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Title Action-Inspired Approach to Design of Navigation Techniques for Effective Spatial Learning in 3-D Virtual Environments
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Publication Date
Date Accessioned
Degree PhD
Discipline/Department Computer Science
Degree Level doctoral
University/Publisher Virginia Tech
Abstract Navigation in large spaces is essential in any environment (both the real world and the virtual world) because one of the human fundamental needs is to know the surrounding environment and to freely navigate within the environment. For successful navigation in large-scale virtual environments (VEs), accurate spatial knowledge is required, especially in training and learning application domains. By acquiring accurate spatial knowledge, people can effectively understand spatial layout and objects in environments. In addition, spatial knowledge acquired from a large- scale VE can effectively be transferred to the real world activities. Numerous navigation techniques have been proposed to support successful navigation and effective spatial knowledge acquisition in large-scale VEs. Among them, walking-like navigation techniques have been shown to support spatial knowledge acquisition more effectively in large-scale VEs, compared to non-body-based and non-walking-based navigation techniques. However, walking-like navigation techniques in large-scale VEs still have some issues, such as whole-body fatigue, large-controlled-space and specialized system configuration that make the walking-like navigation techniques less convenient, and consequently less commonly used. Due to these issues, convenient non-walking-like navigation techniques are preferred although they are less effective for spatial learning. While most research and development efforts are centered around walking- like navigation techniques, a fresh approach is needed to effectively and conveniently support for human spatial learning. We propose an action-inspired approach, to design convenient and effective navigation techniques for supporting people to acquire accurate spatial knowledge acquisition or improve spatial learning. The action-inspired approach is based on our insights from learning, neuropsychological and neurophysiological theories. The theories suggest that action and perception are closely related and core elements of learning. Our observations indicated that specific body-parts are not necessarily related to learning. We identified two types of action-inspired approach, body-turn based and action-transferred. Body- turn based approach keeps body-turn but replaces cyclic leg-movements of original walking action with more convenient control to resolve the issues presented from walking-like navigation techniques. Action-transferred approach addresses the design trade-offs between effectiveness and convenience, the core concept of which is grounded in the motor equivalence theory. We provided two navigation techniques, body-turn based and action-transferred based ones, and demonstrated the benefits of our approach by evaluating these two navigation techniques for spatial knowledge acquisition in several empirical studies. We also developed our own walking-like navigation technique, Sensor- Fusion Walking-in-Place (SF-WIP) because we needed a reference navigation technique for estimating the effect of the…
Subjects/Keywords design approach; action; perception; virtual environment; spatial knowledge; navigation technique
Contributors Quek, Francis K. H.| (committeechair); Gracanin, Denis (committeechair); Bukvic, Ivica Ico (committee member); Winchester, Woodrow W. (committee member); Bowman, Douglas Andrew (committee member)
Rights This Item is protected by copyright and/or related rights. Some uses of this Item may be deemed fair and permitted by law even without permission from the rights holder(s), or the rights holder(s) may have licensed the work for use under certain conditions. For other uses you need to obtain permission from the rights holder(s).
Country of Publication us
Record ID handle:10919/50621
Repository vt
Date Retrieved
Date Indexed 2019-03-19
Issued Date 2013-05-07 00:00:00
Note [degree] Ph. D.;

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