Automatic Control System of Manipulator Clamping Angle Based on Machine Vision

Abstract

In order to shorten the time it takes for the manipulator components to reach the preset position and avoid the behavior state of excessively increasing the gripping angle, an automatic control system for the gripping angle of the manipulator based on machine vision is designed. According to the motion state of the mechanical components of the gripper, the connection sensitivity of the angular position sensor is controlled, and then the tension and pressure control structure is used to complete the on-demand adjustment of the clamping force action form and realize the construction of the application platform environment of the hardware structure of the automatic control system. On this basis, by grabbing the necessary manipulator operation image, following the principle of machine vision, completing the preprocessing, and then combining the kinematic functions to perform the force control switching operation and realizing the gripping force control based on machine vision, and completing the design and application of the automatic control system for the gripping angle of the manipulator. The experimental results show that when the motor driving speed is equal to 2000 PPS,4000 PPS, and 6000 PPS, the consumption time required for the manipulator components to reach the preset position will not exceed 9.5s. Compared with the double closed-loop control system, it is more in line with the application requirements of effectively controlling the behavior of the clamping angle.