Research On The Compliant Control Algorithm For Shaft Hole Assembly Industrial Robot

The robot shaft hole assembly technology has always been an important issue in the research of industrial robot application technology.Industrial robots often suffer from pin jams and even wedges during shaft hole assembly operations,which can damage the assembly parts and the robot body,and have a serious impact on production safety issues.In order to avoid the jamming phenomenon of industrial robots in the shaft hole assembly operation,this paper studies and designs an active compliant RBF neural network robust controller to realize the deblocking operation of the shaft hole assembly.The paper firstly analyzes and studies the related theory of compliance technology in depth,and then describes the basic theories of the robot,including the robot dynamic model,the kinematic model,and the force control.The force is measured.In this paper,the zero-point calibration of the six-dimensional force sensor is performed and error compensation is performed.Then the axle hole assembly is modeled,and the movement modal analysis of the axle hole assembly is performed for the model,and the modality of the whole bolt movement process in the assembly process is obtained,and the maximum inclination angle of the allowable pin insertion hole is obtained.The mechanical analysis was performed for the one-point jam resistance and two-point jam resistance that appeared in the insert pin hole,and the conditions of one-point jam resistance and two-point jam resistance were obtained,and the tilt angle and insertion depth of the two-point contact pin were simulated.The function of the curve diagram,the final establishment of the shaft hole assembly to remove the overall solution.At last,this paper designs an active compliant RBF neural network robust controller,simulates the controller,and verifies the simulation results,which proves the rationality of the controller.