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From neural circuits to adaptive spatial navigation: A comprehensive review of brain-inspired navigation techniques

  • Yixin Liu
  • , Zhihao Zhang
  • , Lingling Wang
  • , Li Fu*
  • , Maria S. Selezneva
  • , Konstantin A. Neusypin
  • *Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

Abstract

Brain-inspired navigation technology, which is derived from the neural mechanisms of the animal brain, demonstrates notable adaptability and energy efficiency. It offers solutions to the shortcomings of conventional analytical navigation systems in complex and dynamic environments. This approach effectively combines spatial cognition and path planning by integrating multimodal information perception, modeling navigation cells, and utilizing brain-inspired neural network algorithms. In particular, adaptability plays a central role in enabling systems to cope with environmental variability, sensor uncertainty and unexpected disturbances. However, challenges remain in enhancing information fusion accuracy, system robustness and real-time performance. Future research should emphasize investigating adaptive neural mechanisms in animals to guide the development of biologically plausible and computationally efficient navigation systems that can operate flexibly and reliably in real-world scenarios.

Original languageEnglish
Article number121046
JournalMeasurement: Journal of the International Measurement Confederation
Volume271
DOIs
StatePublished - 28 Apr 2026

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • Adaptability
  • Brain-inspired navigation
  • Multimodal information perception
  • Navigation cells
  • Neural mechanisms

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