Monocular vision SLAM algorithm based on semi-direct method and sliding window optimization

Abstract

The invention discloses a monocular vision SLAM algorithm based on a semi-direct method and sliding window optimization. The monocular vision SLAM algorithm comprises the steps that 1) color image frames acquired by a monocular color camera are uploaded to a computer through a third-party image acquisition interface; 2) the algorithm initialization process is performed, the camera pose transformation relationship between the two initial frames is established, initial map points are established, the two initial frames act as key frames and the initial map points are inserted in the map and thesliding window; and 3) the map points observed in the previous frame are projected to the current frame, and bundle set optimization computation based on the luminosity error is performed between thetwo frames of images so as to obtain the camera pose transformation between the two frames to track the movement of the camera. The monocular vision SLAM algorithm has faster operation speed, and theused equipment is simple and easy to calibrate so as to have higher practical value and wider application occasions.

Description

technical field [0001] The present invention relates to the technical field of simultaneous localization and mapping (SLAM) algorithms in computer vision, in particular to a monocular vision SLAM algorithm based on semi-direct method and sliding window optimization. Background technique [0002] With the vigorous development of emerging technology fields such as robotics, autonomous driving, augmented reality and virtual reality all over the world, the key technology behind it, simultaneous localization and mapping (SLAM) technology, has also received more and more attention from the scientific research community and industry's attention. Simultaneous positioning and mapping algorithms refer to the ability to continuously track the trajectory of a moving robot or sensor carrier in a completely unknown environment, and at the same time establish a three-dimensional perception of the environmental map. The above-mentioned fields have high technical requirements for SLAM techn...

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to overcome the problem that the calculation speed and accuracy are difficult to balance in the existing monocular vision SLAM algorithm, and provide a monocular vision SLAM algorithm based on semi-direct method and sliding window optimization, which only uses feature points Compared with the feature point-based SLAM method of calculating feature descriptors, this algorithm avoids the disadvantage of spending a lot of computing time to extract feature point descriptors, and has more advantages. fast running speed