How Active Vision Facilitates Familiarity-Based Homing

  • Andrew Philippides
  • Alex Dewar
  • Antoine Wystrach
  • Michael Mangan
  • Paul Graham
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8064)

Abstract

The ability of insects to visually navigate long routes to their nest has provided inspiration to engineers seeking to emulate their robust performance with limited resources [1-2]. Many models have been developed based on the elegant snapshot idea: remember what the world looks like from your goal and subsequently move to make your current view more like your memory [3]. In the majority of these models, a single view is stored at a goal location and acts as a form of visual attractor to that position (for review see [4]). Recently however, inspired by the behaviour of ants and the difficulties in extending traditional snapshot models to routes [5], we have proposed a new navigation model [6-7]. In this model, rather than using views to recall directions to the place that they were stored, views are used to recall the direction of facing or movement (identical for a forward-facing ant) at the place the view was stored. To navigate, the agent scans the world by rotating and thus actively finds the most familiar view, a behavior observed in Australian desert ants. Rather than recognise a place, the action to take at that place is specified by a familiar view.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Andrew Philippides
    • 1
  • Alex Dewar
    • 1
  • Antoine Wystrach
    • 1
  • Michael Mangan
    • 2
  • Paul Graham
    • 2
  1. 1.Centre for Computational Neuroscience and RoboticsUniversity of SussexUK
  2. 2.School of InformaticsUniversity of EdinburghUK

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