Obstacle avoidance during walking in real and virtual environments

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 = 0.16 m), larger obstacle clearance (Δ = 0.16 m), and slower walking speed (Δ = 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 50% 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.

[1]  M. Tarr,et al.  Virtual reality in behavioral neuroscience and beyond , 2002, Nature Neuroscience.

[2]  C. Richards,et al.  The negotiation of stationary and moving obstructions during walking: anticipatory locomotor adaptations and preservation of personal space. , 2005, Motor control.

[3]  J. Loomis,et al.  PART I : General Issues in the Design and Use of Virtual and Adaptive Environments Visual Perception Egocentric ~ istance in Real and Virtual Environments , 2003 .

[4]  J E Cutting,et al.  Comparing effects of the horizontal-vertical illusion on grip scaling and judgment: relative versus absolute, not perception versus action. , 1999, Journal of experimental psychology. Human perception and performance.

[5]  Jack M. Loomis,et al.  Absolute motion parallax weakly determines visual scale in real and virtual environments , 1995, Electronic Imaging.

[6]  Volker H Franz,et al.  Planning versus online control: dynamic illusion effects in grasping? , 2003, Spatial vision.

[7]  K. Nakayama,et al.  Optical Velocity Patterns, Velocity-Sensitive Neurons, and Space Perception: A Hypothesis , 1974, Perception.

[8]  Richard Wilkie,et al.  Controlling steering and judging heading: retinal flow, visual direction, and extraretinal information. , 2003, Journal of experimental psychology. Human perception and performance.

[9]  Zijiang J. He,et al.  Distance determined by the angular declination below the horizon , 2001, Nature.

[10]  Peter Willemsen,et al.  The Influence of Restricted Viewing Conditions on Egocentric Distance Perception: Implications for Real and Virtual Indoor Environments , 2005, Perception.

[11]  Peter Willemsen,et al.  Does the Quality of the Computer Graphics Matter when Judging Distances in Visually Immersive Environments? , 2004, Presence: Teleoperators & Virtual Environments.

[12]  Lynn A. Olzak,et al.  Functional Aspects of Border-Signalling Mechanisms , 1996 .

[13]  Betty J. Mohler,et al.  The influence of feedback on egocentric distance judgments in real and virtual environments , 2006, APGV '06.

[14]  E. Brenner,et al.  A new view on grasping. , 1999, Motor control.

[15]  Frank H. Durgin,et al.  Distance Perception and the Visual Horizon in Head-Mounted Displays , 2005, TAP.

[16]  Charles Audet,et al.  Generalized pattern searches with derivative information , 2002, Math. Program..

[17]  J. Philbeck,et al.  Comparison of two indicators of perceived egocentric distance under full-cue and reduced-cue conditions. , 1997, Journal of experimental psychology. Human perception and performance.

[18]  Brett R Fajen,et al.  Visual Guidance of Intercepting a Moving Target on Foot , 2004, Perception.

[19]  Peter Willemsen,et al.  Throwing versus walking as indicators of distance perception in similar real and virtual environments , 2005, TAP.

[20]  P. Dixon,et al.  Dynamic illusion effects in a reaching task: evidence for separate visual representations in the planning and control of reaching. , 2001, Journal of experimental psychology. Human perception and performance.

[21]  Peter Willemsen,et al.  The effects of head-mounted display mechanics on distance judgments in virtual environments , 2004, APGV '04.

[22]  K. R. Llewellyn,et al.  Visual guidance of locomotion. , 1971, Journal of experimental psychology.

[23]  M. Goodale,et al.  The visual brain in action , 1995 .

[24]  W. H. Warren,et al.  Behavioral dynamics of intercepting a moving target , 2007, Experimental Brain Research.

[25]  A. Fitzgibbon,et al.  Humans Ignore Motion and Stereo Cues in Favor of a Fictional Stable World , 2006, Current Biology.

[26]  M. Goodale,et al.  Size-contrast illusions deceive the eye but not the hand , 1995, Current Biology.

[27]  D. Proffitt,et al.  Eye height scaling of absolute size in immersive and nonimmersive displays. , 2000, Journal of experimental psychology. Human perception and performance.

[28]  M. Fahle,et al.  Grasping Visual Illusions: No Evidence for a Dissociation Between Perception and Action , 2000, Psychological science.

[29]  Brett R Fajen,et al.  Behavioral dynamics of steering, obstacle avoidance, and route selection. , 2003, Journal of experimental psychology. Human perception and performance.

[30]  Margaret A. Hagen,et al.  The Perception of Pictures , 1982 .

[31]  W. Warren,et al.  Visual guidance of walking through apertures: body-scaled information for affordances. , 1987, Journal of experimental psychology. Human perception and performance.

[32]  Hh Bülthoff,et al.  A comparison of grasping real and virtual objects , 1996 .

[33]  Jeroen B J Smeets,et al.  Modeling the time-dependent effect of the Ebbinghaus illusion on grasping. , 2003, Spatial vision.

[34]  Robert S. Allison,et al.  Egocentric Direction and the Visual Guidance of Robot Locomotion Background, Theory and Implementation , 2002, Biologically Motivated Computer Vision.

[35]  Gregor Schöner,et al.  Dynamics of behavior: Theory and applications for autonomous robot architectures , 1995, Robotics Auton. Syst..