Toward Cognitive Navigation: Design and Implementation of a Biologically Inspired Head Direction Cell Network

Zhenshan Bing, Amir E.I. Sewisy, Genghang Zhuang, Florian Walter, Fabrice O. Morin, Kai Huang, Alois Knoll

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

As a vital cognitive function of animals, the navigation skill is first built on the accurate perception of the directional heading in the environment. Head direction cells (HDCs), found in the limbic system of animals, are proven to play an important role in identifying the directional heading allocentrically in the horizontal plane, independent of the animal's location and the ambient conditions of the environment. However, practical HDC models that can be implemented in robotic applications are rarely investigated, especially those that are biologically plausible and yet applicable to the real world. In this article, we propose a computational HDC network that is consistent with several neurophysiological findings concerning biological HDCs and then implement it in robotic navigation tasks. The HDC network keeps a representation of the directional heading only relying on the angular velocity as an input. We examine the proposed HDC model in extensive simulations and real-world experiments and demonstrate its excellent performance in terms of accuracy and real-time capability.

Original languageEnglish
Pages (from-to)2147-2158
Number of pages12
JournalIEEE Transactions on Neural Networks and Learning Systems
Volume33
Issue number5
DOIs
StatePublished - 1 May 2022

Keywords

  • Autonomous driving
  • cognitive navigation
  • continuous attractor network (CAN)
  • head direction cells (HDCs)
  • neural simultaneous localization and mapping (SLAM)

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