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.