Learning Direction of Attention for a Social Robot in Noisy Environments

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

Learning Direction of Attention for a Social Robot in Noisy Environments

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

Department of Electronic Systems

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-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 language	English
Title of host publication	The 3rd AAU Workshop on Robotics : Proceedings
Editors	Zheng-Hua Tan, Shaoping Bai, Thomas Bak, Matthias Rehm, Elizabeth Ann Jochum
Number of pages	7
Publisher	Aalborg Universitetsforlag
Publication date	2015
Pages	8-14
Article number	1
ISBN (Electronic)	978-87-7112- 433-0
Publication status	Published - 2015
Event	The 3rd AAU Workshop on Robotics - Aalborg, Denmark Duration: 30 Oct 2014 → 30 Oct 2014

Conference

Conference	The 3rd AAU Workshop on Robotics
Country/Territory	Denmark
City	Aalborg
Period	30/10/2014 → 30/10/2014

Series	AAU 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). Article 1 Aalborg Universitetsforlag. http://vbn.aau.dk/admin/files/224392713/The_3rd_AAU_Workshop_on_Robotics_2014.pdf

@inproceedings{eeced96245f742249cd9592719e7504a,

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.",

author = "Thomsen, {Nicolai B{\ae}k} and Zheng-Hua Tan and B{\o}rge Lindberg and Jensen, {S{\o}ren Holdt}",

year = "2015",

language = "English",

series = "AAU Workshop on Robotics",

publisher = "Aalborg Universitetsforlag",

pages = "8--14",

editor = "Zheng-Hua Tan and Shaoping Bai and Thomas Bak and Matthias Rehm and Jochum, {Elizabeth Ann}",

booktitle = "The 3rd AAU Workshop on Robotics",

note = "The 3rd AAU Workshop on Robotics ; Conference date: 30-10-2014 Through 30-10-2014",

}

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. <http://vbn.aau.dk/admin/files/224392713/The_3rd_AAU_Workshop_on_Robotics_2014.pdf>

Learning Direction of Attention for a Social Robot in Noisy Environments. / Thomsen, Nicolai Bæk; Tan, Zheng-Hua; Lindberg, Børge et al.
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 proceeding › Article in proceeding › Research › peer-review

TY - GEN

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

AU - Thomsen, Nicolai Bæk

AU - Tan, Zheng-Hua

AU - Lindberg, Børge

AU - Jensen, Søren Holdt

PY - 2015

Y1 - 2015

N2 - 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.

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

A2 - Bak, Thomas

A2 - Rehm, Matthias

A2 - Jochum, Elizabeth Ann

PB - Aalborg Universitetsforlag

T2 - The 3rd AAU Workshop on Robotics

Y2 - 30 October 2014 through 30 October 2014

ER -

Learning Direction of Attention for a Social Robot in Noisy Environments

Abstract

Conference

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