综述: 类脑智能导航建模技术及其应用

doi:10.12305/j.issn.1001-506X.2024.11.27

系统工程与电子技术 ›› 2024, Vol. 46 ›› Issue (11): 3844-3861.doi: 10.12305/j.issn.1001-506X.2024.11.27

综述: 类脑智能导航建模技术及其应用

李卫斌, 秦晨浩, 张天一, 毛鑫, 杨东浩, 纪文搏, 侯彪, 焦李成

西安电子科技大学人工智能学院, 陕西西安 710071

收稿日期:2023-11-16 出版日期:2024-10-28 发布日期:2024-11-30
通讯作者: 李卫斌
作者简介:李卫斌(1976—), 男, 教授, 博士研究生导师, 博士, 主要研究方向为北斗、遥感、智能导航、大模型及应用、人工智能
秦晨浩(2000—), 男, 硕士研究生, 主要研究方向为北斗、遥感、智能导航
张天一(1995—), 男, 博士研究生, 主要研究方向为高分遥感、北斗高精定位
毛鑫(1999—), 男, 硕士研究生, 主要研究方向为SLAM、无人系统自主导航
杨东浩(1999—), 男, 硕士研究生, 主要研究方向为SLAM、无人系统自主导航
纪文搏(1998—), 男, 硕士研究生, 主要研究方向为遥感、智能导航
侯彪(1974—), 男, 教授, 博士, 主要研究方向为遥感图像解译与目标识别、无人系统协同感知、人工智能芯片及系统
焦李成(1959—), 男, 欧洲科学院外籍院士, 俄罗斯自然科学院外籍院士, 教授, 博士, 主要研究方向为人工智能、海量、高维、非结构化信息处理中的优化与学习、复杂影像的预处理、图像分析和数据压缩、深度学习FPGA系统、遥感影像大数据类脑解译系统、类脑SAR系统
基金资助:
宁夏自治区2020年重点研发计划(东西部合作专项)新立项前引导项目(2020BFG02013);陕西省重点研发计划(2021GY-102);国家自然科学基金面上项目(62176196);陕西省陕西省厅市联动重点项目(2022GD-TSLD-61-3);西安市科技计划项目(21RGZN0012);西安市科技计划项目(23ZDCYTSGG0026-2022);咸阳市重点研发计划(2021ZDYF-GY-0031);陕西省煤田地质集团有限公司科研项目(SMDA-2023CX-14)

Review: brain-inspired intelligent navigation modeling technology and its application

Weibin LI, Chenhao QIN, Tianyi ZHANG, Xin MAO, Donghao YANG, Wenbo JI, Biao HOU, Licheng JIAO

School of Artificial Intelligence, Xidian University, Xi'an 710071, China

Received:2023-11-16 Online:2024-10-28 Published:2024-11-30
Contact: Weibin LI

摘要/Abstract

摘要：

自主导航能力是无人系统所要具备的核心能力。近年来, 无人系统作业的环境日益复杂, 所面临的任务也越来越有挑战性, 这对其自主导航能力提出更高的要求。随着神经科学和人工智能的不断发展, 基于动物大脑空间导航机理的类脑导航技术已经成为一种解决复杂环境下智能导航问题的方案。本文对类脑智能导航技术的发展历程进行梳理与总结, 重点讨论类脑导航的空间认知模型建模技术及其应用技术——类脑同时定位与建图(simultaneous localization and mapping, SLAM)技术及类脑集群导航技术。最后, 总结目前类脑导航技术面临的挑战和不足, 并探讨未来的重要发展方向。

关键词: 类脑导航, 自主导航, 认知地图, 类脑同时定位与建图, 人工智能

Abstract:

Autonomous navigation capability is a core capability for unmanned systems. In recent years, the environment in which unmanned systems operate has become increasingly complex and the tasks they face have become more and more challenging, which puts forward higher requirements for their autonomous navigation capability. With the continuous development of neuroscience and artificial intelligence, the brain-inspired navigation technology based on the spatial navigation mechanism of animal brain has become a solution to the problem of intelligent navigation in complex environments. In this paper, the development history of the brain-inspired intelligent navigation technology is sorted out and summarized, focusing on the spatial cognitive model modeling technology of the brain-inspired navigation and its application technology—the brain-inspired simultaneous localization and mapping (SLAM) technology and the brain-inspired cluster navigation technology. Finally, the challenges and shortcomings of the current brain-inspired navigation technology are summarized, and the important future develop ment directions are discussed.

Key words: brain-inspired navigation, autonomous navigation, cognitive map, brain-inspired simultaneous localization and mapping (SLAM), artificial intelligence (AI)

中图分类号:

V249.32

李卫斌, 秦晨浩, 张天一, 毛鑫, 杨东浩, 纪文搏, 侯彪, 焦李成. 综述: 类脑智能导航建模技术及其应用[J]. 系统工程与电子技术, 2024, 46(11): 3844-3861.

Weibin LI, Chenhao QIN, Tianyi ZHANG, Xin MAO, Donghao YANG, Wenbo JI, Biao HOU, Licheng JIAO. Review: brain-inspired intelligent navigation modeling technology and its application[J]. Systems Engineering and Electronics, 2024, 46(11): 3844-3861.

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时间/年份	研究者	研究内容
1971	O’keefe等	位置细胞被发现在哺乳动物大脑海马体中^[7]
1978	Eccles等	揭示了海马回路的神经环路和神经元网络, 证实海马体是海马回路的一部分, 这是一种被认为与空间导航及记忆有关的神经回路^[8]
1979	O’keefe等	阐述认知地图理论, 提出海马体的某些功能能使动物在场地之间建立联系, 以此来进行空间推断与探测^[9]
1990	Taube等	头朝向细胞被发现存在于海马体中, 这些细胞可用来计算头部朝向信息^[10]
2005	Hafting等	网格细胞被证明存在于内嗅皮层中, 可编码表征动物周围环境, 当动物的位置与代表环境的等边三角形网格上的顶点重合时, 网格单元被激活^[11]
2009	Lever等	边界细胞被证实存在于海马体中, 这类细胞可以为位置细胞提供环境信息, 并补充路径整合信息^[12]
2014	Bjerknes等	证明边界细胞在大鼠导航行为开始时就存在, 而网格细胞成熟速度比边界细胞慢^[13]
2015	Kropff等	探讨内嗅皮层中的速度细胞在动物自我定位中的作用, 即提供关于运行速度的信息, 并调节多种导航细胞的放电频率^[14]
2020	Yi等	证明海马体在动物导航过程中有连接及整合多个与导航相关脑区的作用, 支持空间记忆和语言之间连接的神经机制^[15]
2021	Basu等	除了海马体之外, 动物眶额皮层(orbito frontal cortex, OFC)中的神经元也可以形成空间表征, 在导航过程中持续指向动物的后续目标目的地^[16]
2022	Ormond等	验证动物导航过程中, 海马体创建基于矢量的模型来支持动物的灵活导航, 使得动物具有最优路径规划能力^[17]

时间/年份	模拟细胞	传感器数据	主要内容
2000	位置细胞、海马体	单目视觉	提出空间认知和导航任务过程中海马活动的计算模型^[134]
2004	位置细胞、头朝向细胞	单目视觉	提出一个基于位姿细胞的二维SLAM技术, 称为RatSLAM, 以实现大型拓扑地图实时构建功能^[73]
2005	位置细胞	单目视觉	尝试构建模拟哺乳动物神经系统的仿生机器人控制架构^[135]
2008	位置细胞	全景相机	利用神经网络编码的网格细胞进行路径积分, 为移动机器人提供认知地图构建及导航功能^[136]
2013	位置细胞、头朝向细胞	声纳	受RatSLAM提出基于声纳的BatSLAM技术，实现拓扑地图构建任务^[125]
2016	位置细胞、头朝向细胞	声纳相机	将RatSLAM技术从二维延伸至三维的水下作业场景^[126]
2018	位置细胞、头朝向细胞	三维相机、红外传感器	将情景记忆技术引入到无人系统建图网络中, 使得机器人可以在构建出拓扑地图后存储对应的地图信息, 以便于在需要到达指定位置时进行路径规划^[79]
2019	头朝向细胞、网格细胞	视觉传感器	使用三维导航细胞构建三维四自由度类脑SLAM系统, 称为NeuroSLAM^[80]
2020	头朝向细胞、网格细胞	视觉传感器	提出基于贝叶斯吸引子网络的NeuroBayesSLAM技术, 模拟动物导航时的多源感官融合机制, 来完成认知地图构建任务^[137]
2022	头朝向细胞、网格细胞、位置细胞	视觉传感器	构建基于反赫布学习递归神经网络的空间认知模型, 并采用贝叶斯估计方法进行误差修正, 使得无人系统可整合多源信息完成认知地图构建任务^[138]

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综述: 类脑智能导航建模技术及其应用

Review: brain-inspired intelligent navigation modeling technology and its application

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