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.

翻译：机器人的日益部署显著提升了众多行业的自动化水平。本文研究了美容行业中基于激光的皮肤科手术的自动化挑战；这类相关操作任务涉及以重复性模式将美容激光的能量传递至皮肤表面。为自动化这一过程，我们提出使用机器人操作臂，并通过示教学习框架赋予其熟练皮肤科医师的灵巧性。为确保美容激光能正确地将能量传递至个体皮肤表面，我们开发了一种新颖的基于结构化预测的模仿学习算法，其优势在于能够处理几何约束。值得注意的是，我们提出的算法有效解决了与准周期运动相关的模仿挑战——这是许多基于激光的美容任务的常见特征。通过实际实验，我们的机器人美容师在模拟真实皮肤科操作中展现了其性能；新方法不仅能够复现示教中的节律性动作，还能将习得技能适应于未见过的场景与对象。