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.

Keywords:
Computer science Work (physics) Artificial intelligence Deep learning Machine learning Engineering Mechanical engineering

Metrics

5
Cited By
0.58
FWCI (Field Weighted Citation Impact)
25
Refs
0.73
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Human-Automation Interaction and Safety
Social Sciences →  Psychology →  Social Psychology
Augmented Reality Applications
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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