Position Error Modeling And Simulation Analysis Of A Three-degree-of-freedom Parallel Mechanism Grinding Robot

With the development of robotics,parallel mechanisms have a good application prospect in the field of grinding and polishing.As one of the most important processes in industrial manufacturing,the accuracy of the polishing robot directly affects whether the parallel mechanism can meet the expected requirements,therefore,how to improve the position accuracy of the parallel robot has become a current research hotspot.In this paper,we take the three-degree-of-freedom parallel mechanism grinding robot as the research object and carry out theoretical research and simulation analysis from the aspects of structure layout,robot kinematics forward and reverse solution,working space,robot error modeling and compensation,etc.,to reduce the position error of the robot and provide an effective solution for the grinding robot to expand the working space and improve the position accuracy.The main research works are as follows:(1)The kinematic model of the robot is established by the geometric method.The coaxial drive layout configuration and rod configuration are analyzed,showing that the parallelogram rod configuration and rectangular dynamic platform have better constraint performance.The working space of the robot is investigated when the ball hinge and the Hooke hinge are used as its joint hinges,respectively.Finally,the Jacobi matrix condition number is selected to evaluate the robot’s dexterity.(2)The robot end position error model is established.Solve the robot Jacobi matrix,analyze and study the robot error types,and analyze the 12 static error sources of the robot in the specified range of the reachable working space.Adopt the global sensitivity as the sensitivity index for evaluating the robot error sources,analyze the sensitivity of each error source to the robot end position error,and lay the foundation for the subsequent position error compensation of the robot end-effector.(3)The improved particle swarm optimization algorithm is used to compensate for the robot’s position error.Improving the inertia weight coefficients of the standard particle swarm optimization algorithm for the problems of poor local search ability and low accuracy,and verifying the feasibility of the improved particle swarm optimization algorithm in solving the continuum optimum problem by example;The robot end-space position points are randomly selected,and the improved particle swarm optimization algorithm is used to compensate the error,which confirms the effectiveness of the improved particle swarm optimization algorithm for robot position error compensation.(4)Robot software simulation and prototype construction were performed.The simulation is carried out by using the software preset grinding circular trajectory,and the angular velocity of the drive arm after the simulation is imported into the preset error Adams model,and the position error is compensated by the improved PSO algorithm.Comparing the trajectories before and after error compensation,further demonstrating the effectiveness of the improved PSO algorithm for robot position error compensation.The experimental scheme is proposed to lay the foundation for subsequent theoretical research.