Trajectory optimization and closed-loop feedback control of multi-degree-of-freedom robot

Multi-degree-of-freedom robots are widely used in various industries. In order to improve the stability of multi-degree-of-freedom robots, this paper proposes a motion trajectory optimization method based on PSO optimization algorithm and a closed-loop feedback control method for multi-degree-of-freedom robots based on error feedback. The standard D-H parameter method is used for kinematics analysis, combined with the multi-factor constraint parameter fusion method to establish the closed-loop feedback adaptive control law of the robot, and the robot's pose is adaptively adjusted according to the parameter optimization results to realize the stability control of the robot. The analysis results show that the multi-degree-of-freedom robot control with the analysis method in this paper has less error, strong robustness and accuracy of the kinematics method.