Research On Intelligent Grabbing Technology Of Industrial Robot

With the concept of industrial manufacturing intellectualization being put forward,the industrial revolution aiming at this goal began to spread all over the world.In the traditional automatic production system,the introduction of machine vision to make the production system more intelligent has become a research center point.This paper studies the intelligent grasping system of industrial robots in industrial production,understands the development and research focus of the current intelligent grasping system of industrial robots,mainly studies the application of machine vision in industrial robots,and studies some key technologies such as image preprocessing,recognition and positioning,and kinematics of robotic arms.Finally,ABB industrial machine is used as the research object.Based on this,an industrial robot grasping system based on machine vision has been built.In the course of the research,it mainly includes the following contents:Firstly,the traditional Canny algorithm is improved.Image processing is an important part of machine vision.This paper studies image preprocessing technology.The advantages and disadvantages of Gauss filter,mean filter,median filter and bilateral filter are analyzed and compared.When studying image edge extraction operator,an improved scheme is proposed to overcome the shortcomings of traditional Canny operator and applied to the edge extraction of workpiece.Then,for the target recognition and location problem,the SURF algorithm is used to complete the target recognition work.The location principle of monocular vision and the calibration method of camera are described.Zhang Zhengyou calibration method is used to complete the calibration of the camera,and the internal and external parameters of the camera are obtained.The method of feature matching is used in monocular location.The depth information of the target is calculated by decomposing the essential matrix,and the centroid coordinates of the target are extracted.After that,according to the kinematics principle of industrial robot manipulator,utilizing D-H method to model the robot,and using ADAMS software to carry out kinematics simulation,the established forward kinematics model was verified.A soft competitive ART-RBF learning algorithm is used to solve the inverse kinematics of the manipulator.In order to clearly understand the working range of the robot,the threedimensional workspace of the manipulator is obtained by using MATLAB.Finally,the laboratory equipment is used to build a vision-guided industrial robot system to complete the grasping test of the model.In this paper,a vision-guided industrial robot system is built,and machine vision system and industrial robot system are studied.The rationality of the built system is confirmed by tests,which supplies a reference for the design of industrial robot system based upon vision in the real manufacture.