mlsanityData to 7 Oct 2026

Marine Vehicles Localization Using Grid Cells for Path Integration

arXiv 2107.13461 ↗First posted 28 Jul 2021cs.RO cs.AI cs.SYcited by 0

Not on the map. Why?

Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 3 of its 38 references that are in the map. First posted on arXiv 28 Jul 2021.

Builds on

3 of 38 references.

References · 3

  1. 2016Past, Present, and Future of Simultaneous Localization And Mapping: Towards the Robust-Perception Agecited by 405
  2. 2017DeepVO: Towards End-to-End Visual Odometry with Deep Recurrent Convolutional Neural Networkscited by 173
  3. 2020Spiking Neural Networks Hardware Implementations and Challenges: a Surveycited by 14

Built on by

Not cited yet.