Learning Direction of Attention for a Social Robot in Noisy Environments

Nicolai Bæk Thomsen, Zheng-Hua Tan, Børge Lindberg, Søren Holdt Jensen

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review


It is essential for social robots to be able to locate
and direct attention towards communicating persons, however
the operating environments can be challenging. When using
sound source localization (SSL) acoustic noise sources can distract
the robot, which interrupts the desired interaction with people.
Since the noise sources can be of many different kinds, it is
important for the robot to adapt to any environment. In this
paper we present a simple strategy for a robot to adapt to
the environment using feedback from a face detection routine,
thus eventually only directing attention towards humans. Four
experiments with different noise types and different strategies
for using feedback from face detection show the effectiveness of
the proposed strategy.
Original languageEnglish
Title of host publicationThe 3rd AAU Workshop on Robotics : Proceedings
EditorsZheng-Hua Tan, Shaoping Bai, Thomas Bak, Matthias Rehm, Elizabeth Ann Jochum
Number of pages7
PublisherAalborg Universitetsforlag
Publication date2015
Article number1
ISBN (Electronic)978-87-7112- 433-0
Publication statusPublished - 2015
EventThe 3rd AAU Workshop on Robotics - Aalborg, Denmark
Duration: 30 Oct 201430 Oct 2014


ConferenceThe 3rd AAU Workshop on Robotics
SeriesAAU Workshop on Robotics

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    Thomsen, N. B., Tan, Z-H., Lindberg, B., & Jensen, S. H. (2015). Learning Direction of Attention for a Social Robot in Noisy Environments. In Z-H. Tan, S. Bai, T. Bak, M. Rehm, & E. A. Jochum (Eds.), The 3rd AAU Workshop on Robotics: Proceedings (pp. 8-14). [1] Aalborg Universitetsforlag. AAU Workshop on Robotics http://vbn.aau.dk/admin/files/224392713/The_3rd_AAU_Workshop_on_Robotics_2014.pdf