Imitation of human movement by robots is an important area of research to create expressive systems that are able to interact with humans in social settings. One lens through which imitation may be investigated is that of character archetypes, commonly found in human story-telling. Classical ballet, a form of story-telling through movement, makes extensive use of such archetypes. This paper reviews how Laban Movement Analysis creates a descriptive taxonomy in which features of interest may be identified and reported from human performers to robotic platforms, specifically for a BeBop aerial drone and a Nao humanoid platform. To determine the success of this approach, the paper also presents evaluation by lay human viewers that validates the character transfer. Moreover, this paper offers more nuance into this evaluation by querying two specialized groups of experts, which frequently deviated from lay ratings and, thus, offer deeper insight into both the success of the character transfer and the importance of prior training in movement perception. This work may be useful in human-facing scenarios where character archetypes facilitate engagement, identification, and understanding between robots and human counterparts. Further, it highlights nuances in working with expert artists to create broadly applicable designs.

机器人模仿人类的动作是研究创造表达系统的重要领域，该表达系统能够在社会环境中与人类互动。可以用来研究模仿的一种镜头是角色原型，通常是人类讲故事中发现的角色。古典芭蕾是通过运动来讲述故事的一种形式，它广泛使用了这种原型。本文回顾了拉班运动分析如何创建一种描述性分类法，其中可以识别感兴趣的特征并将其从人类表演者报告给机器人平台，特别是针对BeBop空中无人机和Nao人形平台。为了确定这种方法是否成功，本文还提出了由外行观众进行的评估，以验证字符转移。此外，本文通过查询经常偏离外行评级的两个专业专家组，为评估提供了更多细微差别，从而为角色转移的成功以及对动作感知的先前培训的重要性提供了更深入的了解。这项工作在面向角色的角色原型有助于机器人与人类同行之间互动，识别和理解的面向人类的场景中可能会很有用。此外，它还强调了与专家艺术家合作创建广泛适用的设计的细微差别。机器人与人类同行之间的识别和理解。此外，它还强调了与专家艺术家合作创建广泛适用的设计的细微差别。机器人与人类同行之间的识别和理解。此外，它还强调了与专家艺术家合作创建广泛适用的设计的细微差别。