  The increasing deployment of robots has significantly enhanced the automation
levels across a wide and diverse range of industries. This paper investigates
the automation challenges of laser-based dermatology procedures in the beauty
industry; This group of related manipulation tasks involves delivering energy
from a cosmetic laser onto the skin with repetitive patterns. To automate this
procedure, we propose to use a robotic manipulator and endow it with the
dexterity of a skilled dermatology practitioner through a
learning-from-demonstration framework. To ensure that the cosmetic laser can
properly deliver the energy onto the skin surface of an individual, we develop
a novel structured prediction-based imitation learning algorithm with the merit
of handling geometric constraints. Notably, our proposed algorithm effectively
tackles the imitation challenges associated with quasi-periodic motions, a
common feature of many laser-based cosmetic tasks. The conducted real-world
experiments illustrate the performance of our robotic beautician in mimicking
realistic dermatological procedures; Our new method is shown to not only
replicate the rhythmic movements from the provided demonstrations but also to
adapt the acquired skills to previously unseen scenarios and subjects.
