Control optimization of manipulator by introducing Bayesian polynomial interpolation

When the six-axis manipulator moves in space, it is easy to cause the jump of joint Angle due to the mutation of speed and acceleration, and the motion trajectory has random fluctuations of faults, so it cannot move continuously. The interpolation function of the end effector of the manipulator is constructed based on the conventional cubic and quintic polynomial interpolation, and the motion trajectory planning method is optimized by using the Bayesian curve. Based on the standard D-H parameter method and forward kinematics, the mathematical model of the six-axis manipulator is established. And the Monte Carlo method is used to calculate the workspace of the manipulator. The three-five-cubic interpolation method and the Bayesian optimization method based on interpolation were used to obtain the values of Angle, angular velocity and angular acceleration respectively, and the motion trajectory planning was completed. Simulation results show that the proposed method can slightly improve the trajectory.