Effectiveness of simultaneous behavior by interactive robot

Masahiko Taguchi, Kentaro Ishii, Michita Imai

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The ability of a robot to do gaze-drawing and to gesture have become recognized as essential elements in achieving joint attention of the real world during human-robot interaction. However, the ability of a robot using such non-verbal actions to interrupt human action is unclear. We have conducted an experiment in which a robot tries to interrupt human action to demonstrate the effectiveness of an interactive robot acting simultaneously with a person. Using the results of this experiment, we developed a system that a robot can use to predict human motion so that the robot can automatically perform simultaneous behavior.

Original languageEnglish
Title of host publicationArtificial Intelligence and Soft Computing - ICAISC 2008 - 9th International Conference, Proceedings
Pages896-906
Number of pages11
DOIs
Publication statusPublished - 2008 Aug 4
Event9th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2008 - Zakopane, Poland
Duration: 2008 Jun 222008 Jun 26

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5097 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other9th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2008
CountryPoland
CityZakopane
Period08/6/2208/6/26

    Fingerprint

Keywords

  • Human-robot interaction
  • Simultaneous behavior

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Taguchi, M., Ishii, K., & Imai, M. (2008). Effectiveness of simultaneous behavior by interactive robot. In Artificial Intelligence and Soft Computing - ICAISC 2008 - 9th International Conference, Proceedings (pp. 896-906). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5097 LNAI). https://doi.org/10.1007/978-3-540-69731-2_85