Robot calibrate error compensation method based on fuzzy nerve network

A technology of fuzzy neural network and compensation method, which is applied in the field of mechanical processing and manufacturing, can solve the problems of low robot positioning accuracy, interpolation points that cannot meet robot accuracy, and algorithm convergence cannot be guaranteed, and achieve strong robustness
CN104516268AInactive Publication Date: 2015-04-15SHENYANG SIASUN ROBOT & AUTOMATION
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Patent Information

Authority / Receiving Office
CN · China
Current Assignee / Owner
SHENYANG SIASUN ROBOT & AUTOMATION
Publication Date
2015-04-15
Estimated Expiration
Not applicable · inactive patent

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Abstract

The invention discloses a robot calibrate error compensation method based on a fuzzy nerve network; the method comprises the following steps: compiling a homogeneous transformation matrix between adjacent link rods; calculating a kinetics equation and an error equation general formula of a robot end performer according to the transformation matrix; generating a kinetics equation and an error equation of an angle [theta i] according to a geometry parameter nominal value, the kinetics equation and the error equation general formula; compensating a first error compensation for the robot according to the kinetics equation and error equation; applying a fuzzy nerve network model to carry out a second error compensation for the robot; the method can enable the robot error compensation model to be faster, and more accurate with strong robustness.
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Description

technical field

[0001] The invention belongs to the field of mechanical processing and manufacturing, and mainly relates to a robot calibration error compensation method based on a fuzzy neural network. Background technique

[0002] Nowadays, the robots produced by robot manufacturers have relatively high repeat positioning accuracy, but low absolute positioning accuracy. As the off-line programming technology of robots becomes more and more widespread, improving the absolute positioning accuracy of robots has become one of the key technical issues. The calibration of industrial robots is generally divided into four steps: modeling, measurement, parameter identification and compensation, among which compensation is the last step of calibration. Due to the positioning error, installation error and working error (transmission, deformation and other errors) of the robot in the manufacturing and installation process, the absolute positioning accuracy of the working robot is low...

Claims

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