The Research Of Robot Deburring System Based On Vision And Force Feedback

With the development of robotics technology and the strong support of national policy,robots are more and more widely used in industrial production.In deburring operation,robots also have the advantages of flexibility,flexibility,efficiency and safety compared with CNC machine tools,but in practical application,there are many problems such as teaching points,contact force control and so on.On the basis of investigating the present Jinfeikaida Hub Manufacturing Plant,taking the deburring of automobile hubs as the research background,introducing industrial cameras and force sensors on the basis of industrial robots,the research on online acquisition of processing trajectory based on vision and feedback control strategy of contact force is carried out,and the software and hardware systems are built to complete the test verification.The research contents of this paper are as follows:(1)Aiming at the inefficiency of traditional teaching method in recording robot trajectory points,a vision-based on-line deburring trajectory acquisition method is proposed.Firstly,image preprocessing algorithm is used to eliminate the interference factors in the original hub image;Secondly,the key features of automobile hub are extracted to generate discrete path point coordinates;Finally,image processing coordinate system and robot workpiece coordinate system are calibrated,and a self-defined indirect calibration method is proposed to make the end of the robot completely reproduce the trajectory points obtained from image processing,which is consistent with the actual processing path.(2)To solve the problem of contact force control in deburring process,an adaptive impedance control method for unknown environmental dynamics parameters is proposed.Firstly,the force characteristics in deburring process are analyzed,and the impedance control strategy in force position control of robot is studied.Then,a position-based impedance control model is constructed to control the end position by deburring the normal component of force with real-time feedback.Finally,a fuzzy controller is added to the impedance control model to improve the impedance control system in the absence of environmental dynamics parameters.Response accuracy under informed condition.(3)Planning and adjusting trajectory points on the basis of vision and force feedback,and an inverse kinematics algorithm based on pose separation and matrix orthogonality is proposed.Firstly,the kinematics model of the robot is established and the forward and inverse kinematics process of the robot is analyzed;Then the inverse kinematics algorithm is improved to solve the joint angles according to the position sub-matrix and the rotation sub-matrix respectively,which simplifies the solving process and reduces the computing time;Finally,the trajectory planning of the right-angle space and the joint space is completed at the trajectory points obtained by vision,and the image processing is adjusted based on the force control strategy.The initial trajectory is obtained and the position and attitude of the abnormal contact force point are corrected.(4)The software and hardware parts of the system are built and developed,and the experimental research is completed.Firstly,the hardware equipment of the system is installed and completed:ABB-IRB1600 six-degree-of-freedom manipulator and its control accessories,industrial camera and lens,force sensor and data acquisition card;Secondly,software systems such as image acquisition and processing,force information acquisition and processing and robot control are developed and debugged;Finally,the contour trajectory tracking test and adaptive impedance control test are designed to verify the effectiveness of the proposed method.