Learning Direction of Attention for a Social Robot in Noisy Environments

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

Abstract

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
Pages8-14
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

Conference

ConferenceThe 3rd AAU Workshop on Robotics
CountryDenmark
CityAalborg
Period30/10/201430/10/2014
SeriesAAU Workshop on Robotics

Fingerprint

Robots
Face recognition
Feedback
Acoustic noise

Cite this

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
Thomsen, Nicolai Bæk ; Tan, Zheng-Hua ; Lindberg, Børge ; Jensen, Søren Holdt. / Learning Direction of Attention for a Social Robot in Noisy Environments. The 3rd AAU Workshop on Robotics: Proceedings. editor / Zheng-Hua Tan ; Shaoping Bai ; Thomas Bak ; Matthias Rehm ; Elizabeth Ann Jochum. Aalborg Universitetsforlag, 2015. pp. 8-14 (AAU Workshop on Robotics).
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title = "Learning Direction of Attention for a Social Robot in Noisy Environments",
abstract = "It is essential for social robots to be able to locateand direct attention towards communicating persons, howeverthe operating environments can be challenging. When usingsound source localization (SSL) acoustic noise sources can distractthe robot, which interrupts the desired interaction with people.Since the noise sources can be of many different kinds, it isimportant for the robot to adapt to any environment. In thispaper we present a simple strategy for a robot to adapt tothe environment using feedback from a face detection routine,thus eventually only directing attention towards humans. Fourexperiments with different noise types and different strategiesfor using feedback from face detection show the effectiveness ofthe proposed strategy.",
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year = "2015",
language = "English",
series = "AAU Workshop on Robotics",
publisher = "Aalborg Universitetsforlag",
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Thomsen, NB, Tan, Z-H, Lindberg, B & Jensen, SH 2015, Learning Direction of Attention for a Social Robot in Noisy Environments. in Z-H Tan, S Bai, T Bak, M Rehm & EA Jochum (eds), The 3rd AAU Workshop on Robotics: Proceedings., 1, Aalborg Universitetsforlag, AAU Workshop on Robotics, pp. 8-14, The 3rd AAU Workshop on Robotics , Aalborg, Denmark, 30/10/2014.

Learning Direction of Attention for a Social Robot in Noisy Environments. / Thomsen, Nicolai Bæk; Tan, Zheng-Hua; Lindberg, Børge; Jensen, Søren Holdt.

The 3rd AAU Workshop on Robotics: Proceedings. ed. / Zheng-Hua Tan; Shaoping Bai; Thomas Bak; Matthias Rehm; Elizabeth Ann Jochum. Aalborg Universitetsforlag, 2015. p. 8-14 1 (AAU Workshop on Robotics).

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

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T1 - Learning Direction of Attention for a Social Robot in Noisy Environments

AU - Thomsen, Nicolai Bæk

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AB - It is essential for social robots to be able to locateand direct attention towards communicating persons, howeverthe operating environments can be challenging. When usingsound source localization (SSL) acoustic noise sources can distractthe robot, which interrupts the desired interaction with people.Since the noise sources can be of many different kinds, it isimportant for the robot to adapt to any environment. In thispaper we present a simple strategy for a robot to adapt tothe environment using feedback from a face detection routine,thus eventually only directing attention towards humans. Fourexperiments with different noise types and different strategiesfor using feedback from face detection show the effectiveness ofthe proposed strategy.

M3 - Article in proceeding

T3 - AAU Workshop on Robotics

SP - 8

EP - 14

BT - The 3rd AAU Workshop on Robotics

A2 - Tan, Zheng-Hua

A2 - Bai, Shaoping

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Thomsen NB, Tan Z-H, Lindberg B, Jensen SH. Learning Direction of Attention for a Social Robot in Noisy Environments. In Tan Z-H, Bai S, Bak T, Rehm M, Jochum EA, editors, The 3rd AAU Workshop on Robotics: Proceedings. Aalborg Universitetsforlag. 2015. p. 8-14. 1. (AAU Workshop on Robotics).