Boeing designs an energy efficient plane with “transonic” wings
From Popular Mechanics:
Supersonic airliners are poised for a comeback. But while we await the arrival of a new generation of commercial jets that break the sound barrier, Boeing is working on another way to speed up air travel: making planes lighter and more energy efficient.
The aviation giant is building an ultra-lightweight folding “transonic” wing, which Boeing says will allow larger planes to fly at higher altitudes while nearly scraping the speed of sound, which is consistent with the speed of many of today’s airliners. The ultimate goal is to make long-haul flights seem more like medium-haul flights as the wings propel aircraft at speeds just below Mach 1.
According to recent lab tests conducted by Boeing, the conceptual design would allow aircraft to generate top speeds of Mach 0.8. That pales in comparison to the defunct Concorde jet, which reached a top speed of Mach 2.04, or 1,354 mph, before its 2003 retirement. Boeing’s transonic speeds would match what today’s airliners achieve (typically in the 400- to 600-mph range, for physics reasons). The wings are also “less noisy,” according to the company, which sounds like an added bonus for anyone concerned with loud, clattering engines typical of commercial jets (or the sonic booms of supersonic planes).
Still in the conceptual phase, the wings extend a sprawling 170 feet end to end, supported by a truss and a modified wing sweep to make aircraft more aerodynamic. The transonic wings are the product of a decade-long partnership with NASA’s Subsonic Ultra Green Aircraft Research project, based on the space agency’s need for “subsonic aviation concepts and technologies” that could help the aviation industry lower its carbon footprint.
A wearable glove that helps people regain the use of their hand
Considering the level of spectacle you can find at CES, it’s easy to forget that some companies would rather build products that help people instead of flashy displays. Consider Neofect: we met this startup last year and found a lot to like about its NeoMano glove, a wearable that helps people who suffer from specific kinds of paralysis regain some use of their hands.
The last time we checked in, the startup had a mostly functional model but still hadn’t gotten things to the point where they could actually start producing NeoManos for the masses. Since then, though, Neofect redesigned the glove in a few crucial ways (and delivered on its promise to make the NeoMano look a little “cooler”) and successfully ushered it through an IndieGogo campaign. So, what’s actually new here?
For one, it’s a little more comfortable (not to mention sanitary) to wear since the titanium wires used to raise and lower paralyzed fingers are now covered. More importantly, though, it’s (mostly) all wireless. The original version required a hardwired connection between all of the NeoMano’s components, which would’ve been pretty unwieldy for real world use. The current glove, which we’re told is basically the same as the version that will ship to backers this summer, connects to a power and control unit that rests on the wearer’s forearm. That box then connects to a remote that users can wear around their necks, giving them quick access to the grip and open hand controls.
Robots that teach themselves to walk
It’s easy to watch a baby finally learn to walk after hours upon hours of trial and error and think, OK, good work, but do you want a medal or something? Well, maybe only a childless person like me would think that, so credit where credit is due: It’s supremely difficult for animals like ourselves to manage something as every day as putting one foot in front of the other.
It’s even more difficult to get robots to do the same. It used to be that to make a machine walk, you either had to hard-code every command or build the robot a simulated world in which to learn. But lately, researchers have been experimenting with a novel way to go about things: Make robots teach themselves how to walk through trial and error, like babies, navigating the real world.
Researchers at UC Berkeley and Google Brain just took a big step (sorry) toward that future with a quadrupedal robot that taught itself to walk in a mere two hours. It was a bit ungainly at first, but it essentially invented walking on its own. Not only that, the researchers could then introduce the machine to new environments, like inclines and obstacles, and it adapted with ease. The results are as awkward as they are magical, but they could lead to machines that explore the world without us having to coddle them.
The secret ingredient here is a technique called maximum-entropy reinforcement learning. Entropy in this context means randomness — lots of it. The researchers give the robot a digital reward for doing something random that ends up working well. So in this case, the robot is rewarded for achieving forward velocity, meaning it’s trying new things and inching forward bit by bit.
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