  Robots applied in therapeutic scenarios, for instance in the therapy of
individuals with Autism Spectrum Disorder, are sometimes used for imitation
learning activities in which a person needs to repeat motions by the robot. To
simplify the task of incorporating new types of motions that a robot can
perform, it is desirable that the robot has the ability to learn motions by
observing demonstrations from a human, such as a therapist. In this paper, we
investigate an approach for acquiring motions from skeleton observations of a
human, which are collected by a robot-centric RGB-D camera. Given a sequence of
observations of various joints, the joint positions are mapped to match the
configuration of a robot before being executed by a PID position controller. We
evaluate the method, in particular the reproduction error, by performing a
study with QTrobot in which the robot acquired different upper-body dance moves
from multiple participants. The results indicate the method's overall
feasibility, but also indicate that the reproduction quality is affected by
noise in the skeleton observations.
