  Autonomous Underwater Vehicles (AUVs) are platforms used for research and
exploration of marine environments. However, these types of vehicles face many
challenges that hinder their widespread use in the industry. One of the main
limitations is obtaining accurate position estimation, due to the lack of GPS
signal underwater. This estimation is usually done with Kalman filters.
However, new developments in the neuroscience field have shed light on the
mechanisms by which mammals are able to obtain a reliable estimation of their
current position based on external and internal motion cues. A new type of
neuron, called Grid cells, has been shown to be part of path integration system
in the brain. In this article, we show how grid cells can be used for obtaining
a position estimation of underwater vehicles. The model of grid cells used
requires only the linear velocities together with heading orientation and
provides a reliable estimation of the vehicle's position. We provide simulation
results for an AUV which show the feasibility of our proposed methodology.
