User Behavior Adaptive AR Guidance for Wayfinding and Tasks Completion

Augmented reality (AR) is widely used to guide users when performing complex tasks, for example, in education or industry. Sometimes, these tasks are a succession of subtasks, possibly distant from each other. This can happen, for instance, in inspection operations, where AR devices can give instruc...

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Bibliographic Details
Published in:Multimodal technologies and interaction 2021-11, Vol.5 (11), p.65
Main Authors: Truong-Allié, Camille, Paljic, Alexis, Roux, Alexis, Herbeth, Martin
Format: Article
Language:English
Subjects:
Augmented reality
Computer Science
Efficiency
Graphics
head-mounted display
Helmet mounted displays
Inspection
large space
multitask
Neural networks
Prototypes
Task complexity
User behavior
Wayfinding
Workloads
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Summary:Augmented reality (AR) is widely used to guide users when performing complex tasks, for example, in education or industry. Sometimes, these tasks are a succession of subtasks, possibly distant from each other. This can happen, for instance, in inspection operations, where AR devices can give instructions about subtasks to perform in several rooms. In this case, AR guidance is both needed to indicate where to head to perform the subtasks and to instruct the user about how to perform these subtasks. In this paper, we propose an approach based on user activity detection. An AR device displays the guidance for wayfinding when current user activity suggests it is needed. We designed the first prototype on a head-mounted display using a neural network for user activity detection and compared it with two other guidance temporality strategies, in terms of efficiency and user preferences. Our results show that the most efficient guidance temporality depends on user familiarity with the AR display. While our proposed guidance has not proven to be more efficient than the other two, our experiment hints toward several improvements of our prototype, which is a first step in the direction of efficient guidance for both wayfinding and complex task completion.
ISSN:2414-4088
2414-4088
DOI:10.3390/mti5110065