In 2016, the European Union co-funded 17 new robotics projects from the Horizon 2020 Framework Programme for research and innovation. 16 of these resulted from the robotics work programme, and 1 project resulted from the Societal Challenges part of Horizon 2020. The robotics work programme implements the robotics strategy developed by SPARC, the Public-Private Partnership for Robotics in Europe (see the Strategic Research Agenda).
EuRobotics regularly publishes video interviews with projects, so that you can find out more about their activities. You can also see many of these projects at the upcoming European Robotics Forum (ERF) in Tampere Finland March 13-15.
This week features RobMoSys : Composable Models and Software for Robotic Systems.
Objectives
RobMoSys will coordinate the whole community’s best and consorted efforts to realize a step-change towards an industry-grade software development ecosystem.
RobMoSys envisions a model-driven integration approach built around the current code-centric robotic platforms.
RobMoSys intends to establish software quality enabling model and software composability and improved tool support.
RobMoSys will elaborate a common open methodology for software development based on broad involvement of the robotic and software community via Open Calls.
Expected Impact
The major expected impacts of the project are:
Impacts are expected in both the global software and system modelling tool market and in robotic related market domains.
Partners
COMMISSARIAT A L’ENERGIE ATOMIQUE ET AUX ENERGIES ALTERNATIVES
FACHHOCHSCHULE ULM
KATHOLIEKE UNIVERSITEIT LEUVEN
TECHNISCHE UNIVERSITAET MUENCHEN
SIEMENS AKTIENGESELLSCHAFT
PAL ROBOTICS SL
COMAU SPA
ECLIPSE FOUNDATION EUROPE GMBH
EUNITED AISBL
Coordinator:
Coordinator: Sara Tucci
sara.tucci@cea.fr
Project website: robmosys.eu
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In this episode of Robots in Depth, Per Sjöborg speaks with Daniel Pizzata about how his passion for modular robotics led him to start Modbot, a company building robotics platforms. The goal of Modbot is to bring robots out of the research labs and make them accessible to everyone.
Daniel started out in the defence sector in Australia using robotics to measure radio transmissions. He worked on many different projects, but felt that he wanted to work with technology that was more widely applicable in society.
Daniel also talks about how he met his co-founder Adam Ellison and how they had the idea of a platform and a community that could widen the range of people that are able to develop robotics and automation solutions. This turned out to be a life-changing journey with many intense moments and amazing experiences.
Daniel then shares how living on floor 7½ in the mezzanine corridor was one of the interesting aspects of moving to San Fransisco to pursue his dream of starting Modbot.
I have created a gallery in Google Photos with some of the more interesting items I saw at CES, with the bulk of them being related to robocars, robotic delivery and transportation.
Click on the CES 2018 Gallery to view it. Make sure to see the captions, which will either appear at the bottom of the screen, or if you clicke the “Info” button (“i” in circle) it will open up a side panel with the caption, and then you can go through the images with arrow keys or the arrow buttons.
In the gallery you will see commentary on 3 different flying car offerings, many LIDARs, 6 delivery robots and the silliest product of CES 2018.
It’s been reported that Pony.ai got a $112M series A which shows the valuation frenzy is continuing. Pony.ai was founded by veterans of Baido (and Google Chauffeur), but what is more surprising is that their plan is not very ambitious, at least for now — cars for restricted environments such as campuses and small towns. They will go after the Chinese market first.
The U.S. Dept. of Transport will make a 3rd round of robocar regulations this summer. The first round was much too detailed, the 2nd round fixed that but said almost nothing. The 3rd round will probably be a bit closer to the middle, and will also deal with trucks, which were left out of earlier rules.
The Financial Times reported earlier this year that one of the largest clothing manufacturers, Hong Kong-based Crystal Group, proclaimed robotics could not compete with the cost and quality of manual labor. Crystal’s Chief Executive, Andrew Lo, emphatically declared, “The handling of soft materials is really hard for robots.” Lo did leave the door open for future consideration by acknowledging such budding technologies as “interesting.”
One company mentioned by Lo was Georgia Tech spinout, Softwear Automation. Softwear made news last summer by announcing its contract with an Arkansas apparel factory to update 21 production lines with its Sewbot automated sewing machines. The factory is owned by Chinese manufacturer Tianyuan Garments, which produces over 20 million T-shirts a year for Adidas. The Chairman of Tianyuan, Tang Xinhong, boasted about his new investment, saying “Around the world, even the cheapest labor market can’t compete with us,” when Sewbot brings down the costs to $0.33 a shirt.
The challenge for automating cut & sew operations to date has been the handling of textiles which come in a seemingly infinite number of varieties that stretch, skew, flop and move with great fluidity. To solve this problem, Softwear uses computer vision to track each individual thread. According to its issued patents, Softwear developed a specialized camera which captures threads at 1,000 frames per second and tracks their movements using proprietary algorithms. Softwear embedded this camera around robot end effectors that manipulate the fabrics similar to human fingers. According to a description on IEEE Spectrum these “micromanipulators, powered by precise linear actuators, can guide a piece of cloth through a sewing machine with submillimeter precision, correcting for distortions of the material.” To further ensure the highest level of quality, Sewbot uses a four-axis robotic arm with a vacuum gripper that picks and places the textiles on a sewing table with a 360-degree conveyor system and spherical rollers to quickly move the fabric panels around.
Softwear’s CEO, Palaniswamy “Raj” Rajan, explained, “Our vision is that we should be able to manufacture clothing anywhere in the world and not rely on cheap labor and outsourcing.” Rajan appears to be working hard towards that goal, professing that his robots are already capable of reproducing more than 2 million products sold at Target and Walmart. According to IEEE Spectrum, Rajan further asserted in a press release that at the end of 2017, Sewbot will be on track to produce “30 million pieces a year.” It is unclear if that objective was ever met. Softwear did announce the closing of its $7.5 million financing round by CTW Venture Partners, a firm of which Rajan is also the managing partner.
Softwear Automation is not the only company focused on automating the trillion-dollar apparel industry. Sewbo has been turning heads with its innovative approach to fabric manipulation. Unlike Softwear, which is taking the more arduous route of revolutionizing machines, Sewbo turns textiles into hardened substances that are easy for off-the-shelf robots and existing sewing appliances to handle. Sewbo’s secret sauce, literally, is a water-soluble thermal plastic or stiffening solution that turns cloth into a cardboard-like material. Blown away by its creativity and simplicity, I sat down with its inventor Jonathan Zornow last week to learn more about the future of fashion automation.
After researching the best polymers to laminate safely onto fabrics using a patent-pending technique, Zornow explained that last year he was able to unveil the “world’s first and only robotically-sewn garment.” Since then, Zornow has been contacted by almost every apparel manufacturer (excluding Crystal) to explore automating their production lines. Zornow has hit a nerve with the industry, especially in Asia, that finds itself in the labor management business with monthly attrition rates of 10% and huge drop offs after Chinese New Year. Zornow shared that “many factory owners were in fact annoyed that they couldn’t buy the product today.”
Zornow believes that automation technologies could initially be a boom for bringing small-batch production back to the USA, prompting an industry of “mass customization” closer to the consumer. As reported in 2015, apparel brands have been moving manufacturing back from China with 3D-printing technologies for shoes and knit fabrics. Long-term, Zornow said, “I think that automation will be an important tool for the burgeoning reshoring movement by helping domestic factories compete with offshore factories’ lower labor costs. When automation becomes a competitive alternative, a big part of its appeal will be how many headaches it relieves for the industry.”
To date, fulfilling the promise of “Made In America” has proven difficult, as Zornow explained we have forgotten how to make things here. In a recent report by the American Apparel & Footwear Association, US apparel manufacturing fell from 50% in 1994 to roughly 3% in 2015, meaning 97% of clothing today is imported. For example, Zornow shared with me how his competitor was born. In 2002, the US Congress passed the Berry Amendment requiring the armed services to make uniforms domestically, which led DARPA to grant $1.75 million to a Georgia Tech team to build a prototype of an automated sewing machine. As Rajan explains, “The Berry Amendment went into effect restricting the military from procuring clothing that was not made in the USA. Complying with the rule proved challenging due to a lack of skilled labour available in the US that only got worse as the current generation of seamstresses retired with no new talent to take their place. It was under these circumstances that the initial idea for Softwear was born and the company was launched in 2012.”
I first met Zornow at RoboBusiness last September when he demonstrated for a packed crowd how Sewbo is able to efficiently recreate the 10-20 steps to sew a T-shirt. However, producing a typical mens dress shirt can require up to 80 different steps. Zornow pragmatically explains the road ahead, “It will be a very long time, if ever, before things are 100% automated.” He points to examples of current automation in fabric production, such as dyeing, cutting and finishing which augment manual labor. Following this trend “they’re able to leverage machines to achieve incredible productivity, to the point where the labor cost to manufacture a yard of fabric is usually de minimis.” Zornow foresees a future where his technology is just another step in the production line as forward-thinking factories are planning two decades ahead, recognizing that in order “to stay competitive they need new technologies” like Sewbo.