Self-adaptive dead zone inverse model generating device of visual servo mechanical arm system

Abstract

The invention discloses a self-adaptive dead zone inverse model generating device of a visual servo mechanical arm system. The visual servo mechanical arm system is composed of a visual servo controller, a visual module, a motion control module, a driving module, a six-degree-of-freedom mechanical arm, a torque feedback module, a speed and position collecting module and a detecting module. The self-adaptive dead zone inverse model generating device of the visual servo controller is used for eliminating dead zone non-linear constraint and comprises a dead zone inverse model module, a self-adapting module and an operating module, wherein the dead zone inverse model module is used for structuring a smooth dead zone nonlinear inverse model; the self-adapting module adjusts estimated dead zone parameters through self-adaptive laws and transmits the parameters into the dead zone inverse model module to change the parameters of the inverse model; by means of the signal communication of the modules, a closed-loop control system can be formed inside the visual servo mechanical arm system. The self-adaptive dead zone inverse model generating device of the visual servo mechanical arm system can effectively eliminate the influence of the dead zone nonlinear restraint and achieve high image tracing precision.

Description

technical field [0001] The invention relates to an adaptive dead zone inverse model generating device of a visual servo manipulator system, which belongs to the transformation technology of the visual servo manipulator system on the input signal. Background technique [0002] Robot research began in the middle of the 20th century, and it developed along with the development of automation and computer technology and the development and utilization of atomic energy. Robots have been in the process of continuous development from simple to complex, from single to diverse, from low-level to high-level. With the development of electronic device technology, the computing power of computers has been greatly improved and various sensors are used in On the robot system, the working environment of most robots is pre-set, so once there is any change in the working environment, the robot system needs to be reset. As a result, the application range of industrial robots is greatly limited...

AI Technical Summary

Problems solved by technology

[0005] But the key issues at present are: First, the common robotic arm system with visual servo needs to calibrate the camera. However, camera calibration is a cumbersome and inefficient work, although many methods have been used in vision systems. calibration, but the cost of camera calibration is still high

Camera calibration is to obtain the internal and external parameters of the camera through calibration experiments; secondly, because the gears are difficult to fully mesh and the machinery wears down with time and times of use, there will be various nonlinear factors in the torque input of the manipulator system , will not only greatly affect the control effect but also cause the servo system to be unstable. The more common one is the input dead zone nonlinear constraint

When the driver provides the input torque for the motor, the non-linearity of the dead zone is manifested by the overlap of the gear meshing. When the torque can be accurately applied to the motor within a certain range, but when the torque exceeds the dead zone threshold, it appears that the input is applied to the motor. The torque on the motor presents a threshold characteristic, maintaining the maximum input value of the dead zone, causing the control performance to drop sharply and even lead to instability

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