Navigating a Heavy Industry Environment Using Augmented Reality - A Comparison of Two Indoor Navigation Designs

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 12191)


The fourth industrial revolution seeks to enhance and optimize industrial processes through digital systems. However, such systems need to meet special criteria for usability and task support, ensuring users’ acceptance and safety. This paper presents an approach to support employees in heavy industries with augmented reality based indoor navigation and instruction systems. An experimental study examined two different user interface concepts (navigation path vs. navigation arrow) for augmented reality head-mounted-displays. In order to validate a prototypical augmented reality application that can be deployed in such production processes, a simulated industrial environment was created. Participants walked through the scenario and were instructed to work on representative tasks, while the wearable device offered assistance and guidance. Users’ perception of the system and task performance were assessed. Results indicate a superior performance of the navigation path design, as it granted participants significantly higher perceived support in the simulated working tasks. Nevertheless, the covered distance by the participants was significantly shorter in navigation arrow condition compared to the navigation path condition. Considering that the navigation path design resulted in a higher perceived Support, renders this design approach more suitable for assisting personnel working at industrial workplaces.


Augmented reality Heavy industry Indoor navigation Work support HCI Experimental study 



This work was part of the DamokleS 4.0 project funded by the European Regional Development Fund (ERDF) [1], the European Union (EU) and the federal state North Rhine Westphalia. The authors thank Mathias Grimm, Ziyaad Qasem and Vanessa Dümpel for their preparations regarding the setup and help with data collection, as well as all participants contributing to the study.


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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Institute of Computer ScienceUniversity of Applied Sciences Ruhr WestBottropGermany

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