Developing virtual reality (VR) applications which enable actual work over a period of time requires optimization of the most basic interactions, such as object manipulation, so that the immersed participant can concentrate on higher-level tasks rather than on lowlevel motor activities. This paper presents a framework and experimental testbed for studies of VR object manipulation techniques. The framework provides a systematic task analysis of immersive manipulation and suggests a user-specific non-Euclidean system for the measurement of VR spatial relationships. The Virtual Reality Manipulation Assessment Testbed (VRMAT) is a practical implementation of the framework and is a flexible tool allowing in-depth experimental studies of immersive manipulation. Pilot studies have been conducted to evaluate this framework and testbed and to establish a baseline for further development.

The field of view (FOV) in most head-mounted displays (HMDs) is no more than 60 degrees wide -- far narrower than our normal FOV of about 200 wide. This mismatch arises mostly from the difficulty and expense of building wide-FOV HMDs. Restricting a person's FOV, however, has been shown in real environments to affect people's behavior and degrade task performance. Previous work in virtual reality too has shown that restricting FOV to 50 or less in an HMD can degrade performance. I conducted experiments with a custom, wide-FOV HMD and found that performance is degraded even at the relatively high FOV of 112, and further at 48. The experiments used a prototype tiled wide-FOV HMD to measure performance in VR at up to 176 total horizontal FOV, and a custom large-area tracking system to establish new findings on performance while walking about a large virtua...

Cognitive maps are mental models of the relative locations and attributes of phenomena in spatial environments. Understanding how people form cognitive maps of virtual environments is vital to effective virtual world design. Unfortunately, such an understanding is hampered by the difficulty of cognitive map measurement. The present study tests the validity of using sketch maps to examine aspects of virtual world cognitive maps. We predict that subjects who report feeling oriented within the virtual world will produce better sketch maps and so sketch map accuracy can be used as an external measure of subject orientation and world knowledge. Results show a high positive correlation between subjective ratings of orientation, world knowledge and sketch map accuracy, supporting our hypothesis that sketch maps provide a valid measure of internal cognitive maps of virtual environments. Results across different worlds also suggest that sketch maps can be used to find an absolute measure for go...

Introduction Computer technology has only recently become advanced enough to solve the problems it creates with its own interface. One solution, virtual reality (VR), immediately raises fundamental issues in both semantics and epistemology. Broadly, virtual reality is that aspect of reality which people construct from information, a reality which is potentially orthogonal to the reality of mass. Within computer science, VR refers to interaction with computer generated spatial environments, environments constructed to include and immerse those who enter them. VR affords non-symbolic experience within a symbolic environment. Since people evolve in a spatial environment, our knowledge skills are anchored to interactions within spatial environments. VR design techniques, such as scientific visualization, map digital information onto spatial concepts. When our senses are immersed in stimuli from the virtual world, our minds construct a closure to crea

6 Acknowledgements 7 1. Introduction 8 1.1. Spatialization of user interfaces........................................................... .... 8 1.2. Researching navigation in a textual virtual environment..................................10 1.3. Ontology of environmental terms............................................................11 1.4. Structure of this thesis............................................................... .........12 2. Spatial cognition of humans 14 2.1. What is "space"?................................................... ............................14 2.1.1. Philosophical and physical concepts of space.............................14 2.1.2. The mathematical view of space.............................................15 2.1.2.1. Metric spaces ........................................................16 2.1.2.2. Topological space...................................................17 2.1.2.3. Graph theory...........................................................

this paper, we explore the human factors issues involved in using virtual environments for the analysis of scientific data and phenomena. We first discuss the features of virtual reality and the nature of scientific data exploration (Section 2). In Section 3, we outline possible ways to visually represent scientific data, and we describe the perceptual and cognitive considerations that can be significant in architecting a virtual world that will effectively depict the researchers' data. In many ways, the promise of virtual reality lies in the level and the novel forms of interactivity that are possible in a virtual environment. We discuss the human factors issues related to interacting with a virtual world in Section 4, examining the issues related to navigation and travel within a virtual world as well as those related to searching for, grasping, and manipulating objects in the world. 2 Virtual Environments for Scientific Data Analysis Visual analysis of scientific data sets is often best supported by an interactive environment in which the researcher is able to view the entire data set, move forward and backward through time, search for specific values or features, obtain quantitative information about particular data locations, and manipulate objects in the data space. Virtual reality provides an especially interactive environment, and should be well suited to supporting the interactive exploration of scientific data sets [13]. Humans have considerable experience in interacting with a 3-dimensional world, moving about, and interacting with and using tools. In virtual environments, head-tracking or hand-tracking is often used to establish position -- the scientist physically moves or makes gestures in 3-space. This makes navigation within the 3-dimensional model world...

Computer-simulated environments hold promise for training people about real-world spaces. However, relatively little research has examined the role of user characteristics and abilities in determining the effectiveness of these virtual environments (VE's) for training spatial knowledge. A correlational study is reported in which the relationships between the following factors are explored: paper-and-pencil based assessments of spatial ability, ability to form an accurate spatial representation of a large realworld environment, gender, computer attitudes and experience, proficiency with the navigational interface of the virtual environment, and the ability to acquire and transfer spatial knowledge from a VE. Consistent with other studies, the relationship between psychometrically-assessed spatial ability and real-world environmental knowledge is found to be very weak. However, spatial ability is significantly associated with spatial knowledge acquisition in a virtual environment. Profic...

There is currently much research activity involving virtual environments (VEs) and spatial behavior (spatial perception, cognition, and performance). After some initial remarks describing and categorizing the different types of research being conducted on VEs and spatial behavior, discussion in this paper focuses on one specific type, namely, research concerned with the use of VE technology for training spatial behavior in the real world. We initially present an overview of issues and problems relevant to conducting research in this area, and then, in the main portion of the paper, present an overview of the research that we believe needs to be done in this area. We have written this paper for the forum section of PRESENCE because, despite its length, it is essentially an opinion piece. Its aim is not to report the results of research in our own laboratory nor to review the literature; other papers that fulfill these functions are already available in other articles. The primary purpose of this paper is to stimulate discussion about needed future research. In general, we believe that open discussion of research that needs to be done can serve the research enterprise as much as discussion of completed work. 1.

A relatively simple architectural space was modeled and used to compare the effects of spatial training in simulations versus training in the real world. Thirty-five subjects were trained in one of the following conditions: real world (RW), virtual environment (VE), nonimmersive virtual environment (NVE), and model (Mod). The VE condition made use of a head-mounted display to view the simulated environment, while the NVE condition used a desktop monitor. In the Mod condition, the subject viewed and could manipulate a 3-D model of the space, viewed from a desktop display. The training -transfer tasks, performed after brief unstructured exposure to the actual space or to one of the simulations, consisted of estimating the bearing and range to various targets in the real space from various spatially distributed stations, each such pair of estimates constituting a subtask of the overall transfer task. Results obtained from each of the four training conditions proved to be roughly the same. Training in any one of the simulations was comparable to training in the real world. Independent of training condition, there was a strong tendency among subjects to underestimate range. Variability in range errors was dominated by differences among subjects, whereas variability in bearing errors was dominated by differences among subtasks. These results are discussed in the context of plans for future work. 1

Two experiments investigated components of participants' spatial knowledge when they navigated large-scale "virtual buildings" using "desk-top" (i.e., nonimmersive) virtual environments (VEs). Experiment 1 showed that participants could estimate directions with reasonable accuracy when they traveled along paths that contained one or two turns (changes of direction), but participants' estimates were significantly less accurate when the paths contained three turns. In Experiment 2 participants repeatedly navigated two more complex virtual buildings, one with and the other without a compass. The accuracy of participants' route-finding and their direction and relative straight-line distance estimates improved with experience, but there were no significant differences between the two compass conditions. However, participants did develop significantly more accurate spatial knowledge as they became more familiar with navigating VEs in general. 1