On the Use of Persistent Spatial Points for Deploying Path Navigation in Augmented Reality: An Evaluation Study

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Abstract

People use various techniques and tools to perform spatial navigation tasks, such as asking a local person for instructions in order to reach a destination or creating a detailed route plan for their trip through technology-mediated tools. Novel technologies, such as augmented reality, have been introduced to improve the performance and enhance the experience of the end-users. To provide navigation experiences with improved accuracy and decent stability, the developers of such tools can use persistent spatial points, which are stationary points in the real world that an augmented-reality system should keep track of over time. However, the use of persistent spatial points can dramatically increase the development effort, as it requires additional and time-consuming actions to be made by the developers. In this paper, we investigate the use of persistent spatial points for navigation in an AR environment from a developer and an end-user perspective, aiming to understand the trade-off between the development effort, the user performance, and the user experience. We report an empirical study in which a software engineer developed two versions of an augmented-reality navigation application (one with persistent spatial points and one without) which were used by twenty-eight individuals to navigate. Our study results revealed a trade-off between the development effort, the user performance, and the user experience, which depends on the length of the navigation path. The shorter the path is, the less the need for persistent spatial points is, while, on the other hand, the longer the path is, the more critical it is to use persisting spatial points. Based on the results, we discuss ways of mitigating the development effort while maintaining high user performance and experience.

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APA

Bachras, V., Raptis, G. E., & Avouris, N. M. (2019). On the Use of Persistent Spatial Points for Deploying Path Navigation in Augmented Reality: An Evaluation Study. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11749 LNCS, pp. 309–318). Springer Verlag. https://doi.org/10.1007/978-3-030-29390-1_17

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