Online from: 1973
Subject Area: Mechanical & Materials Engineering
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|Title:||Gesture encoding and reproduction for human-robot interaction in text-to-gesture systems|
|Author(s):||Heon-Hui Kim, (Art & Robotics Institute, Kwangwoon University, Seoul, Republic of Korea), Yun-Su Ha, (Division of Information Technology, Korea Maritime University, Pusan, Republic of Korea), Zeungnam Bien, (School of Electrical & Computer Engineering, Ulsan National Institute of Science and Technology, Ulsan, Republic of Korea), Kwang-Hyun Park, (School of Robotics, Kwangwoon University, Seoul, Republic of Korea)|
|Citation:||Heon-Hui Kim, Yun-Su Ha, Zeungnam Bien, Kwang-Hyun Park, (2012) "Gesture encoding and reproduction for human-robot interaction in text-to-gesture systems", Industrial Robot: An International Journal, Vol. 39 Iss: 6, pp.551 - 563|
|Keywords:||Automatic gesture generation, Gesture encoding/decoding, Gesture reproduction, Programming and algorithm theory, Robotics, Text-to-gesture|
|Article type:||Research paper|
|DOI:||10.1108/01439911211268705 (Permanent URL)|
|Publisher:||Emerald Group Publishing Limited|
|Acknowledgements:||This work was partially supported by the research grant of Kwangwoon University in 2008 and by the 2010 research fund of the UNIST.|
Purpose – The purpose of this paper is to deal with a method for gesture encoding and reproduction, particularly aiming at a text-to-gesture (TTG) system that enables robotic agents to generate proper gestures automatically and naturally in human-robot interaction.
Design/methodology/approach – Reproducing proper gestures, naturally synchronized with speech, is important under the TTG concept. The authors first introduce a gesture model that is effective to abstract and describe a variety of human gestures. Based on the model, a gesture encoding/decoding scheme is proposed to encode observed gestures symbolically and parametrically and to reproduce robot gestures from the codes. In particular, this paper mainly addresses a gesture scheduling method that deals with the alignment and refinement of gestural motions, in order to reproduce robotic gesticulation in a human-like, natural fashion.
Findings – The proposed method has been evaluated through a series of questionnaire surveys, and it was found that reproduced gestures by a robotic agent could appeal satisfactorily to human beings.
Originality/value – This paper provides a series of algorithms to treat overlapped motions and to refine the timing parameters for the motions, so that robotic agents reproduce human-like, natural gestures.
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