Point cloud registration method based on hand-eye calibration

Abstract

The invention belongs to the field of three-dimensional measurement, and specifically discloses a point cloud registration method based on hand-eye calibration. The point cloud registration method includes the steps: driving a measuring device by a tail end of a robot to move twice, and respectively obtaining a transformation matrix of a coordinate system at the tail end of the robot and a transformation matrix of a coordinate system of the measuring device during two times of movement; calibrating an equation according to a hand-eye calibration equation; solving a transformation matrix from arobot tail end coordinate system to a measuring device coordinate system; obtaining a transformation matrix from a robot base coordinate system to a measuring device coordinate system; according to the transformation matrix, converting the to-be-measured object measurement point cloud obtained by the measurement device into a robot base coordinate system to complete point cloud coarse registration between the measurement point cloud and the model point cloud; and finally completing point cloud fine registration through the relationship between matching point pairs in the measurement point cloud and the model point cloud under the robot base coordinate system. Marking points do not need to be pasted on the surface of a measured object in the whole process, and the point cloud registrationprocess is simplified, and point cloud registration during measurement of a high-temperature object can be achieved.

Description

technical field [0001] The invention belongs to the field of three-dimensional measurement, and more specifically relates to a point cloud registration method based on hand-eye calibration. Background technique [0002] Point cloud registration is the process of integrating point cloud data under different viewing angles into a specified coordinate system through rigid transformations such as rotation and translation, and is mainly used for 3D reconstruction of the measured object. Point cloud registration includes coarse registration and fine registration: coarse registration is a registration method for quickly estimating a rough point cloud registration matrix when the source point cloud and the target point cloud do not know any initial relative positions at all. ; Fine registration is a registration method that uses the initial transformation matrix in the rough registration to calculate a more accurate solution through methods such as the iterative closest point algori...

AI Technical Summary

Problems solved by technology

[0003] The existing point cloud registration method needs to paste marker points on the surface of the measured object, and realize the coarse registration of the point cloud through the marker points between two adjacent point clouds, but it is time-consuming and laborious to paste marker points on the surface of the measured object , which is not conducive to the construction of an automated three-dimensional measurement system, and for high-temperature workpieces, it is unrealistic to paste mark points on its surface

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