Decoupling And Compensation Of Synthesis Errors And Motion Planning For Machining Robot System

Industrial robots used in machining have advantages of low cost, good dexterity and flexibility. Despite shortcomings of the joints in industrial robot but through appropriate compensation measures, they can still meet the different processing. Currently, industrial robots have been applied in automobile manufacturing, aerospace assembly and flexible machining centers. With the continuous improvement of industrial robot, its application in the field of cutting will be more and more influenced by academia and industry concern.Cutting robot’s inverse kinematics and dynamics equations were establishment and robot error kinematics equation was established by the differential transformation principle firstly. Based on robot error kinematic equations, integrated differential transformation kinematic equations of dynamic and static errors were established. Proved the coupling between dynamic and static errors, and proved the implicated error motion between the robot TCP and the workpiece. Errors between robot’s joints were decoupled, error compensation model were established of cutting robot.In the process of less DOF robot error compensation, required solving the inverse Jacobian matrix, but when Jacobian matrix generalized inverse is ill, numerical calculation errors will cover robot error. In order to avoid solving the inverse Jacobian matrix, improved AFSA be used to solving over determined nonlinear equations. In this case, reduced errors caused by numerical calculation, and improved the precision of error compensation.According to the characteristics of the robot trajectory, improved cubic spline interpolation-five polynomial interpolation-improved cubic spline interpolation was used to plan trajectory. So the robot can be guaranteed in machining speed, acceleration, jerk continuous. Joint force will determine the joint error, and robots expected to complete the task in the shortest time and least energy. To solve above problems, in order to improve the quality of the robot dynamics, reduced the running time, reduced energy consumption targets, the multi-objective trajectory optimization was used.