Name
Abstract | ||
|---|---|---|
Nonverbal behaviors serve as a rich source of information in inter human communication. In particular, motion cues can reveal details on a person's current physical and mental state. Research has shown, that people do not only interpret motion cues of humans in these terms, but also the motion of animals and inanimate devices such as robots. In order to successfully integrate mobile robots in domestic environments, designers have therefore to take into account how the device will be perceived by the user. In this study we analyzed the relationship between motion characteristics of a robot and perceived affect. Based on a literature study we selected two motion characteristics, namely acceleration and curvature, which appear to be most influential for how motion is perceived. We systematically varied these motion parameters and recorded participants interpretations in terms of affective content. Our results suggest a strong relation between motion parameters and attribution of affect, while the type of embodiment had no effect. Furthermore, we found that the level of acceleration can be used to predict perceived arousal and that valence information is at least partly encoded in an interaction between acceleration and curvature. These findings are important for the design of behaviors for future autonomous household robots. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/HRI.2010.5453269 | HRI |
Keywords | Field | DocType |
human-robot interaction,mobile robots,motion control,acceleration,curvature,domestic environments,inter human communication,mobile robots,nonverbal communication,robot motion,Expressive robotic behavior,affective communication,nonverbal communication | Motion control,Computer science,Simulation,Nonverbal communication,Human–computer interaction,Animation,Affect (psychology),Robot,Perception,Mobile robot,Human–robot interaction | Conference |
ISSN | Citations | PageRank |
2167-2121 | 64 | 4.27 |
References | Authors | |
10 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Martin Saerbeck | 1 | 164 | 10.10 |
| Christoph Bartneck | 2 | 1226 | 106.95 |