Handling Work Complexity with AR/Deep Learning

H. Dhiman, S. Büttner, C. Röcker, Raphael-Elias Reisch
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引用次数: 3

Abstract

Complexity is a fundamental part of product design and manufacturing today, owing to increased demands for customization and advances in digital design techniques. Assembling and repairing such an enormous variety of components means that workers are cognitively challenged, take longer to search for the relevant information and are prone to making mistakes. Although in recent years deep learning approaches to object recognition have seen rapid advances, the combined potential of deep learning and augmented reality in the industrial domain remains relatively under explored. In this paper we introduce AR-ProMO, a combined hardware/software solution that provides a generalizable assistance system for identifying mistakes during product assembly and repair.
用AR/深度学习处理工作复杂性
由于定制需求的增加和数字设计技术的进步,复杂性是当今产品设计和制造的基本组成部分。组装和修理如此繁多的部件意味着工人的认知能力受到挑战,需要更长的时间来搜索相关信息,而且容易出错。尽管近年来深度学习方法在物体识别方面取得了快速进展,但深度学习和增强现实在工业领域的结合潜力仍未得到充分探索。本文介绍了AR-ProMO,这是一种硬件/软件结合的解决方案,它提供了一个通用的辅助系统,用于识别产品组装和维修过程中的错误。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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