Neuromorphic inspiring robot cognitive map building method

A cognitive map and construction method technology, applied in the direction of manipulators, program-controlled manipulators, manufacturing tools, etc., can solve the problems of insufficient robustness, mismatching, low efficiency and accuracy of closed-loop detection, etc.

Active Publication Date: 2020-07-07
DALIAN UNIV OF TECH
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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 acc

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  • Neuromorphic inspiring robot cognitive map building method
  • Neuromorphic inspiring robot cognitive map building method
  • Neuromorphic inspiring robot cognitive map building method

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Embodiment Construction

[0050] The method will be described in detail below in conjunction with the accompanying drawings and examples.

[0051] Application scenario: The present invention can be applied to building cognitive maps of robots in indoor and outdoor environments. The robot obtains the surrounding environment information through the camera and estimates its own motion, and then builds a cognitive map, which lays the foundation for the robot to perform subsequent navigation tasks. In this example, we use the KITTI open source outdoor dataset.

[0052] figure 1 It shows the flow chart of the brain-inspired robot cognitive map construction method. First, the robot explores the environment, obtains the environment information around the robot through the camera, obtains the robot's own motion information through the visual odometer, and then inputs the angular velocity and linear velocity into the head orientation. Cell module and position cell module; input the image information to the vi...

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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...

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Application Information

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IPC IPC(8): B25J9/16
CPCB25J9/1602B25J9/1697
Inventor 刘冬吕志邹强丛明
Owner DALIAN UNIV OF TECH
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