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arXiv · 2312.13623

Learning Rhythmic Trajectories with Geometric Constraints for Laser-Based Skincare Procedures

Anqing Duan·Wanli Liuchen·Jinsong Wu·Raffaello Camoriano·Lorenzo Rosasco·David Navarro-Alarcon
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Abstract

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.

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Anqing Duan, Wanli Liuchen, Jinsong Wu, Raffaello Camoriano, Lorenzo Rosasco, David Navarro-Alarcon. 2023-12-21. Learning Rhythmic Trajectories with Geometric Constraints for Laser-Based Skincare Procedures. https://arxiv.org/abs/2312.13623

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