A static calibration method for robot hand and eye

Abstract

The invention relates to a robot hand and eye static calibration method for resolving a robot hand and eye matrix. The method includes the following steps: firstly establishing a classic camera geometric imaging model, obtaining internal reference of a camera; secondly an optical measurement device separately determining how a measurement coordinate system converts with a world coordinate system or a robot rear end flange coordinate system; conducting one-time imaging on a calibration board to as to obtain an external reference of the camera, i.e., how a camera coordinate system converts with a calibration board coordinate system, such that the robot hand and eye relationship can be fast computed. The method overcomes complex resolving process of traditional methods, and robot does not need to move in the whole calibration process, so that static calibration is achieved and low calibration precision caused by errors such as robot connecting pole parameters of the positive vision method is prevented. According to the invention, the method is characterized by reliability, simple computing and high precision. The method is also suitable to the converting between the camera and any base station, is not only applicable to robot rear ends, and can be expanded in terms of fields of application.

Description

technical field [0001] The invention relates to a robot hand-eye calibration method, in particular to a static calibration method which can quickly solve the robot hand-eye relationship. Background technique [0002] In practical applications, visual sensors (such as cameras) are often fixed on the end effector of the robot, that is, the "eye" is installed on the "hand" to form a hand-eye relationship. This allows the robot to measure the pose relationship between the target and the camera in real time through the camera, so as to determine the next movement of the robot. Before that, hand-eye calibration must be performed. [0003] The commonly used calibration methods at home and abroad are mainly divided into three categories: traditional calibration methods, self-calibration methods and active vision calibration methods. The traditional calibration method has high precision but the calculation process is complicated; the self-calibration method is not robust; the active...

AI Technical Summary

Problems solved by technology

The traditional calibration method has high precision but the calculation process is complicated; the self-calibration method is not robust; the active vision calibration method is simple in calculation and strong in robustness, but requires a high-precision active vision platform, and the robot due to processing, installation, etc. Error, the ideal structure parameters usually have a large deviation from the actual, so the accuracy of this method is not high

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