A visual servo tracking method for robotic arms based on adaptive neural network compensation

CN119658673BActive Publication Date: 2025-09-23CHANGCHUN INST OF OPTICS FINE MECHANICS & PHYSICS CHINESE ACAD OF SCI
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Patent Information

Application Number
CN202411462428.8
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2024-10-18
Publication Date
2025-09-23
Estimated Expiration
2044-10-18

AI Technical Summary

Technical Problem

In traditional dynamic target visual servo tracking control, the image feature error is inaccurate due to the delay of the visual servo system and environmental noise, resulting in tracking accuracy. It is difficult to improve the control frequency of the visual servo system in the existing technology, and the tracking accuracy is low.

Method used

Adaptive neural network compensation is introduced. Real-time image feature error correction is performed in the robot arm visual servo system through the adaptive neural network compensator. The actual joint velocity of the robot arm and the image feature error are used for adaptive adjustment to improve the compensation accuracy.

Benefits of technology

Without increasing the control frequency of the visual servo system, the visual servo tracking accuracy of the robotic arm is significantly improved, the tracking error is reduced, and a more efficient tracking effect is achieved.

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Abstract

The present invention relates to the field of robotic arm control technology, specifically providing a robotic arm visual servo tracking method based on adaptive neural network compensation. Based on the image feature error between real-time image features and ideal image features, adaptive neural network compensation is performed on the traditional robotic arm control rate to obtain a compensated robotic arm controller. The controller is used to obtain the control joint velocity of the robotic arm, and the control joint velocity is used to control the robotic arm to track a dynamic target. The method of the present invention can compensate for system tracking errors using an adaptive neural network without increasing the control rate of the robotic arm servo system, thereby greatly improving the robotic arm's tracking accuracy, reducing human intervention, and simplifying the complexity of robotic arm control.
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Citation Information

Patent Citations

  • Mechanical arm target tracking method based on visual servo

    CN112847334A

  • Visual servo finite time control method based on speed observer

    CN118322205A