In this paper, we present our work in progress towards creating a library of motion primitives. This library facilitates easier and more intuitive learning and reusing of robotic skills. Users can teach robots complex skills through Learning from Demonstration, which is automatically segmented into primitives and stored in clusters of similar skills. We propose a novel multimodal segmentation method as well as a novel trajectory clustering method. Then, when needed for reuse, we transform primitives into new environments using trajectory editing. We present simulated results for our framework with demonstrations taken on real-world robots.

翻译：本文介绍了我们为创建运动基元库所进行的工作进展。该库能够促进机器人技能更简便、更直观的学习与复用。用户可通过示教学习向机器人传授复杂技能，系统会自动将演示数据分割为基元并存储于相似技能簇中。我们提出了一种新颖的多模态分割方法以及创新的轨迹聚类方法。当需要复用时，我们通过轨迹编辑技术将基元适配到新环境中。本框架的仿真实验结果基于真实机器人的演示数据获得。