基于光刀图像的机器人示教纠偏方法

为了解决机器人辅助在线检测系统示教过程中效率低、人为干预多的问题,针对孔类特征,提出一种通过处理光刀图像获取机器人位姿纠正参数的方法。在该方法中,纠偏过程按照将图像光刀线调整为水平方向、将被测特征调整至图像中央、根据不同特征调整最优扫描方向3个步骤进行。根据光刀图像可以求出测量坐标系与被测特征的位姿关系,并得到该位姿与理想测量位姿的偏差。经过坐标变换即可得到在机器人基坐标系下的调整参数。另外,可利用电脑控制机器人运动,从而实现了纠偏过程的自动化。实验结果表明,该方法可将初始的示教位姿修正为理想位姿,且比传统方式效率更高。

Deviation correction method of robot teaching based on light stripe images

To solve the problems of low efficiency and more human intervention in the teaching process of robot-aided online detection system,a method of obtaining robot pose correction parameters by processing light stripe images was proposed for the hole-features.In this method,the correction process was carried out in three steps:adjusting the light stripe line to the horizontal direction,adjusting the measured features to the center of the image,and adjusting the optimal scanning direction according to different features.According to the light stripe images,the relationship between the coordinate system and the measured feature was found,and the difference between the position and the ideal measurement position could be obtained.After coordinate transformation,the adjustment parameters were got in the basic coordinate system of the robot.In addition,the computer was used to control the motion of the robot,thus the automation of the rectification process was realized.The experimental results showed that the method could modify the initial teaching posture to the ideal one,and was more efficient than the traditional one.