Marine Vehicles Localization Using Grid Cells for Path Integration
This addresses a critical limitation for marine industry applications by providing a novel localization method, though it appears incremental as it adapts a known biological mechanism to a new domain.
The paper tackles the problem of accurate position estimation for Autonomous Underwater Vehicles (AUVs) in GPS-denied underwater environments by using grid cells from neuroscience for path integration, with simulation results demonstrating feasibility.
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.