Roomba’s Father Says Robots Will Evolve

Release time:2017-11-17
author:Ameya360
source:Rick Merritt
reading:1350

  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.

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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.
2017-11-09 00:00 reading:1287
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