Investigation of robot behavior model to build causality after events

This paper proposes a robot behavior model to build causality not before events but after events in the smart environment. Although smart environment is a useful approach to help elderly people and the physically-challenged people and so on, it cannot avoid the system error, and it gives users discomfort. To solve the problems, we pay attention to causality illusion, and aim to build a robot behavior model to build causality after events. To realize the proposed system, we investigated whether users feel the causality between the robot and the environment by the post action of the robot after the events. Experimental results showed that users feel causality not only when the robot moved before events but also when the robot moved after events. In addition, we also found that the robot behavior after events gave users more positive impression than the robot behavior before events.