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可穿戴机械:让人类变成钢铁侠

可穿戴机械:让人类变成钢铁侠

Brady Dale 2014年09月04日
在移动计算技术的推动下,可穿戴机械设备正变得越来越先进,已经相继在医疗、工业和军事领域投入应用。工业革命和信息时代使人类在机器面前越来越被边缘化,那么让人穿上“机械战甲”,会不会让我们重回时代的舞台中央?
在2012年德国杜塞尔多夫国际残疾人用品及康复设备博鉴会上亮相的ReWalk外骨骼系统。Courtesy: Argo Medical Technologies

    在今年巴西世界杯揭幕战上,开球的是一个名叫朱利亚诺•平托,双腿瘫痪的残疾青年。凭借身上穿戴的一套“外骨骼装置”,他仅靠自己的意念就完成了开球动作——没错,既不靠按钮,也不靠肌肉,而是靠脑电波。

    拜脑电图传感器(EEG)所赐,这套装置背后的工程师团队成功开发了一套似乎能够阅读大脑意图的系统。当然,要读懂一个人的心并不容易,所以朱利亚诺•平托必须要学会如何去“想”——他要把这个动作想上一会儿,才能让这套装置明白他的意图。

    外骨骼系统一直是漫画书和未来风格电影中不可缺少的元素之一,但现在,它们已不再是一种科学幻想了。根据市场调研公司WinterGreen提供的数据,康复机器人、机械假肢和外骨骼系统的市场价值已经达到4,300万美元,到2020年预计将达到18亿美元。几乎可以肯定,要不了多久,我们就会看到许多人穿戴着各种各样的机械做越来越多的事情。

    这并不是说以后你的西装下面也会藏着一套“钢铁侠战衣”(当然你也可以选择这么做)。你需要穿戴哪种机器,很大程度上取决于你需要完成的工作。比如宝马公司(BMW)今年一月宣布,该公司研制了一种新型手套,其主要功能是,在工人往车身框架的排水孔上塞橡胶塞(为了方便喷漆)时,可以减轻手指的压力。虽然这似乎并不是多么惊人的功能,但此类工具的应用只会变得越来越精巧。

    外骨骼系统据称是这些工具中最复杂的类别。它们不仅可以让我们更轻易地完成一个简单的动作,而且还有可能帮助我们完成人体能够做到的最复杂的动作。在外骨骼系统的帮助下,残疾人也可以完成并体验之前几乎不可能做到的事,比如走路。另外,外骨骼系统还能帮助健康人(比如士兵)跑得更快、负载更多东西。

    不管是简单的还是复杂的,这些机器人设备为什么一夜之间离我们如此之近?说来也奇怪,这恰恰是由于智能手机的崛起,Mail.ru集团首席执行官,Grishin Robotics公司创始人,企业家,投资人德米特里•格里辛这样说道。

    他指出:“归功于科技革命和智能手机的兴起,很多并非为机器人设计的元件,比如摄像头、传感器、电池和处理器等等,都变得非常便宜了。这从根本上改变了整个行业的面貌。”

    外骨骼装置以及其它一些没有那么复杂的可穿戴机械设备,很可能会率先在以下三个市场上出现。它们分别是:医疗设备行业、重工业和军事领域。

    At this year’s FIFA World Cup, the first kick was delivered by a man with paralyzed legs, Juliano Pinto. He was wearing an elaborate exoskeleton suit that enabled him to, remarkably, tap a soccer ball with his foot using only his mind—no buttons, no muscles, just brainwaves.

    The engineers behind the suit had developed a system that appears to read the brain’s intentions courtesy of electroencephalographic, or EEG, sensors. It’s not that simple to read someone’s mind, of course, so Pinto had to learn to think—ponder that one for a moment—in such a way that would give the suit orders it could understand.

    Exoskeletons have long been a fixture of comic books and futuristic movies, but they aren’t science fiction any more. According to the market research firm WinterGreen Research, the market for rehabilitation robots, active prostheses, and exoskeletons is already worth $43 million and is projected to reach $1.8 billion by 2020. That many people will soon wear different kinds of machines to get more work done is, at this point, nearly a given.

    That’s not to say that you will have motors and gears hidden inside your chalk-stripe suit. (Well, you might.) The type of machine to use will largely depend on the type of work to accomplish. For example, BMW announced in January the creation of a new glove that takes the stress off of a single action—inserting a rubber plug in a car’s frame to close drain holes for the paint coat—for workers in its factories. A modest start, sure, but the applications for such tools will only become more elaborate.

    Exoskeletons are arguably the most complex category of these tools. They don’t just promise to make it easier to complete a simple action; they promise to support or accomplish some of the most complicated maneuvers our bodies are capable of. With exoskeletons, people with disabilities can do and experience much more than they might have otherwise had reason to believe possible, such as walking. Exoskeletons also promise to allow able-bodied people, such as soldiers, run faster and carry more than the average human body otherwise would.

    Simple or complex, why are all of these robotic devices suddenly possible? Oddly enough, it’s because of the rise of the smartphone, says Dmitry Grishin, an entrepreneur and investor who serves as chief executive of Mail.ru Group and founded Grishin Robotics.

    “Right now, because of the revolution in technology and smartphones. a lot of components that weren’t designed for robots—cameras, sensors, batteries, processors, and all of that—have become really cheap,” he says. “And that has completely changed the whole industry.”

    There are three markets where exoskeletons and their less sophisticated siblings are most likely to first appear: the medical devices industry, heavy industry, and the military. Here’s a look at each.

 
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