Holistic visual encoding of ant-like routes: Navigation without waypoints

  • Baddeley B
  • Graham P
  • Philippides A
 et al. 
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Abstract

It is known that ants learn long visually guided routes through complex terrain. However, the mechanisms by which visual information is first learned and then used to control a route direction are not well understood. In this article, we propose a parsimonious mechanism for visually guided route following. We investigate whether a simple approach, involving scanning the environment and moving in the direction that appears most familiar, can provide a model of visually guided route learning in ants. We implement view familiarity as a means of navigation by training a classifier to determine whether a given view is part of a route and using the confidence in this classification as a proxy for familiarity. Through the coupling of movement and viewing direction, a familiar view specifies a familiar direction of viewing and thus a familiar movement to make. We show the feasibility of our approach as a model of ant-like route acquisition by learning a series of nontrivial routes through an indoor environment using a large gantry robot equipped with a panoramic camera.

Author-supplied keywords

  • Insect navigation
  • autonomous robotics
  • image classification
  • route learning
  • view-based homing

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Authors

  • Bart Baddeley

  • Paul Graham

  • Andrew Philippides

  • Philip Husbands

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