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兵工学报 ›› 2022, Vol. 43 ›› Issue (11): 2965-2980.doi: 10.12382/bgxb.2021.0659

• 综述 • 上一篇    

基于海马体的面向未知复杂环境类脑导航技术综述

陈雨荻1, 熊智1,2, 刘建业1,2, 杨闯1, 晁丽君1, 彭杨3   

  1. (1.南京航空航天大学 自动化学院 导航研究中心, 江苏 南京 211106;2.先进飞行器导航、控制与健康管理工信部重点实验室, 江苏 南京 211106;3.上海航天控制技术研究所, 上海 201109)
  • 上线日期:2022-06-23
  • 通讯作者: 熊智(1976—),男,教授,博士生导师 E-mail:xiongzhi@nuaa.edu.cn
  • 作者简介:陈雨荻(1995—), 女, 博士研究生。E-mail: chenyudi@nuaa.edu.cn
  • 基金资助:
    国家自然科学基金项目(61873125);国防基础科研计划项目(JCKY2020605C009);航空科学基金项目(ASFC-2020Z071052001);中央高校基本科研业务费专项资金项目(NZ2020004);江苏省研究生科研与实践创新计划项目 (KYCX22_0370);直升机旋翼动力学国家重点实验室项目(61422202111)

Review of Brain-inspired Navigation Technology Based on Hippocampal Formation for Unknown Complex Environments

CHEN Yudi1, XIONG Zhi1,2, LIU Jianye1,2, YANG Chuang1, CHAO Lijun1, PENG Yang3   

  1. (1.Navigation Research Center, College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, Jiangsu, China; 2.Key Laboratory of Navigation, Guidance and Health-Management Technologies of Advanced Aerocraft, Ministry of Industry and Information Technology, Nanjing 211106, Jiangsu, China; 3.Shanghai Aerospace Control Technology Institute, Shanghai 201108, China)
  • Online:2022-06-23

摘要: 无人移动平台具有广泛的应用前景,其搭载的自主导航系统在执行任务中发挥了重要作用。随着脑科学研究的逐渐深入,类脑自主导航技术为解决未知复杂环境下难以构建精确导航数学模型问题提供了新的方法和实现途径。本文首先介绍基于内嗅皮层-海马区空间表征机理的类脑自主导航技术理论;其次讨论在大脑导航理论基础上构建类脑自主导航系统和空间表征细胞模型的方法和国内外研究现状;然后归纳未知复杂环境下类脑同步地图构建与定位、类脑路径规划等技术的研究应用,最后对类脑自主导航技术的未来发展提出了一些建议。

关键词: 类脑自主导航, 认知地图, 同步地图构建与定位, 路径规划, 人工智能

Abstract: Unmanned mobile platform has wide application prospects, and its autonomous navigation system plays an important role in performing tasks. As brain science research goes deeper, brain-inspired autonomous navigation technology provides a new method and implementation approach for solving the problem of building mathematical models of precise navigation in unknown and complex environments. Firstly, the brain-inspired autonomous navigation technology theory based on the spatial representation mechanism of the entorhinal cortex-hippocampal formation is introduced. Secondly, the methods and current research status at home and abroad of constructing brain-inspired autonomous navigation systems and spatially representing cell models based on brain navigation are discussed. Then, the research and application of brain-inspired simultaneous localization and mapping and path planning in unknown complex environments are summarized. Finally, some suggestions are put forward for the future development of brain-inspired autonomous navigation technology.

Key words: brain-inspiredautonomousnavigation, cognitivemap, simultaneouslocalizationandmapping, pathplanning, artificialintelligence

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