Visual servo control method based on iterative duration variation

Abstract

The invention discloses a mechanical arm visual servo control method based on iterative duration variation. The method includes the steps that 1, a series of images are acquired in a demonstration mode; 2, the relation between the current image and the tracking image is acquired to define image features which express the movement condition of a mechanical arm; 3, a mutual relation model of a visual control system is established based on a mechanical arm kinematics model and a camera model, and an iterative feedforward and feedback control scheme is adopted; 4, if the phenomenon that a target object is beyond a visual range in the operation process of the mechanical arm, current iteration is ended. According to the method, it is not required that the target is continuously visual in the movement process, and meanwhile it is guaranteed that the mechanical arm can track the target image accurately to some degree.

Description

technical field [0001] The invention relates to a visual tracking method in the field of industrial manipulators, in particular to a visual servo control method based on an iterative time-varying strategy. Background technique [0002] Robotic arm visual tracking is a method of controlling the movement of the robotic arm using the visual system as feedback information, and is an important part of the research on the robotic arm. Visual tracking is a hot and difficult point in the research of industrial robots at present, and it plays an important role when industrial manipulators perform tasks in large or complex environments. [0003] Robotic arm visual tracking techniques can be divided into position-based methods and image-based methods. Among them, the position-based method uses the vision system as a position sensor to control the movement of the manipulator according to the position error. This method has a simple controller design, is suitable for low-precision track...

AI Technical Summary

Problems solved by technology

The image-based method uses the image fed back by the visual system as feedback information to control the movement of the manipulator to the scene that is consistent with the target image. This method has high precision, but because the image-based visual control has only one camera, it lacks depth information. Lead to model uncertainty, which will affect the stability and convergence of the system, and require the target image to be visible throughout the motion process

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