Abstract

Attention is a concept of human perception that enables human subjects to select the potentially relevant parts out of the huge amount of sensory data and that enables interactions with other human subjects by sharing attention with each other. These abilities are also of large interest for autonomous robots, therefore, interest in modeling concepts of human attention computationally has increased strongly in the robotics community during the last decade. Especially in human-robot interaction, the ability to detect what a human partner is attending to and to act in a similar way to enable intuitive communication, are important skills for a robotic system.

Still, there exists a gap in knowledge transfer between researchers in human attention and robotic researchers with their specific, often task-related, problems. Both communities can mutually benefit from each other by sharing ideas. In the workshop, researchers in visual and multi-modal attention can profit from the rapidly growing field of robotics, which offers new and challenging research questions with very concrete applicability to challenging problems. Robotic researchers can learn how to integrate attention to support natural and real-time HRI.