Newly-added sampling method for estimating positioning error of mechanical arm in area

Abstract

The invention discloses a newly-added sampling method for estimating the positioning error of a mechanical arm in an area, which is applied to the technical field of newly-added robot sampling points and aims to solve the problem that the absolute positioning precision of an existing industrial robot is low. The method comprises the following steps: firstly, carrying out Delaunay triangulation on a motion area of a mechanical arm sampling point; then, using an error value of an actual value measured by a laser tracker and a theoretical value of a sampling point as a data output to determine a Kriging model; secondly, predicting a predicted value of an error value corresponding to an inner center point of each Delaunay triangle according to the determined Kriging model, and estimating a mean square error value of an error of the inner center of each triangle; and finally, using the coordinates of the inner center point of the Delaunay triangle with the large mean square error value as newly-added sampling points to create a new Kriging model. Through multiple times of new sampling iteration, the distribution of sampling points for absolute positioning precision estimation of the mechanical arm is more reasonable, and the prediction accuracy is improved.

Description

technical field [0001] The invention belongs to the technical field of robots, and in particular relates to a new sampling point technology. Background technique [0002] With its advantages of fast operation speed, high efficiency, modular structure design, flexible control system, and high repeatability, industrial robots are playing an increasingly important role in automated production and intelligent manufacturing, especially in high-precision, high-strength, It is playing an irreplaceable role in high-risk projects. With the continuous implementation of the key position robot replacement project, the special project of streamlining or unmanned production safety employees, intelligent manufacturing project and new application demonstration policies, the demand for industrial robots in China is further expanding. At present, the traditional manufacturing industry has ushered in great changes. In high-precision, high-intensity, difficult and even high-risk operations, it...

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Problems solved by technology

[0003] At present, industrial robots have high repetitive positioning accuracy, but the absolute positioning accuracy is low. In the absolute positioning accuracy compensation of the manipulator, sampling accounts for more than 80% of the full cycle of accuracy compensation. The distribution of sampling points not only affects the manipulator. Compensation efficiency, but also affect the accuracy of its compensation, so seek a reasonable sampling strategy, can improve the efficiency of sampling while satisfying its compensation accuracy and its important

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