Optic Flow Helps Humans Learn to Navigate through Synthetic Environments

Abstract

Self-movement through an environment generates optic flow, a potential source of heading information. But it is not certain that optic flow is sufficient to support navigation, particularly navigation along complex, multi-legged paths. To address this question, we studied human participants who navigated synthetic environments with and without salient optic flow. Participants used a keyboard to control realistic simulation of self-movement through computer-rendered, synthetic environments. Because these environments comprised series of identically textured virtual corridors and intersections, participants had to build up some mental representation of the environment in order to perform. The impact of optic flow on learning was examined in two experiments. In experiment 1, participants learned to navigate multiple T-junction mazes with and without accompanying optic flow. Optic flow promoted faster learning, mainly by preventing disorientation and backtracking in the maze. In experiment 2, participants found their way around a virtual city-block environment, experiencing two different kinds of optic flow as they went. By varying the rate at which the display was updated, we created optic flow that was either fluid or choppy. Here, fluid optic flow (as compared with choppy optic flow) enabled participants to locate a remembered target position more accurately. When other cues are unavailable, optic flow can be a significant aid in wayfinding. Among other things, optic flow can facilitate path integration, which involves updating a mental representation of place by combining the trajectories of previously travelled paths.