A Robot Hand-Eye Calibration Method Based on Convex Relaxation Global Optimization Algorithm

Abstract

The present invention provides a convex relaxation global optimization hand-eye calibration method based on quaternion theory, the method is aimed at when there are deviations in the positive solution of robot kinematics and the external parameter calibration of the camera, the hand-eye calibration algorithm based on nonlinear optimization cannot ensure The problem that the objective function converges to the global minimum is proposed; considering the influence of the angle between the end of the manipulator relative to the motion rotation axis on the accuracy of the calibration equation, firstly use the Random Sample And Consensus (RANSAC) algorithm to The angle between the rotation axes in the calibration data is pre-screened, and then the rotation matrix is ​​parameterized by the quaternion to establish the polynomial geometric error objective function and constraints, and a global optimization algorithm based on linear matrix inequality (linear matrix inequality, LMI) convex relaxation is adopted Solve the globally optimal hand-eye transformation matrix.

Description

Technical field [0001] The invention relates to a robot hand-eye calibration method based on a convex relaxation global optimization algorithm, relates to the technical field of industrial robot vision calibration, and is used in the technical fields of articulated arm coordinate measuring machines, robotic surgery, and service robots. Background technique [0002] In recent years, with the rapid development of science and technology, robots have gradually entered our social life, such as intelligent assembly, autonomous navigation, reverse engineering, welding engineering and other fields have been widely used. As one of the key technologies of robot vision, robot hand-eye calibration has always been a research hotspot in the field of machine vision. In the robot hand-eye vision system, it is often necessary to combine the camera with the robot arm to obtain the relative position information of the target object in the space relative to the robot actuator, and then precisely con...

AI Technical Summary

Problems solved by technology

In 2011, Zhao proposed a method of calculating the hand-eye transformation matrix using convex optimization theory, which improved the robustness of the calculation results, but the solution process is more complicated

Some of the above studies only focus on the parameterization method or solution algorithm of the hand-eye calibration equation, and some only analyze some factors that affect the solution accuracy of the calibration equation, and comprehensively consider the solution algorithm of the calibration equation and the research on error influencing factors There are still relatively few, but in fact, the screening of calibration data and the solution algorithm of the calibration equation will directly affect the solution accuracy of the hand-eye transformation matrix, so it is necessary to study together

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