Affiliation:
1. Faculty of Information Technology Beijing University of Technology Beijing China
2. Beijing Key Laboratory of Computing Intelligence and Intelligent System Beijing China
Abstract
AbstractThe 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.
Funder
Beijing Municipal Natural Science Foundation
National Natural Science Foundation of China
Publisher
Institution of Engineering and Technology (IET)