论文标题
概率运动基原始中的相位分布，代表了人类运动的识别和繁殖的时间变化
Phase Distribution in Probabilistic Movement Primitives, Representing Time Variability for the Recognition and Reproduction of Human Movements
论文作者
论文摘要
概率运动原语（PROMP）是人类机器人相互作用运动的广泛使用。它们还促进了运动的时间和空间结构的分解。在这项工作中，我们研究了一种时间对齐观测的方法，以便在学习启动时，在维持光滑的相位速度的同时，最大化了观察到运动的空间结构中的信息。我们将方法应用于二维达到任务中的手轨迹的记录。提出了一种同时识别运动和阶段的系统，并讨论了运动识别和运动繁殖的性能。
Probabilistic Movement Primitives (ProMPs) are a widely used representation of movements for human-robot interaction. They also facilitate the factorization of temporal and spatial structure of movements. In this work we investigate a method to temporally align observations so that when learning ProMPs, information in the spatial structure of the observed motion is maximized while maintaining a smooth phase velocity. We apply the method on recordings of hand trajectories in a two-dimensional reaching task. A system for simultaneous recognition of movement and phase is proposed and performance of movement recognition and movement reproduction is discussed.
