Hand-eye calibration parameter identification method, hand-eye calibration parameter identification system based on differential evolution algorithm and medium

Abstract

The invention provides a hand-eye calibration parameter identification method, a hand-eye calibration parameter identification system based on a differential evolution algorithm and a medium. The hand-eye calibration parameter identification method comprises the following steps of moving a robot end of a robot vision system to different poses to collect robot joint data and camera image data; separately calculating a pose matrix of the robot end relative to a robot base coordinate system and a pose matrix of a calibration board relative to a camera coordinate system; defining a rotary component calibrated error function and a translational component calibrated error function; determining and solving a multi-target optimization function of a hand-eye calibration problem; and separately calculating calibrated errors of a rotating part and a translational part of the robot vision system and verifying and identifying the optimum hand-eye calibration parameter. The global optimality of a calibration result can be acquired, the acquired calibration result falls onto a special Euclidean group SE (3), and additionally introduced calculation of calibrating orthogonalization of the acquiredrotating matrix.

Description

technical field [0001] The present invention relates to the field of robot vision, in particular to a method, system and medium for identifying hand-eye calibration parameters based on a differential evolution algorithm. Background technique [0002] The robot vision system is one of the common control systems in the field of robot control. The vision system can provide the robot with rich environmental information, guide the robot to make correct decisions, and complete predetermined actions. In order to analyze the image data captured by the vision system and the three-dimensional motion data in the robot workspace under a unified coordinate frame, it is necessary to perform hand-eye calibration on the robot vision system to obtain the transformation between the vision sensor coordinate system and the robot end coordinate system relation. [0003] There are many methods for hand-eye calibration of the robot vision system, and the more commonly used convex optimization me...

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Problems solved by technology

However, the calibration matrix obtained by this method may not fall on the special Euclidean group SE(3), and the calibration results need to be processed by orthogonalization before use, and it cannot be strictly proved that the processed calibration matrix is ​​still global optimal

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