To Örebro University

When creating datasets for modelling of human skills based on training examples from human motion, one can encounter the problem that the kinematics of the robot does not match the human kinematics. Presented is a simple method of bypassing the explicit modelling of the human kinematics based on a variant of the self-organising map (SOM) algorithm. While the literature contains instances of SOM-type algorithms used for dimension reduction, this reported work deals with the inverse problem: dimension increase, as we are going from 4 to 5 degrees of freedom.