Neuromorphic inspiring robot cognitive map building method

Abstract

The invention discloses a neuromorphic inspiring robot cognitive map building method, and belongs to the technical field of robot environment cognition and motion navigation. A cognitive map can be built to assist a robot in navigation. Firstly, the robot acquires image information surrounding the environment through a robot. Then, a visual odometer processes the image information to obtain the rotating angle speed and the line speed of the robot, the rotating angle speed and the line speed are input to a head orientation cell model and a position cell model, and cognition of the robot to theposition is formed. A visual feature extraction module processes images through a deep learning network and a principal component analysis algorithm, and outside cognition information of the robot tothe environment is obtained; and finally, information is combined through the experience map, and the map is updated through the closed-loop detection and update algorithm. By means of the method, theproblems that in the current neuromorphic cognitive map building method, the robustness of a visual odometer is poor, and accuracy of closed-loop detection is not high enough can be solved, detectionand updating to closed-loop points in the environment can be completed, and global consistency can be guaranteed.

Description

technical field [0001] The invention belongs to the field of brain-inspired computing and intelligent robot navigation, and relates to an experience map construction method that combines a visual odometer and a hippocampus spatial cell computing model to form a robot's spatial cognition, and uses a deep learning network for closed-loop detection. Complete the detection and update of closed-loop points in the environment to ensure global consistency. This method aims to solve the problems of poor robustness of visual odometry and insufficient accuracy of closed-loop detection in current brain-inspired cognitive mapping methods. Background technique [0002] Putting the robot into an unknown location in an unknown environment, is there a way for the robot to draw a complete map of the environment step by step while moving, that is, SLAM. In SLAM problems, the pose estimation of the robot itself is very important. Traditional pose estimation methods include odometer technolog...

AI Technical Summary

Problems solved by technology

[0007] The purpose of the present invention is to solve the problem of poor visual odometer effect, insufficient robustness, and low efficiency and accuracy of closed-loop detection in complex and changeable environments in existing bionic-based mapping models, which easily cause mismatching question

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