Models of Visually Guided Routes in Ants: Embodiment Simplifies Route Acquisition
It is known that ants learn long visually-guided routes through complex terrain. However, the mechanisms by which visual information is first learnt and then used to control a route direction are not well understood. In this paper 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. The specific embodiment of an ant’s visual system means that movement and viewing direction are tightly coupled, 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 non-trivial routes through a simulated environment firstly using the complete set of views experienced during learning and secondly using an approximation to the distribution of these views.
KeywordsInsect Navigation Route Learning View-Based Homing Restricted Boltzmann Machine Generative Models Autonomous Robotics
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