Mechanical arm kinematics self-calibration method based on binocular vision

Abstract

The invention relates to the field of self-adaptive control, in particular to a mechanical arm kinematics self-calibration method based on binocular vision. Firstly, data are collected, and the tail end position information of a mechanical arm and the actual rotation angle and the theoretical rotation angle of each joint of the mechanical arm are obtained through a binocular camera. Then, the DH theory and the hand-eye calibration theory are fused, and a mechanical arm kinematics hybrid model is established. The model is trained by using a multi-population self-adaptive difference algorithm, and parameters of the hybrid model are solved. Finally, each servo motor model is established through a polynomial fitting method, and polynomial parameter solving and compensation prediction are conducted by using a least square method. According to the hybrid model and the servo motor models provided by the invention, the influence of geometric errors on the mechanical arm can be greatly reduced, and more practical model parameters can be calculated. A mechanical arm base coordinate system needed in the hand-eye calibration process does not need to be additionally established through a demonstrator, and automation of the whole calibration process can be achieved on the premise that absolute positioning precision is guaranteed.

Description

Technical field [0001] The present invention relates to the field of adaptive control, and more particularly to a binding method based on bicomputer visual mechanical arm motion self-standard. Background technique [0002] In recent years, mechanical arm control has played an important role in automotive manufacturing, fruit picking, pipeline operations, surgery, etc., and is of great significance to industrial, agriculture and manufacturing development. Most multi-freedom robotic arm systems are essentially a semi-closed control structure that can only accurately control the position of the joint servo motor, and the relationship between the position of the motor position and the actuator position of the mechanical arm is determined by kinematics. At present, the impact of mechanical arms produced by robotic arm manufacturers at home and abroad cannot guarantee the absolute fit of each module, and the mechanical arm is worn in the process of motor wear, external noise and other ...

AI Technical Summary

Problems solved by technology

[0003] Aiming at the problems that the existing kinematics calibration process of the manipulator is cumbersome, the cost is too high and manual participation is required, the present invention proposes a binocular vision-based self-calibration method for the kinematics of the manipulator. The mixed model parameters are used for parameter identification, which reduces the influence of non-geometric factors on the positioning accuracy of the end, simplifies the redundancy of the calibration system, and realizes the automation of the entire calibration process. The servo motor model is established, and the least square method is used to optimize the model, which further improves the performance of the manipulator. Absolute Positioning Accuracy

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