A motivational system for regulating human-robot interaction
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Where to look: a study of human-robot engagement
Proceedings of the 9th international conference on Intelligent user interfaces
Proceedings of the 9th international conference on Multimodal interfaces
Precision timing in human-robot interaction: coordination of head movement and utterance
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Designing gaze behavior for humanlike robots
Designing gaze behavior for humanlike robots
Controlling gaze with an embodied interactive control architecture
Applied Intelligence
Learning spontaneous nonverbal behavior using a three layers hierarchy
ACS'10 Proceedings of the 10th WSEAS international conference on Applied computer science
Design and evaluation techniques for authoring interactive and stylistic behaviors
ACM Transactions on Interactive Intelligent Systems (TiiS)
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Gaze behavior is one of the most important nonverbal behaviors during human-human close encounters. For this reason, many researchers in natural human-robot interaction focus on developing robots that can achieve human-like gaze behavior. Many approaches have been proposed to achieve this natural gaze behavior based on accurate analysis of human behaviors during natural interactions. One limitation of most available approaches is that the behavior is hardwired to the robot and learning techniques are used only, if ever, for adjusting the parameters of the behavior. In this paper we propose and evaluate a different approach in which the robot learns natural gaze behavior by watching natural interactions between humans. The proposed approach uses the LiEICA architecture developed by the authors and is completely unsupervised which leads to grounded behavior. We compare the resulting gaze controller with a state-of-the-art gaze controller that achieved human-like behavior and show that the proposed approach leads to a more natural gaze behavior based on subjective evaluations of subjects.