Lack of depth constancy for grasping movements in both virtual and real environments

Abstract

Recent studies on visuomotor processes using virtual setups have suggested that actions are affected by similar biases as perceptual tasks. In particular, a strong lack of depth constancy is revealed, resembling biases in perceptual estimates of relative depth. With this study we aim to understand whether these findings are mostly caused by a lack of metric accuracy of the visuomotor system or by the limited cues provided by the use of virtual reality. We addressed this issue by comparing grasping movements towards a spherical object located at four distances (420, 450, 480, and 510 mm) performed in three conditions: 1) virtual, in which the target was a virtual object defined by binocular cues, 2) glow-in-the-dark, in which the object was painted with luminous paint but no other cue was provided, and 3) full-cue, in which the movement was performed with the lights on and all the environmental information was available. Results revealed a striking effect of object distance on grip aperture equally in all three conditions. Specifically, grip aperture gradually decreased with increase in object distance, proving a consistent lack of depth constancy. These findings clearly demonstrate that systematic biases in grasping actions are not induced by the use of virtual environments and that action and perception may involve the same visual information, which does not engage a metric reconstruction of the scene.

Keywords: 3D; depth constancy; grasping; virtual reality; visuomotor control.

Fig. 1.

The grasping of a spherical object was performed in 3 different conditions. A, virtual: sphere and the visual feedback of the fingers were virtually rendered. The virtual sphere was paired with a real one located at the same distance and having the same dimension (ø 60 mm). Visual feedback of the index finger and thumb were rendered by means of virtual cylinders (height: 20 mm; ø: 10 mm). B, glow-in-the-dark: the sphere and the fingers of the participants were covered with luminous material to make them visible in the dark. The start and end of the trials was indicated by the PLATO goggles turning transparent and opaque. C, full-cue: the object was perfectly visible in front of the participants as well as their hand. All cues were available and the light was on for the duration of the experiment. The start and end of the trials was indicated by the PLATO goggles turning transparent and opaque.

Fig. 2.

For both the index finger and thumb 3 markers located at the vertexes of a triangle and the finger pad defined a rigid prism (dashed lines). During calibration, the position of the finger pad relative to the three markers was determined through a fourth calibration marker (gray discs) so that the location of the finger pad was uniquely specified for any orientation of the 3-marker configuration.

Fig. 3.

A: averaged maximum grip aperture (MGA) performed in the 3 conditions, virtual (black line), glow-in-the-dark (dark gray line), and full-cues (light gray line) as function of distance. Error bars represent means ± SE. B: plot of the grip aperture along the spaced-normalized trajectory (sampled at 101 points) for the 3 experimental conditions. For each subject and at each points of the trajectory, we fitted a linear regression model as function of distance (centered by subtracting its mean). Separately for the 3 conditions we run a 1-sample t-test on the slopes of the model to test from which point of the trajectory the grip aperture was significantly modulated by the target distance. The frames represent a blow-up of the part of the trajectory in which the grip aperture was modulated as function of the target distance. The shading bar on the bottom of each plot represents the P value of the t-test run on the single slopes.

Fig. 4.

Averaged peak velocity performed in the 3 conditions, virtual (black line), glow-in-the-dark (dark gray line), and full-cues (light gray line) as function of distance. Error bars represent means ± SE.

Fig. 5.

Averaged movement duration of the 3 conditions. Bars are segmented in subsequent movement phases from black to light gray: from movement onset to time of peak acceleration; from time of peak acceleration to time of peak velocity; from time of peak velocity to time of peak deceleration; from time of peak deceleration to time of MGA; and from time of MGA to movement end.