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A Real-Time Robot Motion Generation System Based on Human Gesture

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Advances on Broadband and Wireless Computing, Communication and Applications (BWCCA 2018)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 25))

Abstract

When a communication robot conveys some messages to human users, showing some motions matching with the messages is an effective way in human robot interaction. Designing and implementing a set of useful robot motions, however, is a difficult problem. It requires developers to describe instructions for accurately controlling motors embedded in the robot. In this paper, we propose a method for generating robot motions by using human gestures as input. The proposed method captures human gestures in real time by using motion sensors, converting the acquired data to robot motion instructions, and applying them to a physical robot. We developed a prototype system targeted at supporting different motion sensors and robots with lightweight data communication between a control node and a robot. We conducted experiments for controlling the robots by human gestures to verify the effectiveness of the proposed method. It can promote better human robot communication environments with reducing labors in robot motion development.

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References

  1. Shimizu, D., Haramaki, T., Nishino, H.: A mobile wireless network visualizer for assisting administrators. In: Proceedings of the 6th International Conference on Emerging Internet, Data and Web Technologies, pp. 651–662 (2018)

    Chapter  Google Scholar 

  2. Yatsuda, A., Haramaki, T., Nishino, H.: An Unsolicited heat stroke alert system for the elderly. In: Proceedings of the 2017 IEEE International Conference on Consumer Electronics - Taiwan, pp. 347–348 (2017)

    Google Scholar 

  3. Haramaki, T., Yatsuda, A., Nishino, H.: A robot assistant in an edge-computing-based safe driving support system. In: Proceedings of the 21th International Conference on Network-Based Information Systems, pp. 144–155 (2018)

    Google Scholar 

  4. Okazaki, S., Haramaki, T., Nishino, H.: A safe driving support method using olfactory stimuli. In: Proceedings of the 12th International Conference on Complex, Intelligent and Software Intensive Systems, pp. 958–967 (2018)

    Google Scholar 

  5. Matsui, D., Minato, T., MacDorman, K., Ishiguro, H.: Generating natural motion in an android by mapping human motion. In: Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 3301–3308 (2005)

    Google Scholar 

  6. Imai, M.: Why do we have to use a robot? IPSJ Mag. 59(8), 692–697 (2018). (in Japanese)

    Google Scholar 

  7. Cicirelli, G., Attolico, C., Guaragnella, C., D’Orazio, T.: A kinect-based gesture recognition approach for a natural human robot interface. Int. J. Adv. Rob. Syst. 12(3), 1–11 (2015)

    Google Scholar 

  8. Qureshi, A.H., Nakamura, Y., Yoshikawa, Y., Ishiguro, H.: Show, attend and interact: perceivable human-robot social interaction through neural attention Q-network. In: Proceedings of IEEE International Conference on Robotics and Automation, pp. 1639–1645 (2017)

    Google Scholar 

  9. Jung, J., Kanda, T., Kim, M.-S.: Guidelines for contextual motion design of a humanoid robot. Int. J. Social Robot. 5(2), 153–169 (2013)

    Article  Google Scholar 

  10. Leap Motion. https://www.leapmotion.com/. Accessed July 2018

  11. Cao, Z., Simon, T., Wei, S.-E., Sheikh, Y.: Realtime multi-person 2D pose estimation using part affinity fields. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 1302–1310 (2017)

    Google Scholar 

  12. Mehta, D., Sridhar, S., Sotnychenko, O., Rhodin, H., Shafiei, M., Seidel, H.-P., Xu, W., Casas, D., Theobalt, C.: VNect: real-time 3D human pose estimation with a single RGB camera. ACM Trans. Graph. 36(4), 44:1–44:14 (2017)

    Article  Google Scholar 

  13. Sota. https://sota.vstone.co.jp/home/. Accessed Aug 2018. (in Japanese)

  14. Pepper. https://www.softbank.jp/robot/pepper/. Accessed Aug 2018. (in Japanese)

  15. MQTT. http://mqtt.org/. Accessed July 2018

  16. Mosquitto. https://mosquitto.org/. Accessed July 2018

  17. Eclipse Paho. https://www.eclipse.org/paho/. Accessed July 2018

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Author information

Authors and Affiliations

  1. Faculty of Science and Technology, Oita University, Oita, Japan

    Toshiyuki Haramaki & Hiroaki Nishino

  2. Graduate School of Engineering, Oita University, Oita, Japan

    Kenta Goto, Hokuto Tsutsumi & Akihito Yatsuda

Authors
  1. Toshiyuki Haramaki
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  2. Kenta Goto
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  3. Hokuto Tsutsumi
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  4. Akihito Yatsuda
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  5. Hiroaki Nishino
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Corresponding author

Correspondence to Hiroaki Nishino .

Editor information

Editors and Affiliations

  1. Department of Information and Communication Engineering, Faculty of Information Engineering, Fukuoka Institute of Technology, Fukuoka, Japan

    Leonard Barolli

  2. Tunghai University, Taichung, Taiwan

    Fang-Yie Leu

  3. Rissho University, Tokyo, Japan

    Tomoya Enokido

  4. Asia University, Taichung, Taiwan

    Hsing-Chung Chen

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Haramaki, T., Goto, K., Tsutsumi, H., Yatsuda, A., Nishino, H. (2019). A Real-Time Robot Motion Generation System Based on Human Gesture. In: Barolli, L., Leu, FY., Enokido, T., Chen, HC. (eds) Advances on Broadband and Wireless Computing, Communication and Applications. BWCCA 2018. Lecture Notes on Data Engineering and Communications Technologies, vol 25. Springer, Cham. https://doi.org/10.1007/978-3-030-02613-4_12

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  • DOI: https://doi.org/10.1007/978-3-030-02613-4_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-02612-7

  • Online ISBN: 978-3-030-02613-4

  • eBook Packages: EngineeringEngineering (R0)

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