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The model builds on biological constraints and \nassumptions drawn from the anatomy and physiology of the \nhippocampal formation of the rat. The emphasis of the presented \nresearch is on the usability of a computer model originally \nproposed to describe episodic memory capabilities of the \nhippocampus in a spatial task. In the present model two \nmodalities - vision and path integration - are contributing to \nthe recognition of a given place. We study how place cell \nactivity emerges due to Hebbian learning in the model \nhippocampus as a result of random exploration of the \nenvironment. The model is implemented in the Webots mobile \nrobotics simulation software. Our results show that the location \nof the robot is well predictable from the activity of a \npopulation of model place cells, thus the model is suitable to \nbe used as a basic building block of location-based navigation \nstrategies. 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