Research On Industrial Robots Self Calibration Technology

With the development of industrial intelligent manufacturing,the requirements for the rapidity and accuracy of robot positioning accuracy are more stringent.However,the collision,wear and tear in robot operation,as well as the error of robot parts processing and assembly have become the factors that affect the positioning accuracy of robot.Various measuring instruments used in traditional calibration methods are expensive,the calibration process is cumbersome,and specialized technicians are required to operate,and the calibration results are easily affected by subjective factors.In order to meet the calibration requirements of the positioning accuracy of industrial robots,simplify the calibration steps and improve the calibration speed,a robot self-calibration system based on the depth camera is designed in this paper,and the experimental verification is carried out on the robot self-calibration experimental platform.Robot self-calibration system focuses on the following aspects:(1)First of all,through research to establish the basic model based on robot kinematics Paul method,based on robot joint coordinate system to the base coordinate system is constructed in the mapping relationship between the end of the robot joint position,derived the equations describing robot end space position posture.Based on the parallax principle and pinhole model,the camera imaging model in binocular stereo vision system is analyzed,and the transformation equation between camera coordinate system and pixel coordinate system is constructed.(2)The second is based on the comprehensive analysis of the differential movement principle and the theory of partial differential equation of robot kinematics model and the posture error of adjacent linkage between the coordinate system is deduced equation of kinematics analysis of robot kinematics model parameters and the robot end function relation between positioning error,further to the end of the robot posture error model is deduced.(3)Based on the point cloud image data collected by the binocular stereo vision system,the feature screening algorithm based on data density clustering is adopted to remove the abnormal points in the point cloud image data,and the final feature parameters are obtained by feature fitting of the point cloud image data through filtering and denoising algorithm.(4)The method of describing the correlation between robot positioning error and robot pose is discussed,and a spatial fixed-point interpolation compensation method based on the grid model of robot workspace is proposed.The robot self-calibration system based on depth camera designed in this paper is a new robot self-calibration method with a wide range of applications.It simplifies the robot calibration operation,improves the absolute position accuracy of the robot,and meets the needs of modern industry for the speed and accuracy of robot positioning.