During navigation, humans combine visual information from their surroundings with body-based information from the translational and rotational components of movement. Theories of navigation focus on the role of visual and rotational bodybased information, even though experimental evidence shows they are not sufficient for complex spatial tasks. To investigate the contribution of all three sources of information, we asked participants to search a computer generated "virtual" room for targets. Participants were provided with either only visual information, or visual supplemented with body-based information for all movement (walk group) or rotational movement (rotate group). The walk group performed the task with nearperfect efficiency, irrespective of whether a rich or impoverished visual scene was provided. The visual-only and rotate groups were significantly less efficient, and frequently searched parts of the room at least twice. This suggests full physical movement plays a critical role in navigational search, but only moderate visual detail is required.

Navigation is the most common interactive task performed in three-dimensional virtual environments (VEs), but it is also a task that users often find difficult. We investigated how body-based information about the translational and rotational components of movement helped participants to perform a navigational search task (finding targets hidden inside boxes in a room-sized space). When participants physically walked around the VE while viewing it on a head-mounted display (HMD), they then performed 90% of trials perfectly, comparable to participants who had performed an equivalent task in the real world during a previous study. By contrast, participants performed less than 50% of trials perfectly if they used a tethered HMD (move by physically turning but pressing a button to translate) or a desktop display (no body-based information). This is the most complex navigational task in which a real-world level of performance has been achieved in a VE. Behavioral data indicates that both translational and rotational body-based information are required to accurately update one's position during navigation, and participants who walked tended to avoid obstacles, even though collision detection was not implemented and feedback not provided. A walking interface would bring immediate benefits to a number of VE applications.

Two experiments investigated participants' ability to search for targets in a cluttered small-scale space. The first experiment was conducted in the real world with two field of view conditions (full vs. restricted), and participants found the task trivial to perform in both. The second experiment used the same search task but was conducted in a desktop virtual environment (VE), and investigated two movement interfaces and two visual scene conditions. Participants restricted to forward only movement performed the search task quicker and more efficiently (visiting fewer targets) than those who used an interface that allowed more flexible movement (forward, backward, left, right, and diagonal). Also, participants using a high fidelity visual scene performed the task significantly quicker and more efficiently than those who used a low fidelity scene. The performance differences between all the conditions decreased with practice, but the performance of the best VE group approached that of the real-world participants. These results indicate the importance of using high fidelity scenes in VEs, and suggest that the use of a simple control system is sufficient for maintaining ones spatial orientation during searching. MOVEMENT AROUND CLUTTERED ENVIRONMENTS

Three levels of virtual environment (VE) metric are proposed, based on: (1) users' task performance (time taken, distance traveled, and number of errors made), (2) physical behavior (locomotion, looking around, and time and error classification), and (3) decision making (i.e., cognitive) rationale (think aloud, interview, and questionnaire). Examples of the use of these metrics are drawn from a detailed review of research into VE wayfinding. A case study from research into the fidelity that is required for efficient VE wayfinding is presented, showing the unsuitability in some circumstances of common metrics of task performance such as time and distance, and the benefits to be gained by making fine-grained analyses of users' behavior. Taken as a whole, the paper highlights the range of techniques that have been successfully used to evaluate wayfinding and explains in detail how some of these techniques may be applied.

No abstract