Information processing method and device

Abstract

The invention discloses an information processing method and equipment. The information processing method is applied to information processing equipment. The information processing equipment comprises a three-dimensional map which is created for a specific space environment in advance, and the terminal equipment positioned in the specific space environment can determine the position of its own according to the three-dimensional map. The method comprises the following steps: obtaining an image shot by the terminal equipment; extracting feature points in the image, and obtaining feature descriptors used for representing the feature points; on the basis of the position of the terminal equipment and depth information in the image, obtaining a three-dimensional position of each feature point; determining a minimum spatial node in the specific space environment; according to the obtained three-dimensional position of each feature point, determining a minimum spatial node where each feature point belongs to so as to carry out clustering to obtain all feature descriptors contained in the minimum spatial node; and on the basis of a specific data structure, managing each minimum spatial node.

Description

technical field [0001] The present invention relates to an information processing method and device, more specifically, to an information processing method and device capable of conveniently and quickly managing and updating a feature library. Background technique [0002] For an unknown environment, a 3D map can be pre-built by means of real-time localization and map construction (Simultaneous Localization and Mapping, SLAM) technology. In an environment where a map has been built, a mobile terminal device (such as a robot) obtains its own positioning information by matching the feature points in the image it captures with the feature points of the global map. In robot self-localization, since the scene of the robot is constantly changing, and the feature database of the global map has a large amount of data, it is very important to match the feature points in the image captured by the robot itself with the feature points in the feature database of the global map. time con...

AI Technical Summary

Problems solved by technology

In robot self-localization, since the scene of the robot is constantly changing, and the feature database of the global map has a large amount of data, it is very important to match the feature points in the image captured by the robot itself with the feature points in the feature database of the global map. time consuming

In addition, the operation of updating the feature library of the global map based on the images taken by the robot itself is also very time-consuming.

In addition, extending the feature library of the global map may involve complex data manipulation

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