Iterative improvement of path accuracy of industrial robots using external measurements

This paper presents a cascaded methodology for enhancing the path accuracy of industrial robots by using advanced control schemes. It includes kinematic calibration as well as dynamic modeling and identification. This is followed by a centralized model-based compensation of robot dynamics. The implemented feed-forward torque control shows the expected improvements of control accuracy. However, external measurements show the influence of joint elasticities as systematic path errors. To further increase the accuracy an iterative learning controller (ILC) based on external camera measurements is designed. The implementation yields to significant improvements of path accuracy. By means of a kind of automated “Teach-In”, an overall effective concept for the automated calibration and optimization of the accuracy of industrial robots in high-dynamic path-applications is realized.