develop computer models and simulations of the system. Those revealed that lithium ions moved in two additional directions on the surface of the material, making lithium iron phosphate a three-dimensional conductor. “As it turns out, these extra pathways are problematic for the material, promoting the popcorn-like behavior that leads to its
Spanning different scales To follow up on this study, the researchers will continue to combine modeling, simulation and experiments to try to understand fundamental questions about battery performance at many different length and time scales with facilities such as SLAC’s Linac Coherent Light Source, or LCLS, where researchers will be able to probe single ionic hops that happen at timescales as fast as one trillionth of a second. “One of the roadblocks to developing lithium-ion battery technologies is the huge span of length and time scales involved,” Chueh said. “Key processes can happen in a split second or over many years. The path forward requires mapping these processes at lengths that go from meters all the way down to the motion of atoms. At SLAC, we’re studying battery materials at all of these scales. Combining that with modeling and experiment is really what made this understanding possible.” RR
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ADVANCED TECHNOLOGY PRODUCTS ATP is a premium manufacturer headquartered in Milford Center, Ohio. Established in 1990, ATP began as a joint venture between a Japanese tubing manufacturer and an American distribution company. The original focus was the manufacture of polyurethane spiral recoil hoses and the distribution of imported Japanese trade items. Since then, ATP has grown to manufacture and distribute plastic tubing, weld spatter tubing, hose, push-to-connect fittings, clamps, and other industrial accessories. ATP has also expanded its footprint with several expansions and acquisitions in Milford Center and Mechanicsburg, Ohio, as well as Murfreesboro, Tennessee. Advanced Technology Products 12740 State Route 4 Milford Center, OH 43045 Phone: 937-349-4055 Email: info@atp4pneumatics.com Web: www.atp4pneumatics.com
Bal Seal® for improved robot performance Low friction Bal Seal® spring-energized seals provide superior protection against leakage and contamination in arms, drives, end effectors and other critical industrial robot parts. The seals eliminate stick-slip and promote consistent, accurate movement/placement. Seal jackets can be made from Bal Seal Engineering’s SP191, a polyimide-filled PTFE compound which exhibits minimal wear in rotary and reciprocating sealing service. The SP191 material contains ingredients that meet FDA regulation 21 CFR 170.39 for use in food contact applications. It is suggested for use in temperatures ranging from -400 °F to 550 °F, and its low friction properties make it ideal for use in stop-start applications.
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Bal Seal Engineering, Inc. 19650 Pauling Foothill Ranch, CA 92610 949.460.2100 or 800.366.1006 www.balseal.com sales@balseal.com
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Robotics Robotics
BIMBA Bimba, a part of IMI Precision Engineering, is a forward-thinking innovator providing industry-leading pneumatic, hydraulic, and electric motion solutions that are easy to use, reliable and ready for all engineering solutions. Bimba markets an extensive line of industry-leading products including pneumatic, hydraulic, and electric actuators; valves; fittings; vacuum products; air preparation and a variety of safety and production solutions. In addition to its broad line of standard catalog products, the company’s business develops many custom and semi-custom products designed for specific customers and applications. These products, used in machinery and automation, are sold to original equipment manufacturers and end-users throughout the world in an expanding variety of industries.
University Park Headquarters 25150 S. Governors Hwy University Park, IL 60484 Phone: 708-534-8544 Tech Support: 800-44-BIMBA www.bimba.com
CIRTRONICS You come first Depending on your needs, we build, ship, test and provide aftermarket support. When appropriate, our engineering teams can collaborate during the design process. Collaboration enables seamless transition to manufacturing through design reviews to ensure part sourcing, efficient assembly and effective testing. We have the experience and expertise to support the entire manufacturing process, from DFx reviews, supply chain optimization and risk management, to manufacturing and assembly of circuit boards, sub-assemblies, and final systems. We manufacture robots that serve a wide range of markets, including military, defense and first responders, virtual presence, medical and surgical. Each customer and each project has its own unique requirements, and we’ll tailor our services to you. We’re ITAR and FDA Registered, ISO 9001 and 13485 Certified, and a Woman Owned Small Business. Are you ready to choose a contract manufacturing partner? We’ll make it easy. Promise.
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Cirtronics Corporation 528 Route 13 South Milford, NH 03055 603 249 9190 www.cirtronics.com info@cirtronics.com
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FESTO Corporation Ready-to-Install 2D and 3D Cartesian Handling Systems Festo offers a range of Cartesian handling systems to fit the needs of your assembly and material handling operations. An economic and energyefficient alternative to conventional 4- to 6-axis industrial robots, you can easily adapt Festo’s 2D and 3D systems to linear and rotational applications. Each system is ready to install and comes with a matching motor and controller. Choose from: • Single-axis systems, which feature a 3,000-mm stroke and include an energy chain for cable and hose routing. • 2D linear gantries for two-dimensional vertical movements. This system boasts high dynamic response and short cycle times. • 2D planar surface gantries for two-dimensional horizontal movements. This option can handle larger work spaces and loads up to 6 kg. • 3D gantries for three-dimensional movement. Suitable for heavy loads, this system combines three horizontal gantry axes and a vertical axis.
Phone: 631.435.0800 Web: www.festo.com E-mail: customer.service.us@festo.com
Harmonic Drive Customizable supermini actuator Small enough to fit inside the finger of a robotic hand, these ultra-compact servo actuators utilize zero backlash Harmonic Drive® precision gears, a brushless servo motor and an incremental encoder. RSF supermini actuators are available in 2 sizes with ratios 30:1, 50:1 and 100:1. Peak torque .13~1.4 Nm, max speed 100~333 rpm. RSF Supermini actuators are remarkably reliable. Known for our expert engineering and manufacturing, Harmonic Drive® products are relied upon every day throughout the robotics industry. 247 Lynnfield Street Peabody, MA 01960 United States www.harmonicdrive.net
Harmonic Drive is a registered trademark of Harmonic Drive Systems
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Festo Corporation 1377 Motor Pkwy. Ste 310 Suffolk County Islandia, NY 11749
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Robotics Robotics
Honeywell Intelligrated Advanced robotics for the DC Unmatched integration experience and domain expertise uniquely position Honeywell Intelligrated to bring the benefits of smart robotics to your distribution center. From sorter induction to loading and unloading, Honeywell Robotics has a broad portfolio of patented robotic innovations and constantly develops new solutions. The Honeywell Universal Robotic Control (HURC) unleashes the power of artificial intelligence and the latest robotic controls software to enable new applications and continuous optimization. The highperformance platform enables machine learning across applications, enabling faster perception and more effective action. This allows Honeywell Intelligrated to provide meaningful performance advantages and
www.intelligrated.com 1.866.936.7300 info@intelligrated.com
reduce operator interventions.
Kollmorgen Kollmorgen TBM™ Offers Optimal Performance in a Compact Package As new applications for robots continue to emerge the market for high power density motors also grows. Kollmorgen’s TBM series of Direct Drive Frameless motors offer the flexibility to help you push the limits of what’s possible by working seamlessly within your design. Kollmorgen TBM series of Direct Drive Frameless motors are designed to be directly embedded into machines, using the machine’s own bearings to support the rotor. TBM technology is optimized for applications that require high power in a small, compact package with minimal weight and inertia. Additional features include: • Efficient electromagnet design leads to lower temperature rise • Low voltage design is optimized for applications up to 48 VDC • High quality materials ensure a long service life
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Honeywell Intelligrated 7901 Innovation Way Mason, Ohio 45040
Want to learn more about Kollmorgen TBM frameless motors? Contact info: Gene Matthews Kollmorgen 203A West Rock Road Radford, VA 24141 Phone: 1.540.633.3545 Email: www.kollmorgen.com
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LAPP LAPP SKINTOP® Cable Glands Enable Safest Cleaning Possible Ideal for applications that require hygienic operation, LAPP’s SKINTOP® HYGIENIC and INOX series of edge-free, stainless steel cable glands include special design features that prevent microorganisms and bacteria from sticking to the surface— preventing contamination and enabling safe, easy cleaning. SKINTOP® HYGIENIC • Certified to NSF/ANSI 169 • Stainless steel with FDA-approved sealing material • Protection ratings: IP68 & IP69 • Temperature range: -20 to +100°C • Wide clamping range • Available with NPT and metric threads SKINTOP® INOX • Certified to NSF/ANSI 169 • Highly corrosion-resistant stainless steel • Protection ratings: IP68 & IP69 • Temperature range: -40 to +100°C • Wide clamping range • Available with NPT and metric threads
Toll Free: 1-800-774-3539 Tel: 973-660-9700 Fax: 973-660-9330 www.lappusa.com Email: sales(at)lappusa.com
maxon precision motors Drive Systems for Robotics Reliable, Powerful, Efficient A complete joint actuation unit. Includes a brushless DC motor, an internal high resolution encoder, planetary gearhead with absolute encoder and position controller with CAN and RS232 interface. Exoskeleton Joint Actuator • Compact Housing • Integrated Controller • Reduced Weight and Cost • For Use in Hip and Knee Exoskeletons maxon is your single source for motion solutions. When you choose maxon, you can expect outstanding service, creative options and quality without question. Want to get your ideas moving? Contact maxon today. Learn more about the maxon solutions and visit www.maxonmotorusa.com
November 2018 www.therobotreport.com
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Corporate Headquarters 29 Hanover Road Florham Park, NJ 07932
maxon precision motors, inc. 101 Waldron Road Fall River, MA 02720 Phone: 508.677.0520 www.maxonmotorusa.com info@maxonmotorusa.com
THE ROBOT REPORT
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Robotics Robotics
New England Wire Technologies Advancing innovation for over 100 years Why accept a standard product for your custom application? NEWT is committed to being the premier manufacturer of choice for customers requiring specialty wire, cable and extruded tubing to meet existing and emerging worldwide markets. Our custom products and solutions are not only engineered to the exacting specifications of our customers, but designed to perform under the harsh conditions of today’s advanced manufacturing processes. Cables we specialize in are LITZ, multi-conductor cables, hybrid configurations, coaxial, twin axial, miniature and micro-miniature coaxial cables, ultra flexible, high flex life, low/high temperature cables, braids, and a variety of proprietary cable designs. Contact us today and let us help you dream beyond today’s technology and achieve the impossible.
NEW ENGLAND WIRE T E C H N O LO G I E S
New England Wire Technologies www.newenglandwire.com 603.838.6624
NSK Precision For Maintenance Free Operation Choose NSK K1TM Lubrication Unit NSK’s K1TM is a uniquely designed system that not only lubricates but also helps minimize contamination. K1 material composition consists of 70% mineral
oil
and 30% polyolefin resin which ensures long-term, maintenancefree operation even under tough lubrication environments. K1TM offers no maintenance for up to 5 years or 10,000 km operational distance. K1 is ideal for environments where the lubricant is hard to replace or is easily washed away. Available in ball screws, linear guides, monocarriers and tough carriers.
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Contact info:
NSK Americas www.nskamericas.com
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Posital-Fraba Upgrade Your Motor Feedback with POSITAL Absolute Kit Encoders POSITAL absolute Kit Encoders offer a great upgrade path for the traditional incremental kit encoders used for servomotors. Compact, rugged and cost effective, they provide accurate position feedback for precision motion control in robots, production machinery, autonomous vehicles and other motion and position control application. They can also be used to provide closed-loop feedback control for stepper motors. Rotational resolution is up to 17-bit (one part in 130,000) with a multi-turn range of
POSITAL-FRABA Inc.
more than 8 million revolutions.
1800 East State Street, Suite 148 Hamilton, NJ 08609
Standardized compact form factors make POSITAL absolute kit encoder a straightforward replacement for US Digital or Broadcom incremental kit encoders in existing machinery or in new designs.
Website: www.posital.com Email: info@fraba.com Phone: +1 609.750.8705
QUANTICTM Encoder series The QUANTiC encoder system integrates Renishaw’s filtering optics design and interpolation technology to create a high performance, super-compact, digital all-in-one incremental open optical encoder. QUANTiC encoders are easy to install with exceptionally wide installation and running tolerances, along with builtin installation and calibration functions. More detailed diagnostic information can be accessed by using the Advanced Diagnostic Tool ADTi‑100 and ADT View software during installation or for in-field diagnostics and fault finding.
November 2018 www.therobotreport.com
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USA
Website: www.renishaw.com Email: usa@renishaw.com Phone: (847) 286-9953 Address: 1001 Wesemann Drive West Dundee, IL 60118 USA
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Robotics Robotics
Schneider Electric Motion Absolute MDrive A multi-turn absolute encoder feature is available integrated with all-in-one motor and electronics Lexium MDrive products. Without increasing product size, rotary and linear stepper motors with integrated electronics deliver multi-turn absolute encoder benefits in a compact size and at an extremely competitive price. Saving time, money and energy, MDrive intelligent motors are in motion globally in a wide range of industries and applications. Delivering reliable and cost-effective closed-loop performance for EtherNet/IP, Profinet, ModbusTCP, RS-422/485 and CANopen systems.
Tel: 860-295-6102 Email: info@imshome.com www.motion.schneider-electric.com
Universal Robots Universal Robots has reinvented industrial robotics with the lightweight and flexible UR 5e and UR10e robot arms. The Danish-designed robots automate production in all industries – even in SMBs that regard automation as costly, cumbersome, and difficult to integrate. The robots can work alongside personnel and are easily moved around production sites to complete even the most detailed tasks. Programming is intuitive, eliminating the need for skilled programmers; simply Contact info:
grab the robot arm to show it the desired movement, or use the simple touch screen. The robots are sold in over 50 countries worldwide, typical ROI is 3 – 8 months.
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Schneider Electric Motion 370 N. Main Street Marlborough, CT 06447
Universal Robots USA, Inc. 5430 Data Court, Suite 300 Ann Arbor, Michigan 48108 United States Phone: +1 844.462.6268 Email: ur.na@universal-robots.com
www.therobotreport.com
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AD INDEX
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New England Tubing Technologies ..................... 63
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NSK Precision ..................................................................... 31 Renishaw ............................................................................ 49 Rotor Clip ............................................................................IBC Schneider Electric Motion USA ......................................7 Universal Robots USA Inc. ........................................... IFC
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