Abstract. An essential capability for a robot designed to interact with humans is to show attention to the people in its surroundings. To enable a robot to involve multiple persons into interaction requires the maintenance of an accurate belief about the people in the environment. In this paper, we use a probabilistic technique to update the knowledge of the robot based on sensory input. In this way, the robot is able to reason about the uncertainty in its belief about people in the vicinity and is able to shift its attention between different persons. Even people who are not the primary conversational partners are included into the interaction. In practical experiments with a humanoid robot, we demonstrate the effectiveness of our approach.

@InProceedings{bennewitz05iros,
  author     = {Maren Bennewitz and Felix Faber and Dominik Joho and
                Michael Schreiber and Sven Behnke},
  title      = {Integrating Vision and Speech for Conversations with
                Multiple Persons},
  year       = {2005},
  booktitle  = {Proceedings of the {IEEE}/{RSJ} International Conference on
                Intelligent Robots and Systems {(IROS)}},
  address    = {Edmonton, Canada},
  pages      = {2523--2528},
  doi        = {10.1109/IROS.2005.1545158},
  isbn       = {0-7803-8912-3}
}