基于深度学习和物联网的机器人应用

C. Pascal, Laura-Ofelia Raveica, D. Panescu
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引用次数: 2

摘要

本文提出了一种将工业机器人集成到物联网中的方法,并将其与深度学习应用程序结合使用。除了工业场景中通常存在的制造商限制之外,作为工业4.0的一部分,还需要一种扩展和合并机器人感知和决策系统的简单方法。与此相关,所提出的方法将基于IBM Watson物联网云的平台,Node-RED云应用程序,带有TensorFlow的深度学习机制(用于计算机视觉案例研究)和老一代工业机器人结合在一起。有几个结论强调了在真实制造环境中使用物联网和深度学习解决方案的权衡。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Robotized application based on deep learning and Internet of Things
This paper presents a way to integrate an industrial robot into Internet of Things and to use it with a deep learning application. Besides of manufacturer’s restrictions, which usually exist in an industrial scenario, an easy method to extend and merge the sensorial and decisional systems for robots will be required as part of Industry 4.0. Related to this, the proposed method couples IBM Watson IoT cloud-based platform, a Node-RED cloud application, a deep learning mechanism with TensorFlow (this being applied for a computer vision case study), and an old generation industrial robot. Several conclusions highlight the tradeoff of using IoT and deep learning solutions for a real manufacturing environment.
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