robot self-initiative and personalization by learning through repeated interactions
We have developed a robotic system that interacts with the user, and through repeated interactions, adapts to the user so that the system becomes semi-autonomous and acts proactively. In this work we show how to design a system to meet a user's preferences, show how robot pro-activity can be learned and provide an integrated system using verbal instructions. All these behaviors are implemented in a real platform that achieves all these behaviors and is evaluated in terms of user acceptability and efficiency of interaction.
learning by demonstration human-robot interaction