Abstract
This paper examines locomotion methods for large virtual environments presented through head-mounted displays and involving complex navigation. Our interest is on comparing methods involving bipedal locomotion to those involving motion controlled continuously through a joystick. In the first of two experiments 36 participants performed a navigational search task where they either walked, their translation/rotations were controlled by joystick, or their translations were controlled by joystick but their rotations were controlled by body-based turning. In addition, the optic flow rate, or translational gain of movement, was varied. In the second experiment, 24 participants performed a complex search involving only walking and joystick translation with body-based rotation, followed by a task in which they were asked to recall their search from novel viewpoints. Our findings suggest that for such complex tasks walking is preferable if space and equipment allow for such a locomotion mode.
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Notes
- 1.
The bi-dimensional regression package we used is found in R.
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Acknowledgement
The authors would like to thank Qiufeng Lin for help throughout, and the reviewers for constructive comments. This material is based upon work supported by the National Science Foundation under grants 1116988 and 1526448.
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Xie, X., Paris, R.A., McNamara, T.P., Bodenheimer, B. (2018). The Effect of Locomotion Modes on Spatial Memory and Learning in Large Immersive Virtual Environments: A Comparison of Walking with Gain to Continuous Motion Control. In: Creem-Regehr, S., Schöning, J., Klippel, A. (eds) Spatial Cognition XI. Spatial Cognition 2018. Lecture Notes in Computer Science(), vol 11034. Springer, Cham. https://doi.org/10.1007/978-3-319-96385-3_5
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