Point cloud splicing method based on precision control field and point cloud feature similarity

Abstract

The invention discloses a point cloud splicing method based on a precision control field and point cloud feature similarity. The method comprises: a reference measurement system constructing a control field and a global coordinate system, a sensor collecting mark points at an initial pose, and obtaining a source point set; the sensor collecting the mark points at the next pose to obtain a target point set; respectively solving an initial conversion relation RT0 between the source point set and the target point set; performing translation rotation on the target point set by utilizing the RT0, solving an overlapping region, and solving a conversion relation RT1 between the target point set and a global coordinate system based on point cloud similarity; searching candidate homonymy points by using the RT1 and each contrast point; continuously constructing a target function jointly constrained by the precision control field and the point cloud similarity, and iterating to obtain RT2; obtaining the conversion relation of all poses, and completing overall scanning. According to the scheme, the existing splicing process is optimized, and the requirement for the number of mark points is reduced; practicality, flexibility and efficiency of large complex object point cloud splicing are improved.

Description

technical field [0001] The invention relates to the field of three-dimensional measurement, in particular to a point cloud splicing method based on precision control field and point cloud feature similarity. Background technique [0002] Point cloud stitching is an important part of the three-dimensional measurement of large objects, and its purpose is to accurately unify the point clouds scanned multiple times (multiple fields of view) into the same coordinate system. There are three types of commonly used point cloud stitching methods: point cloud similarity stitching, marker point stitching, and precision control field stitching. [0003] The point cloud feature similarity stitching method uses the geometric topology similarity of the overlapping parts of adjacent field of view point clouds to achieve stitching. Its advantage is that it does not need to arrange marker points on the surface of the measured object, and it is convenient and flexible in actual use. However, ...

AI Technical Summary

Problems solved by technology

However, the precision control field splicing method requires more than 3 marker points for each field of view. For large and complex objects, a large number of marker points need to be laid out. In actual use, not only the workload is heavy, but also the flexibility is poor and the operation is inconvenient.

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