Research On Key Algorithm Of Scara Robot Vision System

Industrial robots are the important carrier of "industrial 4.0" which promote China's manufacturing transformation and upgrading.More sophisticated sensors and decision-making system can greatly enhance the level of robot's intelligence.The robot vision system is one of them.Industrial applications require robotic vision algorithms with greater adaptability,higher accuracy,higher robustness,and higher performance.In order to meet the above requirements,much common used algorithms such as the image distortion correction algorithm,geometric feature recognition and location correlation algorithm and Scara robot vision calibration algorithm are deeply studied.Some optimized solutions are proposed,such as improving the stability of distortion correction result and simplifying application process.The performance of linear detection and circle detection in strong interference conditions was improved.What's more,the efficiency of template matching algorithm is improved and the visual calibration algorithm under a variety of camera installation is proposed.The main work,innovation or features of this dissertation are summarized as follows:● To avoid the coupling of internal and external parameters which can lead to the instability of the result,an image distortion correction algorithm based on collinear points is proposed.More than that,the new algorithm increases the convenience of the use.● The sub-pixel edge detection algorithm is studied and analyzed.The method of determining the accuracy of Gaussian fitting method,Zernike moment method and interpolation method is proposed by comparing the fitting distance,and the experimental verification is carried out.● Hough transform algorithm is used calculate the initial value for distance-weighted iterative fitting.Hough transform is proposed to improve the anti-jamming ability of straight line fitting,and the distance-iterative method is used to improve the precision of straight line fitting.● A double threshold maximum interclass variance algorithm can help obtain five different gray levels of the image,and enhance the scene adaptability of the module.● A template matching algorithm which use the improved Haustorff distance and gradient difference to make two-level decisions is proposed.The search flow of the algorithm optimized to improve the efficiency of template matching to meet the needs of industrial production.● After a lot of research,the camera fixed installation automatic calibration algorithm is put forward,which not only solved the problem of loss of accuracy resulted by manual calibration,but also greatly simplifies the calibration process.Many experiments show that the calibration error is less than 0.2 pixels.In order to meet the needs of complex and diverse industrial applications,the key algorithms of Scara robot vision system are integrated,improved and encapsulated.This program can realize rapid secondary development,shorten the development cycle and improve the quality of the system.A number of projects have proved that the robot vision system equipped by algorithms presented in the paper has much application value and strong market competitiveness.