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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
  • *此作品的通讯作者
  • Beihang University
  • Bauman Moscow State Technical University

科研成果: 期刊稿件 › 文献综述 › 同行评审

摘要

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.

源语言英语
期刊论文编号121046
期刊Measurement: Journal of the International Measurement Confederation
卷271
DOI
出版状态已出版 - 28 4月 2026

联合国可持续发展目标

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  1. 可持续发展目标 7 - 经济适用的清洁能源
    可持续发展目标 7 经济适用的清洁能源

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