Three 2D-warping schemes for visual robot navigation
Autonomous Robots
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Insects can remember and return to a place of interest using the surrounding visual cues. In previous experiments, we showed that crickets could home to an invisible cool spot in a hot environment. They did so most effectively with a natural scene surround, though they were also able to home with distinct landmarks or blank walls. Homing was not successful, however, when visual cues were removed through a dark control. Here, we compare six different models of visual homing using the same visual environments. Only models deemed biologically plausible for use by insects were implemented. The average landmark vector model and first order differential optic flow are unable to home better than chance in at least one of the visual environments. Second order differential optic flow and GradDescent on image differences can home better than chance in all visual environments, and best in the natural scene environment, but do not quantitatively match the distributions of the cricket data. Two models—centre of mass average landmark vector and RunDown on image differences—could produce the same pattern of results as observed for crickets. Both the models performed best using simple binary images and were robust to changes in resolution and image smoothing.