Stable grasping control of robot based on particle swarm optimization

Abstract

In order to improve the compensation and stability control ability of handling robot's stable grasping and positioning control, a method of stable grasping and positioning control for handling robot based on particle swarm optimization is proposed. Combining visual information fusion and sensitive sensor information fusion, the constraint parameters of stable grasping control for handling robot are analyzed, and sensitive mechanical sensors are used to collect and identify the information of grasping posture parameters of handling robot. The feature quantity of spatial distribution information of grasping posture parameters of the handling robot is extracted, and the compensation and optimization control of posture parameters in the process of grasping posture determination of the handling robot are carried out by using the particle swarm optimization control method. The adaptive positioning error compensation and feedback correction method are combined to carry out particle optimization parameter fusion and optimal solution analysis in the process of grasping posture determination of the handling robot, and the adaptive parameter correction and error feedback fusion method are combined to realize stable grasping positioning control of the handling robot. The simulation results show that the output stability of this method is better and the positioning error is lower, which improves the output stability of the handling robot in the grasping process.