工业制造制动化 应用了机器学习的人机交互问题解决

工业制造制动化 应用了机器学习的人机交互问题解决 李翰 对于现代制造业来说,自动化机器人设备的使用已经无处不在,例如常规的机械手,以及被应用在智能仓库中的自动引导运输车(Auto-guided Vehicle)。然而,在绝大多数的工作环境中,人类操作者仍然无法被完全取代。这带来一个问题:人机的交互。对于一个受到监控的系统而言,灵活且不受控的人类给工序带来了极大的干扰和不可预见性。这使得自动化管控系统的建模和优化变得更具挑战性。因此,为了在更大的范围内应用自动化机器人设备,工业制造领域需要一个更具适应性的自主决策系统。以强化学习代理进行系统建模就是方案之一, 由强化学习训练出来的自动化系统将拥有更高的适应能力,使其可以根据观察到的信息来对系统策略做出调整。 计算机运算能力的进步使得现代工业生产获得了多方面的进步,这些进步主要是通过对环境的感知捕捉,并且将这个过程中的生成的数据进行适当的数据处理来实现的。将生产工作的工序,事件用各类传感器捕获,处理,分析使得创建数字化制造系统成为可能。所谓智能制造正是基于上述系统所收集到的信号进行建模,预测,优化的产物。 结合硬件和软件,并能够将控制过程数字化的系统被称CPS(Cyber-Physical-System),先进的系统能够根据这些数据进行适应和自主决策。如何将各个步骤数字化本身就是一个非常有挑战性的工作,在此之上,数字化表示的生产工序会跟着系统的升级而变得更加详细,现有的数据等级结构在面对着更大的数据量时存在着一些问题。为了解决这些问题以实现数据自适应和自主决策,系统将不同的任务分配给系统内的代理模块。每个代理都拥有自主权,独立处理本地的数据以及决策,并且根据自身积累的经验进行学习、优化。 最近的这些系统利用机器学习(基于神经网络算法)来自动化每个代理的控制和分析过程,根据每个代理的累积经验进行优化,并且控制整个系统的决策流程。 在工业制造领域,机器学习已经以各种方式得到了应用,如前文所述,他是实现自主CPS的核心驱动力。监督学习技术已经为现有的系统提供了非常先进的预测系统,这类系统可以通过数据中提取的更详细、更准确的信息来解决维护、生产力优化、物流优化、动态模拟模型的问题。最近,以强化学习为主的深度学习的进步进一步的改进了这些预测模型,这主要体现在计算机视觉能力上。更精确的对周围环境的掌控,进一步优化了CPS预测周围环境以及和周围联动、协调的能力。 如上文所述,CPS需要考虑到和人类同事在生产过程中的交互,不论是直接的交互,或者是时序的交互。从系统层面来讲,系统需要考虑到不同分区如何观察人类行为,并在内部(系统内的多个数据处理的代理)以及外部(环境、人类同事)进行相互适应以打成统一目标。这方面的工作在人机交互的设计中非常重要,因为人类不受系统控制,且人类的工作状态也会根据外部因素(比如疲劳)进行实时改变。 在一些直接合作的情况(人类和机器人一起执行一个动作,而非单纯的协调双方的动作), 人机合作任务已经受益于带有人机交互能力的智能控制系统的引入,尤其是那些直接涉及到物理合作的项目。比如说让机器人去处理一些高难度的任务,并且使用机器学习技术来提高此类任务的精度和协调性,或者让机器人去相对轻松的操作一些大型的组件。这类任务同样也用到了类似的学习算法来进行机器人的教学一次来完成一些复杂的制造工序,比如果复合材料的叠层和焊接制造(这道工序需要极高的灵活度,而且必须达到和专业人类同等的光滑度)。 其他应用则侧重于被动的合作形式,比如说识别当前工作环境下人员的专业程度、结合环境的状况或者直接观察、判断人员的状态,然后以此给出相应的提示,警告或者优化方案。这类技术在手势控制方案上也同样有效,并且还有延展到更多人机交互的趋势:通过预测认为因素对人的性能影响,使得机器可以根据人效率的改变来做出适应性的行为。 总而言之,因为强化学习对CPS感知、预测、决策能力的提升,这项技术将会在现代化工业智能生产的领域上解决优化以人机交互需求为主的问题。这将从根本上解决由人类行为的不确定因素所造成的隐患,诸如人类效率下降导致的生产流程失误,未经授权的访问或者未经授权行为的制止,以及将人类也作为对象的生产监控、优化。集成了人机交互能力的CPS系统应该将会成为工业制造领域发展的趋势。

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Cameras installed at Japanese train station can automatically identify drunken commuters

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You Don’t Like Sharing Your Car. But Can Elon Musk Change Your Mind?

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Too Bad You’ll Never Drive Nissan’s Razor-Like Electric Concept

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iBeacon technology powers a new Smart Public Transport project in Bucharest

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India Marks Success in First Reusable Spacecraft Test

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Watch an Electric Corvette Obliterate Its Own Speed Record

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