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.
- Character-driven robot design
- Embodied movement analysis
- Human-like movement
ASJC Scopus subject areas
- Computer Science(all)