Learning Accurate Path Control of Industrial Robots with Joint Elasticity

An adaptive architecture for feedforward control oj industrial robots with standard positional controller is presented. This approach explicitly considers robots with elastical joints. It assumes that the real position of the TCP can be recorded for ofline evaluation. Compensation of elasticity is trained in a feedforward controller. Adaptation takes place without any knowledge of the physical system model. The performance of the method is demonstrated in experiments with a 6am”sindustrial robot KUKA KR6\l for which real path errors during full speed motion are reduced by ?’0 %. Reductions of 50 % can be expected for untrained paths or other robots of the same type.