Physiological studies reveal that rats rely on multiple spatial cells for spatial navigation and memory. In this paper, we investigated the firing mechanism of spatial cells within the entorhinal-hippocampal structure of the rat brain and proposed a spatial localization model for mobile robot. Its characteristics were as follows: on the basis of the information transmission model from grid cells to place cells, the neural network model of place cells interaction was introduced to obtain the place cell plate with a single-peaked excitatory activity package. Then the solution to the robot's position was achieved by establishing a transformation relationship between the position of the excitatory activity package on the place cell plate and the robot's position in the physical environment. In this paper, simulation experiments and physical experiments were designed to verify the model. The experimental results showed that compared with RatSLAM and the model of grid cells to place cells, the positioning performance of the model in this paper was more accurate, and the cumulative error in the long-time path integration process of the robot was also smaller. The research results of this paper lay a foundation for the robot navigation method that mimics the cognitive mechanism of rat brain.
生理学研究发现，大鼠进行空间导航和记忆依赖多种空间细胞。基于此，本文对鼠脑内嗅—海马结构内空间细胞的放电机制进行研究，提出了一种移动机器人空间定位模型。其特点为：在网格细胞到位置细胞信息传递模型的基础上，引入位置细胞相互作用的神经网络模型得到具有单峰兴奋活动包的细胞板。通过建立兴奋活动包在细胞板上的位置与机器人在物理环境中的位置之间的转换关系，实现对机器人位置的解算。本文设计了仿真实验和物理实验对模型进行验证。实验结果表明：相较于RatSLAM和网格—位置映射模型，本文模型的定位性能更加精确，且在机器人长时间的路径积分过程中所产生的累积误差也更小。本文研究成果为仿鼠脑认知机制的机器人导航方法奠定了基础。.
Keywords: Entorhinal-hippocampal; Grid cells; Path integration; Place cells; Spatial localization.