Point cloud relative pose estimation method based on three-dimensional curve matching

Abstract

The invention discloses a point cloud relative pose estimation method based on three-dimensional curve matching. The method includes the steps that the edge contours of two frames of input point clouds are extracted, and three-dimensional point sets (img file='dest_path_image 002. TIF' wi='13' he='16' / ) and (img file='dest_path_image 004. TIF' wi='14' he='16' / ) on behalf of the three-dimensional edge contour curve are obtained; according to the three-dimensional point sets (img file='915081 dest_path_image 002. TIF' wi='14' he='17' / ) and (img file='301063 dest_path_image 004. TIF' wi='14' he='16' / ), orderly point sets (img file='dest_path_image 006. TIF' wi='26' he='20' / ) are obtained through extraction; each orderly point set (img file='dest_path_image 008. TIF' wi='14' he='20' / ) or (img file='dest_path_image 010. TIF' wi='15' he='21' / ) is decomposed, each subset is on behalf of one arc section after decomposition, and a feature description vector of each arc section is established; the feature description vectors of the edge curve arc sections of the two frames of point clouds are matched to establish a matching relation, and the relative pose transformational matrixes (img file='dest_path_image 012. TIF' wi='39' he='18' / ) of the two frames of point clouds are calculated. The point cloud relative pose estimation method based on three-dimensional curve matching does not depend on an initial pose, only an environmental contour is used for matching, and the relative pose is estimated; only the edge point sets are processed, and calculation is lowered; the method can be suitable for chaff interferent in which point clouds exist.

Description

technical field [0001] The invention relates to the field of three-dimensional environment reconstruction, in particular to a point cloud relative pose estimation method based on three-dimensional curve matching. Background technique [0002] Existing point cloud relative pose estimation methods are mainly divided into two categories. One type is based on point cloud feature matching. The disadvantage is that it is greatly affected by the change of point cloud density, and the difference in density will directly lead to an increase in error probability. Another type of direct matching based on point clouds has the disadvantage of relying on the initial pose and having a large amount of computation. [0003] For the matching of three-dimensional curves, the existing methods are mainly based on convolution, which is difficult to apply to the matching of multiple curves to multiple curves. Contents of the invention [0004] The purpose of the present invention is to overcom...

AI Technical Summary

Problems solved by technology

One type is based on point cloud feature matching, the disadvantage is that it is greatly affected by the change of point cloud density, and the difference in density will directly lead to an increase in error probability

Another type of direct matching based on point cloud, the disadvantage is that it depends on the initial pose and has a large amount of calculation

[0003] For the matching of three-dimensional curves, the existing methods are mainly based on convolution, which is difficult to apply to the matching of multiple curves to multiple curves.

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