How a new generation of grippers with improved 3D perception and tactile sensing is learning to manipulate a wide variety of objects This is a guest post. The views expressed here are solely those of the author and do not represent positions of IEEE Spectrum or the IEEE. While robots have prepared entire breakfasts since 1961, general manipulation in the real world is arguably an even more complex problem than autonomous driving. It is difficult to pinpoint exactly why, though. Closely watching the 1961 video suggests that a two-finger parallel gripper is good enough for a variety of tasks, and that it is only perception and encoded common sense that prevents a robot from performing such feats in the real world. Indeed, a recent Science article reminded us that even contact-intensive assembly tasks such as assembling a piece of furniture are well within the realm of current industrial robots. The real problem is Continue reading Robots Getting a Grip on General Manipulation
But Zume’s investors have given it unicorn status anyway Zume, the robotic pizza maker, is now valued at more than US $2 billion, thanks to its latest round of investment. According to The Wall Street Journal, this latest infusion of funds—$375 million—came entirely from SoftBank; and the Japanese conglomerate apparently has another $375 million at the ready should Zume need it. The valuation, in Silicon Valley terms, makes the new company a unicorn, one of the rare breed of startups thought to be worth over $1 billion. This is just wrong. Because it’s just not good pizza. Zume, based in Mountain View, Calif., launched three years ago. The company set out to revolutionize pizza delivery by turning pizza-making over to robots, and then cooking the pizza in the back of delivery vans in ovens controlled through cloud-based software. Zume has pitched van-based ovens as a vastly more efficient model for pizza Continue reading Zume, the Robotic Pizza Company, Makes Pies Only a Robot Could Love
In a quest for penny-priced plastic sensors, Arm and its partners are demonstrating a stripped-down form of machine learning Body odor is a stubborn problem. Not just for people, but also for sensors. Sensors and the computing attached to them struggle to perceive armpit odors in the way humans do, because B.O. is really a complex mix of dozens of gaseous chemicals. The UK’s PlasticArmPit project is designing the first machine learning–enabled flexible plastic sensor chip. Its target audience: those who think they might stink. The prototype chip will be manufactured and tested in 2019. The project is part of a broader effort Arm has been involved in to drive the cost of plastic IoT devices down below US $0.01 so that they can be embedded in all sorts of consumer goods, including disposable ones.