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International Standard Serial Number:
ISSN 1001-4551
Sponsor:
Zhejiang University;
Zhejiang Machinery and Electrical Group
Edited by:
Editorial of Journal of Mechanical & Electrical Engineering
Chief Editor:
ZHAO Qun
Vice Chief Editor:
TANG ren-zhong,
LUO Xiang-yang
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86-571-87041360,87239525
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86-571-87239571
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No.9 Gaoguannong,Daxue Road,Hangzhou,China
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meem_contribute@163.com
Abstract: In order to solve the problems of high cost, low efficiency and complex identification model, the low-cost, real-time and non-model calibration method of robot arm was investigated. A real-time model-free calibration method of manipulator based on multi-target recognition was proposed. Firstly, a low-cost binocular camera was selected as the measuring equipment.Taking the calibrated robot arm as the object, the marker was fixed on each joint respectively, and the pose transformation matrix from marker to joint was established.Then, considering the influence of vision system error and contour error, the mapping from the measured pose of marker to the real pose of the corresponding joint was established based on the micro-error principle.A non-model-based identification method for link parameters was proposed.Finally,in order to verify the accuracy of the model-free calibration method of the manipulator based on multi-object recognition, a simulation experiment was built to simulate the real-time model-free identification process of the connecting rod parameters in the real scene.The research results show that the deviation between the estimated and real value of actual joint pose can be ignored, and the non-model identification error of the link parameters is 0%~4% correspondingly. This indicates that the identification accuracy of the new method is only related to the first calibration accuracy of robot arm and hand eye calibration accuracy of camera, but not the visual system error and the robot arm contour error. Therefore, the new method meets the high accuracy requirement of the real-time and non-model calibration of the robot arm with the support of the existing visual measurement technology.
Key words: robot calibration; stereo vision; absolute positioning accuracy; nonmodelbased identification method; model solution method; multi-target measurement