基于大鼠脑内嗅-海马工作机制的实时认知图谱构建方法

IF 1.2 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Yishen Liao, Naigong Yu
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引用次数: 0

摘要

内嗅-海马体结构中空间细胞的放电被认为能够形成对环境的认知地图。受大鼠大脑空间认知机制的启发,作者提出了一种基于内嗅-海马工作机制的实时认知地图构建方法。首先,基于大鼠脑的生理特性,构建了内嗅-海马CA3神经计算模型进行路径整合。然后,利用单元板与真实环境之间的变换关系求解机器人的位置。路径积分不可避免地会产生累积误差,需要进行闭环检测和位姿优化来消除误差。针对RatSLAM算法姿态优化速度慢的问题,提出了一种基于多层CA1位置单元的姿态优化方法,提高姿态优化速度。为了验证该方法,作者设计了仿真实验、数据集实验和物理实验。实验结果表明,与其他类脑SLAM算法相比,本文方法在路径整合精度和地图构建速度方面具有突出的性能。因此,作者的方法可以赋予移动机器人在复杂和未知环境中快速准确构建认知地图的能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A real-time cognitive map construction method based on the entorhinal-hippocampal working mechanism of the rat's brain

A real-time cognitive map construction method based on the entorhinal-hippocampal working mechanism of the rat's brain

The firing of spatial cells in the entorhinal-hippocampal structure is believed to enable the formation of a cognitive map for the environment. Inspired by the spatial cognitive mechanism of the rat's brain, the authors proposed a real-time cognitive map construction method based on the entorhinal-hippocampal working mechanism. Firstly, based on the physiological properties of the rat's brain, the authors constructed an entorhinal-hippocampal CA3 neurocomputational model for path integration. Then, the transformation relationship between the cell plate and the real environment is used to solve the robot's position. Path integration inevitably generates cumulative errors, which require loop-closure detection and pose optimisation to eliminate errors. To solve the problem that the RatSLAM algorithm is slow in pose optimisation, the authors proposed a pose optimisation method based on a multi-layer CA1 place cell to improve the speed of pose optimisation. To validate the method, the authors designed simulation experiments, dataset experiments, and physical experiments. The experimental results showed that compared to other brain-like SLAM algorithms, the authors’ method possesses outstanding performance in path integration accuracy and map construction speed. As a result, the authors’ method can endow mobile robots with the ability to quickly and accurately construct cognitive maps in complex and unknown environments.

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来源期刊
Cognitive Computation and Systems
Cognitive Computation and Systems Computer Science-Computer Science Applications
CiteScore
2.50
自引率
0.00%
发文量
39
审稿时长
10 weeks
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