Augmented Reality for Supporting Workers in Human–Robot Collaboration

Author:

Moya Ana1,Bastida Leire1ORCID,Aguirrezabal Pablo2ORCID,Pantano Matteo3ORCID,Abril-Jiménez Patricia4

Affiliation:

1. TECNALIA, Basque Research and Technology Alliance (BRTA), 48160 Derio, Spain

2. TECNALIA, Basque Research and Technology Alliance (BRTA), 01510 Miñano, Spain

3. Technology Department, Siemens Aktiengesellschaft, 81739 Munich, Germany

4. Life Supporting Technologies—LifeSTech, Universidad Politécnica de Madrid, 28030 Madrid, Spain

Abstract

This paper discusses the potential benefits of using augmented reality (AR) technology to enhance human–robot collaborative industrial processes. The authors describe a real-world use case at Siemens premises in which an AR-based authoring tool is used to reduce cognitive load, assist human workers in training robots, and support calibration and inspection tasks during assembly tasks. The study highlights the potential of AR as a solution for optimizing human–robot collaboration and improving productivity. The article describes the methodology used to deploy and evaluate the ARContent tool, which demonstrated improved usability, reduced task load, and increased efficiency in the assembly process. However, the study is limited by the restricted availability of workers and their knowledge of assembly tasks with robots. The authors suggest that future work should focus on testing the ARContent tool with a larger user pool and improving the authoring tool based on the shortcomings identified during the study. Overall, this work shows the potential for AR technology to revolutionize industrial processes and improve collaboration between humans and robots.

Publisher

MDPI AG

Subject

Computer Networks and Communications,Computer Science Applications,Human-Computer Interaction,Neuroscience (miscellaneous)

Reference28 articles.

1. EU (2023, March 23). Industry 5.0. Available online: https://research-and-innovation.ec.europa.eu/research-area/industry/industry-50_en.

2. Industry 5.0 and Human-Robot Co-Working. Procedia Comput;Demir;Science,2019

3. Post COVID-19 Industrial Revolution 5.0. The Dawn of Cobot, Chipbot and Curbot;Iftikhar;Pak. J. Surg. Med.,2020

4. Matheson, E., Minto, R., Zampieri, E., Faccio, M., and Rosati, G. (2019). Human–Robot Collaboration in Manufacturing Applications: A Review. Robotics, 8.

5. Lin, C.J., and Lukodono, R.P. (2021). Sustainable Human–Robot Collaboration Based on Human Intention Classification. Sustainability, 13.

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