摘要：AbstractAn iterative, learning based, feed-forward method for compensation of friction in industrial robots is studied. The method is put into an ILC framework by using a two step procedure proposed in literature. The friction compensation method is based on a black-box friction model which is learned from operational data, and this can be seen as the first step in the method. In the second step the learned model is used for compensation of the friction using the reference joint velocity as input. The approach is supported by simulation experiments.
