Human-humanoid robot social interaction: Laughter

Sarah Cosentino, Tatsuhiro Kishi, Massimiliano Zecca, Salvatore Sessa, Luca Bartolomeo, Kenji Hashimoto, Takashi Nozawa, Atsuo Takanishi

Research output: Contribution to conferencePaperpeer-review

8 Citations (Scopus)

Abstract

In this paper, we describe a human gesture recognition system developed to make a humanoid robot understand non-verbal human social behaviors, and we present the results of preliminary experiments to demonstrate the feasibility of the proposed method. In particular, we have focused on the detection and recognition of laughter, a very peculiar human social signal. In fact, although it is a direct form of social interaction, laughter is classified as semi voluntary action, can be elicited by several different stimuli, and it is strongly associated with positive emotion and physical well-being. The possibility of recognize, and further elicit laughter, will help the humanoid robot to interact in a more natural way with humans, to build positive relationships and thus be more socially integrated in the human society.

Original languageEnglish
Pages1396-1401
Number of pages6
DOIs
Publication statusPublished - 2013 Jan 1
Event2013 IEEE International Conference on Robotics and Biomimetics, ROBIO 2013 - Shenzhen, China
Duration: 2013 Dec 122013 Dec 14

Conference

Conference2013 IEEE International Conference on Robotics and Biomimetics, ROBIO 2013
CountryChina
CityShenzhen
Period13/12/1213/12/14

Keywords

  • bioinstrumentation
  • gesture recognition
  • Human-robot interaction
  • humanoid robot
  • sensing

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Biotechnology

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