Improving robot calibration results using modeling optimization

Abstract

This work describes techniques for planning, optimizing and simulating the calibration processes of robots using offline programming. The identification of geometric parameters of the nominal kinematic model is optimized using techniques of numerical optimization of the mathematical model. The simulation of the actual robot and the measurement system is achieved by introducing random errors representing their physical behaviour similar to its statistical repeatability. An evaluation of the corrected nominal kinematic model brings about a clear perception of the influence of distinct variables involved in the process for suitable planning, and indicates a considerable accuracy improvement when the optimized model is compared to the nonoptimized one.