Robot 3D vision hand-eye calibration method

Abstract

The invention discloses a robot 3D vision hand-eye calibration method. The method comprises the steps that S1, a posture, relative to robot base coordinates, of a robot flange and a posture, relativeto a 3D sensor coordinate system, of a calibration plate are obtained; S2, a rotation matrix, relative to a robot base coordinate system, of the 3D sensor coordinate system is calculated; S3, multiplecoordinate data of workpiece grasping points in the 3D sensor coordinate system and corresponding multiple coordinate data in the base coordinate system of a robot base are obtained; S4, transformational relations of X coordinate axes, Y coordinate axes and Z coordinate axes of the 3D sensor coordinate system and the robot base coordinate system are calculated. Compared with traditional hand-eyecalibration that only one transformational matrix is used for describing transform from the 3D sensor coordinate system to the robot base coordinate, by means of the robot 3D vision hand-eye calibration method, the transformational relations of positions and postures from a 3D sensor to the robot base coordinates are obtained respectively, compared with the prior art, the method is more flexible,the precision requirements in actual engineering application can be better met, and the hand-eye calibration precision is improved.

Description

technical field [0001] The invention belongs to the technical field of robot 3D vision calibration, and in particular relates to a robot 3D vision hand-eye calibration method. Background technique [0002] The rapid advancement of intelligent manufacturing has led to the rapid development of multi-joint robots. Industrial robots have participated in various fields of industrial manufacturing and production, and have become an indispensable role in the process of factory automation and intelligence. Machine vision endows robot eyes with advanced image processing, 3D data analysis algorithms, and the application of artificial intelligence technology, so that robot actions are no longer limited to point-to-point movements or established trajectories obtained through teaching, but under the guidance of vision For more flexible and intelligent actions, the application in high-precision detection and workpiece grasping and positioning is in the ascendant. Compared with traditiona...

AI Technical Summary

Problems solved by technology

However, in actual industrial applications, due to errors in the calibration of the coordinate system of the 3D sensor itself, system errors in the robot, calculation errors in the transformation matrix and some other factors, only one matrix is ​​used to express the entire 3D sensor coordinate system and the robot base The relationship between the standard system, the accuracy obtained is often difficult to meet the requirements

For example, the 3D robot proposed by [Tsai R Y, Lenz R K. A new technique for fully autono mous and efficient 3D robotics hand / eyecalibration [J]. IEEE Transactions on Robotics and Automation, 1989,5(3):345-358] The hand-eye calibration method is divided into two steps to solve the hand-eye transformation matrix, first solve the rotation matrix, and then use the calculated rotation matrix to solve the translation vector, so the error calculated by the rotation matrix is ​​also brought into the translation vector, resulting in insufficient accuracy

Another example is the robot 3D vision hand-eye calibration module in the Halcon machine vision software. The root mean square error of the translation transformation part obtained through experimental testing is about 2 mm, which cannot meet the accuracy requirements of actual industrial applications.

[0006] In addition, some current hand-eye calibration methods have high requirements on the physical accuracy of manipulators, calibration boards and other auxiliary facilities during the calibration process, which increases the cost of calibration.

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