| With the rapid development of industrialization,the application of robots is becoming popular,and one of the faster development is the direction of robotic grinding,which can not only improve the quality of grinding,but also greatly improve the efficiency of grinding,but the difficult point for grinding robots is one is the force control of grinding robots,which can control the grinding force,so as to get the polished parts with good surface quality;the second is the motion control of grinding robots,which can make the In this paper,the force control and motion planning of the grinding robot are studied in order to successfully apply the grinding robot to weld grinding.The research content of the paper can be summarized as follows:The overall architecture of the robotic grinding system is conceived,weld defects are introduced and a force analysis of weld grinding is performed,followed by the dynamics between the robot end and the environment and the underlying impedance control model.Finally,the system coordinate system is established and the coordinate transformations are analysed,the forward and reverse kinematics of the robot are analysed and its motion planning is modelled.The force control of the grinding robot was investigated and gravity compensation of the six-dimensional force sensor was completed to enable the six-dimensional force sensor to obtain accurate grinding forces.In order to understand the effect of different parameters in the impedance control system on the system performance,simulation analysis was carried out and finally the constant force output of the grinding robot was achieved using adaptive impedance control based on the processing volume.Based on the previous kinematic analysis,a genetic genetic path planning was completed to enable the robot to find the shortest path for grinding,followed by an improved particle swarm algorithm to obtain the time-optimal trajectory of the robot during the grinding process.Finally,a weld grinding experiment was set up to test the grinding of weld defects and to verify the robot’s motion planning and force control methods. |