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<span style='color:red'>Robo</span>t Changes Skins to Change Its Moves

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Robot Changes Skins to Change Its Moves

　　MIT has invented a robot that swaps out water-soluble, recyclable exoskeletons to perform different tasks by walking, rolling on wheels, gliding, or floating. Daniela Rus, director of MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), led the engineering team that developed the robot, dubbed Primer.　　Although robots that can change their form or function have been created at larger sizes, building smaller-scale self-reconfiguring robots is difficult, partly because of the size and weight of onboard electronics. The cube-shaped Primer robot is controlled remotely via magnets. Its exoskeletons, or skins, are heat-activated, rectangular plastic sheets that self-fold into different shapes to customize the robot for various tasks. Immersion in water dissolves the exoskeleton after Primer completes the job.　　Primer’s technology derives from previous projects by Rus’ team, including centimeter-long, “origami” microrobots that can be precisely customized from sheets of plastic, as well as magnetic blocks that assemble themselves into different shapes. Other CSAIL self-assembling robotics projects have included tiny robotic pebbles that self-assemble to duplicate an object when it’s placed inside a pile of them.　　The idea behind Primer and other self-reconfiguring robots is to give a single machine the ability to perform multiple functions, instead of requiring a separate robot for each task. The team plans to add more modes, such as burrowing in sand, driving through water, and camouflaging the robot’s color. “I can imagine one day being able to customize robots with different arms and appendages,” said Rus in a statement. “Why update a whole robot when you can just update one part of it?”　　Modular, self-reconfiguring robots, and even self-assembling/reassembling robots, have been developed at other university labs, including the University of Pennsylvania’s Modular Robotics Laboratory, the University of Southern California’s Robotics and Autonomous Systems Center, the Georgia Institute of Technology’s Georgia Robotics and Intelligent Systems (GRITS) Laboratory, and Carnegie Mellon University’s Robotics Institute.

Key word：

Robot ,Skins

Release time：2017-12-01 00:00 reading：1062 Continue reading>>

Roomba’s Father Says <span style='color:red'>Robo</span>ts Will Evolve

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Roomba’s Father Says Robots Will Evolve

　　Industrial robots are poised for change.　　They will become more integrated, easy to use and widely deployed, especially in China, which is emerging as a center of robotics innovation. Large fulfillment operations run by the likes of Alibaba and Amazon will be drivers in the next stage of their growth.　　Those were some of the views of Rodney Brooks, a robotics pioneer and current chairman and CTO of Rethink Robotics, speaking in a keynote at an event here.　　Today more than half the cost of a factory robot goes to systems integrators who configure it with sensors and train it, typically writing custom programs and generating proprietary data that stays on the factory floor.　　By contrast, tomorrow’s industrial robots will come with integrated sensors and computer vision. They will be trained without elaborate coding on open platforms that send their data to cloud services. And widely used programmable logic computers (PLCs) will become “art projects,” Brooks predicted.　　“Today’s business model is going away…We are in an industry where deployment speed is like molasses, but it’s not going to be like that forever,” he said.　　Brooks imagined a future where untethered robots, respond to voice commands, freeing their supervisors from today’s interactions via scripting languages. “In the last five years, we have seen a tremendous increase in functionality in speech systems…speech is going to be fine in factories,” he said.　　“The robot industry is squarely stuck in the 20th century…[but] there are so many little startups coming along that things are going to happen, so start worrying because hundreds of thousands of entrepreneurs are coming,” he told an audience of several hundred industrial robot builders.　　China alone has several hundred robotics startups today. They are fueled by a government industrial policy that wants to maintain China’s standing as a global manufacturing center. Robots are also seen as key to dealing with a labor shortage for factory jobs where turnover rates vary from 16-30 percent, Brooks said.　　“A lot of these China startups are low-end manufacturers of cheaper light industrial robots with six-degrees of freedom, dragging prices down so it’s hard for U.S. and European companies to compete there… we can scoff at their level of innovation, but it’s only a matter of time before it increases,” he said.　　So far, promises of millions of robots on Foxconn lines in China have not come true, in part due to the challenges with programming today’s robots, said Brooks, who had his original Roomba robotic vacuum cleaners made by toy manufacturers in Shenzhen. With 20 million units sold, the Roomba became the largest selling robot to date.　　Giant fulfillment operations run by the likes of Alibaba and Amazon will also be big drivers for next-gen robots, probably using machine learning.　　“Amazon Robotics employs 700 people just in Boston, but the robots can’t do pick or pack operations, so they are hiring every Christmas,” Brooks said, noting Amazon funds a university challenge for robots that pack.　　“These fulfillment centers have an incredible need for pick and pack operations where every package is unique. That will drive development in robotic arms in ways we haven’t seen and that will in turn impact factory automation in ways we can’t predict,” he said, calling it a “tremendous” demand that “will disintermediate many people in robotics.”　　One of the big challenges ahead is dealing with safety, an issue for which the Robotics Industry Association hosting the event has set up several working groups.　　Rethink’s own robots currently set payload and velocity constraints as a first step toward safety, but that won’t work for factories that need heavy loads handled quickly. Some companies are now using external cameras and controls to monitor and manage robots, but more solutions are needed, Brooks said.　　Long term, an aging population may demand “speech-controlled robots that help you in and out of bed — that’s an incredible driver of safety,” he said.　　Rethink’s current robotic arms already embed cameras, force sensors and smarts to learn and remember actions. “We can’t do all the things high-end PLCs do, but we can do a lot of it,” he said.　　Another big change will be a move to wireless networking on the factory floor, he predicted“Many of our customers don’t have any network on the factory floor and many keep their data walled off…Wireless is changing things rapidly, there will be a whole different set of infrastructure and policies for what comes on and off the factory floor,” he said.　　Unlike startup Embodied Intelligence, recently launched by Berkeley robotics researchers, Brooks does not believe VR headsets will find wide use as an interface to robots. Instead, he sees supervisors monitoring and managing automated factories with tablets.

Key word：

Robots

Release time：2017-11-17 00:00 reading：1398 Continue reading>>

<span style='color:red'>Robo</span>ts Get AI from Startup

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Robots Get AI from Startup

　　In the next few months, industrial robots will learn how to do their jobs by watching humans, using software from a startup that debuts today. The neural-networking program from Embodied Intelligence also will let robots improve their performance over time.　　The work marks a step toward a future in which robots will understand the visual world. Today, human experts typically train factory-floor robots to repeat motions in a relatively slow two-step process that sometimes requires humans writing custom software.　　“Instead of programming each procedure, we demo it — it doesn’t require an expert … the robot learns from trial and error,” said Peter Chen, a co-founder and chief executive of the company.　　“Our robot software is not restricted to fixed motions. Today, robots do the same mechanical tasks over and over. Our software gives robots the ability to really see through their cameras and make adjustments.”　　In addition to training robots faster and more cheaply, the software also opens the door to teaching new tasks. For example, the system could teach a robot how to thread a wire through a mechanical part, something most computer-vision systems cannot do given the complexity of tracking and programming for a flexible object.　　The startup uses virtual reality headsets to train robots. It currently uses the HTC Vive headset and its motion controller, although any VR headset will do.　　“You see what the robot sees, you make decisions based on what the robot sees … and the robot imitates it,” he said.　　Chen was one of three Berkeley researchers who published results earlier this year of experiments teaching robots 10 basic tasks using machine learning and a VR connection. “With a three-minute demo in VR, robots solved all tasks that previously might have required a PhD in writing algorithms,” he said.　　The approach uses the same deep neural network techniques that web giants such as Google and Facebook use to recognize images and other tasks. VR demos act as the training, setting up neural network pathways or policies that the robots later refine by running inference tasks.　　The company currently builds its own Linux x86 servers using up to eight high-end Nvidia GPUs for training and one for inference work.　　“In the beginning, we will provide this as a service for users who come to us with their specs … that will help us perfect our platform,” he said. “At some point, we will license the software to systems integrators.”　　Chen claims that most of the money that a factory spends on a robot goes to systems integrators who train them — as much as $90,000 of an average total of $150,000. “We are going after that $90,000,” he said.　　Others agree that the brunt of the cost of a robot lies outside the base hardware, much of it in training.　　Factories are expected to buy more than 300,000 robots this year, said Dan Kara, research director for robotics at market watcher ABI Research. He pegs the average cost of an industrial robot at $42,000 and an installed and trained system at $126,000, much of it in software development.　　“Programming industrial robots is a difficult, costly, and time-consuming task,” said Kara in an email exchange. “Tools and techniques that simplify and speed robot-control programming are in high demand.”　　Kara listed Fizyr, Osaro, and Preferred Networks as three other companies working on teaching industrial robots. Google and Brown University are among others doing research in the area.　　Henrik I. Christensen, director of the Institute for Contextual Robotics at U.C. San Diego, said that PlusOne, Universal Robotics, and researchers in Seattle are also pursuing the area.　　“There are quite a few groups trying to use machine learning for robotics,” said Christensen.　　“The reality is that use of machine learning is still quite limited in this area,” said Chen. “The most common thing is using machine learning in inspection; many people are doing that.”　　Chen and two Berkeley colleagues co-authored more than 180 papers in the field before they founded Embodied Intelligence. The trio worked together at OpenAI for about 18 months when they decided that there was a commercial gap they thought they could fill.　　Other founders include Berkeley alums Pieter Abbeel and Rocky Duan, the startup’s chief scientist and chief technology officer, respectively. They were joined by Tianhao Zhang from Microsoft Research as a fourth co-founder.　　The startup raised a $7 million seed round, which Chen said could take it through its first two years. Investors were led by Amplify Partners and include Lux Capital, 11.2 Capital, A.Capital, SV Angels, Rostrum Capital, and angel investors such as Lip-Bu Tan, chief executive of Cadence.

Key word：

Robots,AI

Release time：2017-11-09 00:00 reading：1338 Continue reading>>

Renovo Develops <span style='color:red'>Robo</span>car-Cloud OS

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Renovo Develops Robocar-Cloud OS

　　Ever heard of Renovo? If you’re in the know, of course you have. Renovo is a Campbell, Calif.-based startup, still in a stealth mode, devising a common platform on which numerous service apps can be developed for fleets of highly automated vehicles.　　The startup’s formidable goal is to design an operating system — or more accurately, abstraction layers between automated vehicles and the cloud — that developers can tap to write a variety of “automated mobility on demand” apps for automated vehicles, presumably across the board.　　In a recent phone interview with EE Times, Chris Heiser, Renovo CEO and co-founder, told us, “Think about how Android (based on Linux kernel) allowed app developers to leverage the platform and to bring disruptions to the smartphone market.” Renovo wants to do the same for the auto market.　　From walled garden to open ecosystem　　Heiser noted, “Many automakers like Ford or GM are putting a robot in a car that will be owned by humans.” In his opinion, that [building a Level 4 car] is an easier problem to solve.　　In contrast, Renovo isn’t developing an OS for a robot inside the car, but instead, “We are developing a platform from which a variety of services can be launched.”　　As with many automotive startups in Silicon Valley, Renovo has not detailed its technology. Nor has it publicly demonstrated it. Yet, there is a mounting evidence that the company is getting traction from a few big guns.　　Two strategic investors Renovo has picked up thus far are Samsung, whose big automotive ambitions led to its acquisition of Harman, and Verizon, a cellular network giant with one of the largest telematics and fleet management practices in the world.　　Separately, when Delphi and BlackBerry announced last month their partnership on a software operating system for self-driving cars, the companies said that Delphi’s turnkey self-driving system — called CSLP — is using BlackBerry QNX as an operating system. Delphi said, at that time, that other partners on the CSLP platform include Intel’s Mobileye and Silicon Valley startup Renovo.　　Delphi has not elaborated on its relationship with Renovo. However, as Delphi positions itself as a leading Tier One offering a turnkey self-driving vehicle platform to automakers yet to develop their own self-driving systems, it’s not hard to imagine an opportunity for Renovo to piggyback Delphi and help those carmakers with self-driving service architecture.　　Phil Magney, founder and principal advisor for Vision Systems Intelligence (VSI), believes that Renovo has “a pretty compelling solution that helps bridge some of the gaps in the cloud eco-system.” He added, “The biggest and most ambitious of them is the openness that will take mobility services from a walled garden to an open eco-system.”　　Fleets of highly automated vehicles as a service　　First, let’s clarify Renovo’s thinking, as it develops its technology and business model.　　Renovo is a firm believer in “automated vehicles as a service.” Heiser predicts “a massive shift” in the way people use cars in cities, as cost per miles driven by fleets of automated vehicles inevitably go down.　　Similarly, automakers’ revenue will be much less driven by unit sales. Miles driven per vehicle will be increasingly important. In this circumstance, cities and the automotive industry will initially need a whole bunch of robocars. But missing from this formula, in Renovo’s view, is a service infrastructure, or ecosystem, in which robocars are the integral element.　　Software stacks are necessary for highly automated vehicles to do things like steering, navigation, deciding on where to go, EV charging, pulling over, identifying construction sites on roads, and a lot more.　　Services that will require such software stacks include fleet management, security, “tele-operation,” data collection and other smart city-related applications.　　‘Netflix’ of vehicle automation　　Asked the pressing issues Renovo is trying to solve, Magney said, “Primarily, Renovo provides linkage between fleets of highly automated vehicles and the cloud in terms of how the data from the both sides are being used and monetized.”　　Obviously, a data giant like Google already has the upper hand on the service platform model Renovo is pursuing. Google owns the cloud, and its Waymo leads in the development of highly-automated vehicles.　　But that doesn’t mean it’s game-over for the rest of the automotive industry, in Heiser’s view, because Waymo thus far is building an ecosystem of its own.　　As more U.S. cities allow autonomous car tests on their streets, carmakers face “tremendous pressure,” said Heiser. Besides testing their own vehicles in each city, carmakers need to figure out their own service architecture for fleets of automated vehicles.　　Will Ford, GM and other automakers opt for building their separate ecosystems for fleets of AVs as a service, or opt to join a common platform that enables a variety of services including their own?　　Renovo is betting its future on the latter.　　Magney believes Renovo’s desire is to “enable the ‘Netflix’ of vehicle automation.” He explained, “Renovo’s automated vehicle platform has the capacity to enable lots of third party services and business models that monetize through data/services coming into and out of the vehicles.”　　Unlocking the value of sensors　　During the interview, Renovo’s Heiser noted that an iPhone contains more than two dozen sensors. More important, he noted, “There are already 2 million apps that are taking advantage of data collected by those embedded sensors.”　　Renovo wonders why it can’t do the same for highly automated vehicles. “If there is a clearly defined abstraction layer, we can unlock the value of those sensors already inside the vehicle,” said Heiser.　　Heiser’s reference to “abstraction layers,” however, appears to include even a safety critical layer at vehicle level so that certain applications can talk to actuators and sensors. Renovo’s goal is to build a platform that is hardware- and vehicle-agnostic.　　A big question, however, is whether carmakers will ever allow such a layer to be abstracted.　　Magney said, “I don’t think consumer vehicle manufacturers would be ready to sign on to this concept just yet. However, companies building fleets would favor this approach if the Renovo model starts seeing some traction.”　　Calling it “a chicken and egg problem,” Magney observed, “There’s a reason why Renovo would want to target fleet operators first and foremost — Renovo seems to want to shake up the transportation ecosystem by putting operators and services at the top of the food chain!”　　As Magney sees it, “One critical element of the Renovo model is tele-operation where the service provider has the capacity to take over control of the vehicle.”　　He said, “It is hard to imagine a highly automated world without this capability.” But he acknowledged that getting access vehicle control raises lots of questions about the safety and security of transportation fleets.　　Partnership with Argus　　Inevitably, when a company talks about remote operations of highly automated vehicles, it must be ready for questions about security.　　To that end, Renovo last month announced a partnership with Argus Cyber Security to incorporate Argus’ patented Intrusion Detection and Prevention System technology into Renovo’s automated mobility operating system.　　The two companies said the partnership will cover future cooperation to integrate advanced, multi-layered cybersecurity solutions with Renovo’s proposed platform for automated mobility on-demand services.　　Competitions　　Renovo appears ready to release more details about its technology and business models. Gaps in the cloud ecosystem for highly automated vehicles will become a big story, and the window for Renovo to tell its stories “will begin to close,” said Magney, as big tech companies start announcing their own solutions.　　Magney believes Renovo will face “challenges from the tech heavyweights like Baidu or Google.” Those companies are “really good at device management,” and “both are working on their autonomous vehicle projects.”　　And let’s not forget the standard soon emerging from a consortium of carmakers and Tier Ones like Autosar (AUTOmotive Open System Architecture).　　Magney pointed out, “You also have Adaptive Autosar which defines the technical requirements and services layer necessary to modify or alter to the runtime components of the AV software stack.” He explained, “The Autosar layer is deeper and concerns itself with defining the ECU interfaces and the structure of how ECUs communicate.” Magney believes Adaptive Autosar is complimentary to Renovo’s project.　　He summed up: “Renovo model starts to define the structure of connecting fleets to cloud assets and create a platform that lays the groundwork for advanced automation.” He called it a “very shrewd move,” on the part of the startup, because “nobody, in my opinion, has really defined how this will shape up.”

Key word：

Renovo,Robocar-Cloud OS

Release time：2017-10-26 00:00 reading：1224 Continue reading>>

Nvidia Deals Tilt <span style='color:red'>Robo</span>-Car Race

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Nvidia Deals Tilt Robo-Car Race

　　Claiming that robo-car development by automakers has already moved from the R&D phase to production, Nvidia this week unveiled three new partnership deals — all aimed at leveraging its AI car-computing platform.　　Nvidia announced Monday (June 26) that Volvo and Autoliv have selected Nvidia’s Drive PX 2 for production of self-driving cars in 2021.　　Nvidia said that it also sealed a deal with ZF & Hella, who are both committed to working with Nvidia to deliver with the New Car Assessment Program (NCAP) safety certification for the mass deployment of self-driving vehicles.　　But wait. There’s more. Nvidia also disclosed an agreement Volkswagen, under which the German carmaker will expand deep learning “competence” throughout the enterprise and developing a number of AI apps running in the data center.　　Prior to these disclosures, Nvidia had already picked up a number of other notable car OEMs and tier ones as partners for autonomous vehicle development. Among them, Tesla has been already using Drvie PX in its current-generation cars. Audi is planning to deliver Level 4 cars based on Drive PX platform in 2020, and Toyota will use Nvidia’s platform to power advanced autonomous driving systems. Separately, Daimler, Mercedes Benz (owned by Daimler) and tier one Robert Bosch have also chosen Nvidia as their autonomous platform partner.　　Nvidia's senior automotive director Danny Shapiro told reporters, “The momentum of autonomous vehicles” is growing. The focus of activity is shifting from development to the “production phase.”

Key word：

Nvidia,Robo-Car

Release time：2017-06-28 00:00 reading：1112 Continue reading>>

TI’s Shrewd <span style='color:red'>Robo</span>-Car Strategy

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TI’s Shrewd Robo-Car Strategy

　　While Nvidia and Intel are busy sparring for glory as innovators of fully autonomous vehicle platforms, Texas Instruments, focused on ADAS, has kept its profile low.　　It’s not that TI is indifferent to autonomy. It’s just that TI, one of the leading automotive chip suppliers, sees a different way to get there. Its plan is to use its current ADAS-focused platform to eventually enable Level 4, Level 5 autonomous car.　　In a recent interview with EE Times, Brooke Williams, business manager in the automotive ADAS business unit at Texas Instruments, said TI has been actively participating in carmakers’ RFQs on models four to five years out. Some of the RFQs are for Level 4 and Level 5 autonomous cars. Others address ADAS features to achieve 5-star ratings. “We support all of their requests,” said Williams.　　Above all, TI’s priority is responding to “needs for system-level safety across the board” — all cars, all models, according to Williams.　　TI’s strengths lie in 30 years of ASIL D-level safety experience and a litany of TI technologies that include power management, analog devices, networking solutions such as LVDS and Ethernet, and sensors including radars, he said. The only automotive electronics devices TI doesn’t offer are CMOS image sensors and memory.　　This “system-level safety” argument might seem to be just TI talking points. But the company’s financial results demonstrate how well a modest strategy — focused more on Level 2 autonomous cars — has worked so far. TI reported in April better-than-expected first quarter revenue growth driven primarily by strong sales to the automotive and industrial markets.　　Phil Magney, founder and principal advisor for Vision Systems Intelligence (VSI), noted, “TI does not subscribe to massive architectural overhauls.” He pointed out, “For TI, it is all about incremental ADAS features which become the enablers to automation. TI is not concerned with L4 and L5 at the moment. In time their architectures will support advanced levels of automation but for now they are targeting automotive safety and convenience features because that is where the money is.”　　‘No wholesale change in platform’　　OK. So, today’s TI is all about ADAS.　　But really, what are the plans, if any, for TI to shift its current ADAS platform to Level 4/Level 5 autonomy? During the interview, TI’s Williams noted, “We don’t believe a wholesale change in the platform is needed” to add autonomy to cars.　　That view, however, has triggered a host of questions from automotive industry analysts.

Key word：

TI

Release time：2017-06-13 00:00 reading：1368 Continue reading>>

model	brand	Quote
RB751G-40T2R	ROHM Semiconductor
BD71847AMWV-E2	ROHM Semiconductor
CDZVT2R20B	ROHM Semiconductor
MC33074DR2G	onsemi
TL431ACLPR	Texas Instruments

model	brand	To snap up
ESR03EZPJ151	ROHM Semiconductor
BU33JA2MNVX-CTL	ROHM Semiconductor
IPZ40N04S5L4R8ATMA1	Infineon Technologies
BP3621	ROHM Semiconductor
TPS63050YFFR	Texas Instruments
STM32F429IGT6	STMicroelectronics

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