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A Body Emotion-Based Human-Robot Interaction

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Computer Vision Systems (ICVS 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10528))

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Abstract

In order to achieve reasonable and natural interaction when facing vague human actions, a body emotion-based human-robot interaction (BEHRI) algorithm was developed in this paper. Laban movement analysis and fuzzy logic inference was used to extract the movement emotion and torso pose emotion. A finite state machine model was constructed to describe the paradigm of the robot emotion, and then the interactive strategy was designed to generate suitable interactive behaviors. The algorithm was evaluated on UTD-MHAD, and the overall system was tested via questionnaire. The experimental results indicated that the proposed BEHRI algorithm was able to analyze the body emotion precisely, and the interactive behaviors were accessible and satisfying. BEHRI was shown to have good application potentials.

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Acknowledgements

This work has received funding from the Major Research plan of the National Natural Science Foundation of China (91646205), and the National Natural Science Foundation of China (61403368).

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Authors and Affiliations

  1. Department of Automation, Shanghai Jiao Tong University, Shanghai, China

    Tehao Zhu & Qunfei Zhao

  2. Nanjing Research Institute of Electronics Technology, Nanjing, China

    Tehao Zhu

  3. Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China

    Jing Xiong

Authors
  1. Tehao Zhu
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  2. Qunfei Zhao
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  3. Jing Xiong
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Corresponding author

Correspondence to Jing Xiong .

Editor information

Editors and Affiliations

  1. Hong Kong University of Science and Technology, Hong Kong, China

    Ming Liu

  2. Harbin Institute of Technology, Shenzhen, China

    Haoyao Chen

  3. Technische Universtiät Wien, Vienna, Austria

    Markus Vincze

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Zhu, T., Zhao, Q., Xiong, J. (2017). A Body Emotion-Based Human-Robot Interaction. In: Liu, M., Chen, H., Vincze, M. (eds) Computer Vision Systems. ICVS 2017. Lecture Notes in Computer Science(), vol 10528. Springer, Cham. https://doi.org/10.1007/978-3-319-68345-4_24

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  • DOI: https://doi.org/10.1007/978-3-319-68345-4_24

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-68344-7

  • Online ISBN: 978-3-319-68345-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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