Robots as Tool to Study the Robustness of Visual Place Cells

In this paper, a model of place cells (PCs) built from precise neurobiological data is presented. The robustness of the model in real indoor and outdoor environments is tested. Results show that the interplay between precise neurobiological modelling and robotic experiments can promote the understanding of the biological circuitry and the achievement of very robust robot navigation algorithms. Short Term Memory (STM), soft competition and sparse coding are important for both landmark identification and computation of PC activities.

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