Dexterous in-hand manipulation is a peculiar and useful human skill. This ability requires the coordination of many senses and hand motion to adhere to many constraints. These constraints vary and can be influenced by the object characteristics or the specific application. One of the key elements for a robotic platform to implement reliable inhand manipulation skills is to be able to integrate those constraints in their motion generations. These constraints can be implicitly modelled, learned through experience or human demonstrations. We propose a method based on motion primitives dictionaries to learn and reproduce in-hand manipulation skills. In particular, we focused on fingertip motions during the manipulation, and we defined an optimization process to combine motion primitives to reach specific fingertip configurations. The results of this work show that the proposed approach can generate manipulation motion coherent with the human one and that manipulation constraints are inherited even without an explicit formalization.

翻译：灵巧的内手操作是人体特有的实用技能。这种能力需要多种感官与手部运动的协同配合，以满足多重约束条件。这些约束条件随物体特性或具体应用场景而变化，是机器人平台实现可靠内手操作技能的关键要素——需要将这些约束整合到运动生成过程中。这些约束可通过经验学习或人类示教隐式建模。本文提出一种基于运动基元字典的方法，用于学习与复现灵巧内手操作技能。我们重点研究了操作过程中的指尖运动，并定义了优化流程以组合运动基元实现特定指尖位形。结果表明，本方法可生成与人类操作一致的运动轨迹，且即使未显式建模操作约束，该方法仍能继承相应的约束特征。