Experimental results from a first order P-type ILC algorithm applied to a large size six degrees of freedom commercial industrial robot are presented. The ILC algorithm is based on measurements of the motor angles, but in addition to the conventional evaluation of the ILC algorithm based on the control error on the motor side, the tool path error on the arm side is evaluated using a laser tracker. Experiments have been carried out in three different operating points using movements that represent typical paths in a laser cutting application, and different choices of algorithm design parameters have been studied. The motor angle error is reduced substantially in all experiments, and the tool path error is reduced in most of the cases. In one operating point, however, the error does not decrease as much and an oscillatory tool behaviour is observed. Changed filter variables can give worse error reduction in all operating points. To achieve even better performance, especially in difficult operating points, it is concluded that an arm side measurement, from for example an accelerometer, needs to be included in the learning. Abstract: Experimental results from a first order P-type ILC algorithm applied to a large size six degrees of freedom commercial industrial robot are presented. The ILC algorithm is based on measurements of the motor angles, but in addition to the conventional evaluation of the ILC algorithm based on the control error on the motor side, the tool path error on the arm side is evaluated using a laser tracker. Experiments have been carried out in three different operating points using movements that represent typical paths in a laser cutting application, and different choices of algorithm design parameters have been studied. The motor angle error is reduced substantially in all experiments, and the tool path error is reduced in most of the cases. In one operating point, however, the error does not decrease as much and an oscillatory tool behaviour is observed. Changed filter variables can give worse error reduction in all operating points. To achieve even better performance, especially in difficult operating points, it is concluded that an arm side measurement, from for example an accelerometer, needs to be included in the learning.