Method for improving absolute positioning precision based on six-degree-of-freedom series mechanical arm

Abstract

The invention relates to the field of self-adaptive control, in particular to a method for improving absolute positioning precision based on a six-degree-of-freedom series mechanical arm. The method comprises the following steps of, firstly, acquiring tail end target spot information through a laser tracker, and preprocessing to carry out coordinate conversion between the mechanical arm and the laser tracker; then, establishing an exponential product model of the mechanical arm by applying Lie Groups and Lie Algebras, fusing the exponential product model with a method for solving a global minimum value through a sequential quadratic programming algorithm, and compensating tail end geometric errors generated by joint parameter deviation of the mechanical arm; and finally, solving an inverse kinematics solution through an actual point location obtained by the laser tracker and the exponential product model, carrying out model training by using a Gaussian process regression algorithm, carrying out compensation prediction on a non-geometric motion error, and inputting a predicted compensated angle value into a demonstrator. According to the method, the actual kinematics model parameters of the mechanical arm can be calculated more accurately, and the tail end point position error is reduced so as to improve the absolute positioning precision of the mechanical arm.

Description

technical field [0001] The invention relates to the field of adaptive control, in particular to a method for improving absolute positioning accuracy based on a six-degree-of-freedom series mechanical arm. [0002] technical background [0003] The problem of position error compensation at the end of the manipulator has attracted more and more research due to its potential application prospects and value in multiple disciplines, such as numerical calculation, adaptive control, convex optimization, intelligent gripping and assembly, etc. interest. Due to various factors such as inaccurate kinematic model parameters, assembly errors, and zero position deviation of the joint axis, the deviation between the nominal point position and the actual point position at the end of the mechanical arm is too large, which brings difficulties to the further motion control of the mechanical arm. More challenges. Therefore, a variety of position compensation methods for the end of the manipul...

AI Technical Summary

Problems solved by technology

However, many unknown and uncertain influencing factors, including motor gear wear, joint shaft clearance error, structural mismatch, external interference and noise, etc., usually exist in nonlinear error sources

These uncertainties will lead to the inability to further improve the accuracy only through geometric error compensation, affecting and restricting the manipulator to perform high-precision tasks

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