论文标题
在工业任务中以功能性对象网络的基础
Grounding of the Functional Object-Oriented Network in Industrial Tasks
论文作者
论文摘要
在这项初步工作中，我们建议设计一个适合工业4.0（I4.0）应用程序的活动识别系统，尤其是专注于在协作机器人任务中从演示中学习（LFD）。更确切地说，我们专注于活动识别系统和协作机器人系统之间的数据交换问题。我们建议使用以对象为导向的网络（FOON）链接数据的活动识别系统，以促进工业用例。最初，我们为用例起草了一个Foon。之后，通过使用对象和手动识别系统以及经常性神经网络来估算一个动作，该系统指的是FOON对象和状态。最后，使用现有的链接数据模型通过上下文代理共享检测到的操作，从而使机器人系统能够解释该操作并之后执行该操作。我们的初始结果表明，FOON可用于工业用例，我们可以在LFD应用程序中使用现有的链接数据模型。
In this preliminary work, we propose to design an activity recognition system that is suitable for Industrie 4.0 (I4.0) applications, especially focusing on Learning from Demonstration (LfD) in collaborative robot tasks. More precisely, we focus on the issue of data exchange between an activity recognition system and a collaborative robotic system. We propose an activity recognition system with linked data using functional object-oriented network (FOON) to facilitate industrial use cases. Initially, we drafted a FOON for our use case. Afterwards, an action is estimated by using object and hand recognition systems coupled with a recurrent neural network, which refers to FOON objects and states. Finally, the detected action is shared via a context broker using an existing linked data model, thus enabling the robotic system to interpret the action and execute it afterwards. Our initial results show that FOON can be used for an industrial use case and that we can use existing linked data models in LfD applications.
