Qualitative Research of Robot-Helping Behaviors in a Field Trial
Sachie Yamada, Takayuki Kanda, Kanako Tomita- Artificial Intelligence
- Human-Computer Interaction
During the previous field study with a robot and its interaction with mall visitors, we observed a surprising event during which a leaflet-distributing robot was abused, although it was subsequently helped by one of its previous abusers. After analyzing 72.25 hours of video data, we identified 47 cases where a robot dropped a leaflet and classified them according to following three criteria: 1) interaction between the potential helper or others with the robot before it dropped the leaflet, 2) the nature of the interaction (abused or not), and 3) whether it was helped. Using the Trajectory Equifinality Model (TEM), we analyzed 19 cases where the robot was helped. We identified the following interaction process that started with individuals who paid attention to the robot, whether they had abusive or non-abusive interactions with it, whether they noticed its failure, and finally whether they helped it. The presence of others encouraged the person to focus on the robot, and the interactions with it led to helping, regardless whether the interaction was abusive. The absence of others when the robot dropped the leaflet encouraged helping. The findings of this study will motivate interaction designs for social robots that can leverage human help.