Monocular SLAM initialization method

Abstract

The invention discloses a monocular SLAM initialization method. The method comprises: feature points of a template picture are extracted, poses of the camera and the template picture are transmitted to a configuration file; collecting a picture containing a template as a first frame of picture; extracting ORB feature points of the first frame of picture and matching the ORB feature points with thefeature points on the template picture; a homography matrix is calculated; projecting known points defined in the template picture into the first frame of picture by using a homography matrix; calculating the pose of the first frame of picture relative to the template picture, and finally calculating the spatial coordinates of the feature points reserved in the feature points, matched with the first frame of picture, on the template picture according to the established self-defined coordinate system, and taking the spatial coordinates as corresponding map points in the SLAM map to complete initialization. Compared with an existing method, the rapid initialization method provided by the invention has higher precision and faster initialization speed, and greatly reduces the calculation costof initialization.

Description

Technical field [0001] The invention belongs to the technical field of computer vision and image processing, and particularly relates to a monocular SLAM initialization method. Background technique [0002] Simultaneous localization and map creation is also called SLAM (Simultaneous Localization and Mapping). Simply put, the robot explores a static unknown environment when its position is uncertain, and establishes a map and localization technology at the same time. Its application platform is also very extensive, from home sweeping robots to unmanned vehicles driving on the road, all cannot do without the support of SLAM technology. Due to the low cost of monocular cameras, the development of monocular SLAM is very hot. [0003] The monocular camera cannot obtain the depth information of the scene in the image, so monocular SLAM has an initialization process to restore the scene, but the restored scene still has a scale problem, that is, the unit of the scene depth is not known. ...

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to provide a monocular SLAM initialization method, which overcomes the problems that the traditional monocular SLAM initialization takes a long time, the accuracy of the map is not high enough, and the real scale of the scene cannot be calculated.

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