The present study investigates users' movement behavior in a virtual environment when they attempted to avoid a virtual character. At each iteration of the experiment, four conditions (Self-Avatar LookAt, No Self-Avatar LookAt, Self-Avatar No LookAt, and No Self-Avatar No LookAt) were applied to examine users' movement behavior based on kinematic measures. During the experiment, 52 participants were asked to walk from a starting position to a target position. A virtual character was placed at the midpoint. Participants were asked to wear a head-mounted display throughout the task, and their locomotion was captured using a motion capture suit. We analyzed the captured trajectories of the participants' routes on four kinematic measures to explore whether the four experimental conditions influenced the paths they took. The results indicated that the Self-Avatar LookAt condition affected the path the participants chose more significantly than the other three conditions in terms of length, duration, and deviation, but not in terms of speed. Overall, the length and duration of the task, as well as the deviation of the trajectory from the straight line, were greater when a self-avatar represented participants. An additional effect on kinematic measures was found in the LookAt (Gaze) conditions. Implications for future research are discussed.
To compare and evaluate locomotion interfaces for users who are (virtually) moving on foot in VEs, we performed a study to characterize task behavior and task performance with different visual and locomotion interfaces. In both a computer-generated environment and a corresponding real environment, study participants walked to targets on walls and stopped as close to them as they could without making contact. In each of five experimental conditions participants used a combination of one of three locomotion interfaces (really walking, walking-in-place, and joystick flying), and one of three visual conditions (head-mounted display, unrestricted natural vision, or field-of-view-restricted natural vision). We identified metrics and collected data that captured task performance and the underlying kinematics of the task. Our results show: 1) Over 95 of the variance in simple motion paths is captured in three critical values: peak velocity; when, in the course of a motion, the peak velocity occurs; and peak deceleration. 2) Correlations of those critical value data for the conditions taken pairwise suggest a coarse ordering of locomotion interfaces by "naturalness." 3) Task performance varies with interface condition, but correlations of that value for conditions taken pairwise do not cluster by naturalness. 4) The perceptual variable, r (also known as the time-to-contact) calculated at the point of peak deceleration has higher correlation with task performance than r calculated at peak velocity. This paper addresses the problem of understanding the shape of the locomotor trajectories for a human being walking in an empty space to reach a goal defined both in position and in direction. Among all the possible trajectories reaching a given goal what are the fundamental reasons to chose one trajectory instead of another (see Fig. (1))? The underlying idea to attack this question has been to relate this problem to an optimal control problem: the trajectory is chosen according to some optimization principle. This is our basic starting assumption. The subject being viewed as a controlled system, the question becomes what criteria is optimized? Is it the time to perform the trajectory? the length of the path? the minimum jerk along the path?... In this study we show that the human locomotor trajectories are well approximated by the geodesics of a differential system minimizing the L2 norm of the control. Such geodesics are made of arcs of clothoids. The clothoid or Cornu spiral is a curve, whose curvature grows with the distance from the origin. The study is based on an experimental protocol involving 7 subjects. They had to walk within a motion capture room from a fixed starting point, and to cross over distant porches from which both position in the room and orientation were changing over trials. Previous research suggests that postural sway in standing increases in virtual reality (VR) environments. This study was conducted to examine whether gait instability is prevalent when people walk in a VR environment. Ten healthy adults participated in the study. Subjects walked on a treadmill in a VR environment and a non-VR environment at each of three walking speeds: 0.9, 1.1, and 1.3 m s. In the VR environment, an endless corridor with colored vertical stripes comprising the walls was projected onto a hemispherical screen placed in front of the treadmill. The speed of the moving corridor image was matched to the speed of the treadmill to create the illusion that subjects were walking through the endless corridor. Spatiotemporal data during gait were collected with an instrumented treadmill housing two piezoelectric force platforms. Gait parameters reflective of gait instability (stride length, step width, variability in stride velocity, and variability in step width) were compared between the VR and non-VR environments. Subjects walked in the VR environment with reduced stride lengths (p = 0.001), increased step widths (p = 0.001), and with increased variability in stride velocity (p < 0.001) and step width (p = 0.002). The gait deviations suggest that walking in a VR environment may induce gait instability in healthy subjects.  Immersive virtual environments are a promising research tool for the study of perception and action, on the assumption that visual--motor behavior in virtual and real environments is essentially similar. We investigated this issue for locomotor behavior and tested the generality of Fajen and Warren's [2003] steering dynamics model. Participants walked to a stationary goal while avoiding a stationary obstacle in matched physical and virtual environments. There were small, but reliable, differences in locomotor paths, with a larger maximum deviation (Δ e 0.16 m), larger obstacle clearance (Δ e 0.16 m), and slower walking speed (Δ e 0.13 m s) in the virtual environment. Separate model fits closely captured the mean virtual and physical paths (R2 > 0.98). Simulations implied that the path differences are not because of walking speed or a 50p distance compression in virtual environments, but might be a result of greater uncertainty about the egocentric location of virtual obstacles. On the other hand, paths had similar shapes in the two environments with no difference in median curvature and could be modeled with a single set of parameter values (R2 > 0.95). Fajen and Warren's original parameters successfully generalized to new virtual and physical object configurations (R2 > 0.95). These results justify the use of virtual environments to study locomotor behavior. Virtual walking, a fundamental task in Virtual Reality (VR), is greatly influenced by the locomotion interface being used, by the specificities of input and output devices, and by the way the virtual environment is represented. No matter how virtual walking is controlled, the generation of realistic virtual trajectories is absolutely required for some applications, especially those dedicated to the study of walking behaviors in VR, navigation through virtual places for architecture, rehabilitation and training. Previous studies focused on evaluating the realism of locomotion trajectories have mostly considered the result of the locomotion task (efficiency, accuracy) and its subjective perception (presence, cybersickness). Few focused on the locomotion trajectory itself, but in situation of geometrically constrained task. In this paper, we study the realism of unconstrained trajectories produced during virtual walking by addressing the following question: did the user reach his destination by virtually walking along a trajectory he would have followed in similar real conditions? To this end, we propose a comprehensive evaluation framework consisting on a set of trajectographical criteria and a locomotion model to generate reference trajectories. We consider a simple locomotion task where users walk between two oriented points in space. The travel path is analyzed both geometrically and temporally in comparison to simulated reference trajectories. In addition, we demonstrate the framework over a user study which considered an initial set of common and frequent virtual walking conditions, namely different input devices, output display devices, control laws, and visualization modalities. The study provides insight into the relative contributions of each condition to the overall realism of the resulting virtual trajectories.  