Modular approach to kinematic reliability analysis of industrial robots

Abstract

The robot kinematic reliability analysis methods based on parts or the whole machine have defects in accuracy and efficiency. Therefore, the paper proposes an efficient method to calculate and evaluate the kinematic reliability of industrial robots based on motion function modules (MFMs). Taking MFMs as the basic analysis units, the paper focuses on the influence of the uncertainty of intermediate MFMs on robot kinematic reliability. Based on the differential linearization error model and multivariate Gaussian distribution method, the transfer and accumulation of errors in the joint motion layer and the functional layer are described. And then, the summation method is proposed to calculate and evaluate the kinematic reliability of industrial robots. Through the error sum functions, the error variables are integrated into the appropriate motion module layer. It can effectively reduce the number of uncertain parameters in the kinematic reliability model, and then reduce the operation cost. In the case study, a TA6R robot is taken as an example to verify the accuracy and practicability of the proposed method.