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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References
Wehner, R.: Desert ant navigation: How miniature brains solve complex tasks. J. Comp. Physiol. A 189, 579–588 (2003)
Graham, P., Philippides, A.: Insect-Inspired Vision and Visually Guided Behavior. In: Bhushan, B., Winbigler, H.D. (eds.) Encyclopedia of Nanotechnology. Springer (2012)
Cartwright, B.A., Collett, T.S.: Landmark Learning in Bees - Experiments and Models. J. Comp. Physiol. A 151, 521–543 (1983)
Möller, R., Vardy, A.: Local visual homing by matched-filter descent in image distances. Biol. Cybern. 95, 413–430 (2006)
Smith, L., Philippides, A., Graham, P., Baddeley, B., Husbands, P.: Linked local navigation for visual route guidance. Adapt. Behav. 15, 257–271 (2007)
Baddeley, B., Graham, P., Philippides, A., Husbands, P.: Holistic visual encoding of antlike routes: Navigation without waypoints. Adapt. Behav. 19, 3–15 (2011)
Baddeley, B., Graham, P., Husbands, P., Philippides, A.: A Model of Ant Route Navigation driven by Scene Familiarity. PLoS Comput. Biol. 8(1), e1002336 (2012)
Graham, P., Philippides, A., Baddeley, B.: Animal cognition: Multi-modal interactions in ant learning. Curr. Biol. 20, R639–R640 (2010)
Wehner, R., Michel, B., Antonsen, P.: Visual navigation in insects: coupling of egocentric and geocentric information. J. Exp. Biol. 199, 129–140 (1996)
Wystrach, A., Mangan, M., Philippides, A., Graham, P.: Snapshots in ants? New interpretations of paradigmatic experiments. J. Exp. Biol. 216, 1766–1770 (2013)
Müller, M., Wehner, R.: Path integration provides a scaffold for landmark learning in desert ants. Curr. Biol. 20, 1368–1371 (2010)
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Philippides, A., Dewar, A., Wystrach, A., Mangan, M., Graham, P. (2013). How Active Vision Facilitates Familiarity-Based Homing. In: Lepora, N.F., Mura, A., Krapp, H.G., Verschure, P.F.M.J., Prescott, T.J. (eds) Biomimetic and Biohybrid Systems. Living Machines 2013. Lecture Notes in Computer Science(), vol 8064. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39802-5_56
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DOI: https://doi.org/10.1007/978-3-642-39802-5_56
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