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Virtual plate based controlling strategy of toy play for robot’s communication development in JA space

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Abstract

Toy play is a basic skill for a humanoid robot after it has joint attention (JA) ability. Because such skill is helpful for human-robot interaction and cooperation, we must realize this skill to enhance the robots communication ability with person. In this paper, we researched a toy play controlling strategy in JA space based on a virtual plate with a serial robot arm, which has five degrees of freedom (5-DoF). For this purpose, a reachable space of joint attention was constructed firstly. And then the toy play controlling strategy was proposed in details. Here we used a virtual plate to enhance the toy play effect. In order to realize this skill better, toy play energy and some restraining relations were analyzed. By contrasting the audio waveform in the experiments, good performance effect of toy play was demonstrated.

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References

  1. T. Charman, S. Baron-Cohen, J. Swettenham, G. Baird, A. Cox, A. Drew. Testing joint attention, imitation, and play as infancy precursors to language and theory of mind. Cognitive Development, vol. 15, no. 4, pp. 481–498, 2000.

    Article  Google Scholar 

  2. S. Dunphy-Lelii, J. LaBounty, J. D. Lane, H. M. Wellman. The social context of infant intention understanding. Journal of Cognition and Development, vol. 15, no. 1, pp. 60–77, 2014.

    Article  Google Scholar 

  3. T. Grossmann, S. Lloyd-Fox, M. H. Johnson. Brain responses reveal young infants’sensitivity to when a social partner follows their gaze. Developmental Cognitive Neuroscience, vol. 6, pp. 155–161, 2013.

    Article  Google Scholar 

  4. Z. Y. Xia, L. Li, J. Xiong, Y. Qiang, K. Chen. Design aspects and development of humanoid robot THBIP-2. Robotica, vol. 26, no. 1, pp. 109–116, 2008.

    Article  Google Scholar 

  5. L. G. Zhang, Q. Huang, J. Yang, Y. Shi, Z. J. Wang, A. R. Jafri. Design of humanoid complicated dynamic motion with similarity considered. Acta Automatica Sinica, vol. 33, no. 5, pp. 522–528, 2007. (in Chinese)

    Article  MATH  Google Scholar 

  6. H. Sumioka, Y. Yoshikawa, M. Asada. Reproducing interaction contingency toward open-ended development of social actions: case study on joint attention. IEEE Transactions on Autonomous Mental Development, vol. 2, no. 1, pp. 40–50, 2010.

    Article  Google Scholar 

  7. C. M. Huang, A. L. Thomaz. Joint attention in human-robot interaction. In Proceedings of the AAAI Fall Symposium, AAAI, Menlo Park, USA, pp. 32–37, 2010.

    Google Scholar 

  8. S. M. Anzalone, S. Boucenna, S. Ivaldi, M. Chetouani. Evaluating the engagement with social robots. International Journal of Social Robotics, vol. 7, no. 4, pp. 465–478, 2015.

    Article  Google Scholar 

  9. J. F. Ferreira, J. Dias. Attentional mechanisms for socially interactive robots-A survey. IEEE Transactions on Autonomous Mental Development, vol. 6, no. 2, pp. 110–125, 2014.

    Article  Google Scholar 

  10. G. Skantze, A. Hjalmarsson, C. Oertel. Turn-taking, feedback and joint attention in situated human-robot interaction. Speech Communication, vol. 65, pp. 50–66, 2014.

    Article  Google Scholar 

  11. T. Ichijo, N. Munekata, K. Hiraki, T. Ono. Entrainment effect caused by joint attention of two robots. In Proceedings of the 9th Annual ACM/IEEE International Conference on Human-Robot Interaction, ACM, New York, USA, pp. 178–179, 2014.

    Google Scholar 

  12. E. Carlson, J. Triesch. A computational model of the emergence of gaze following. Connectionist Models of Cognition and Perception II, H. Bowman, C. Labiouse, Eds., Singapore: World Scientific, pp. 105–114, 2003.

    Google Scholar 

  13. Y. Nagai, K. Hosoda, A. Morita, M. Asada. A constructive model for the development of joint attention. Connection Science, vol. 15, no. 4, pp. 211–229, 2003.

    Article  Google Scholar 

  14. C. Breazeal, D. Buchsbaum, J. Grey, D. Gatenby, B. Blumberg. Learning from and about others: Towards using imitation to bootstrap the social understanding of others by robots. Artificial Life, vol. 11, no. 1–2, pp. 31–62, 2005.

    Article  Google Scholar 

  15. M. Imai, T. Ono, H. Ishiguro. Physical relation and expression: Joint attention for human-robot interaction. IEEE Transactions on Industrial Electronics, vol. 50, no. 4, pp. 636–643, 2003.

    Article  Google Scholar 

  16. Y. Nagai, M. Asada, K. Hosoda. Learning for joint attention helped by functional development. Advanced Robotics, vol. 20, no. 10, pp. 1165–1181, 2006.

    Article  Google Scholar 

  17. H. Sumioka, K. Hosoda, Y. Yoshikawa, M. Asada. Acquisition of joint attention through natural interaction utilizing motion cues. Advanced Robotics, vol. 21, no. 9, pp. 983–999, 2007.

    Article  Google Scholar 

  18. M. Hashimoto, H. Kondo, Y. Tamatsu. Gaze guidance using a facial expression robot. Advanced Robotics, vol. 23, no. 14, pp. 1831–1848, 2009.

    Article  Google Scholar 

  19. J. K. Chu, R. H. Li, Q. Y. Li, H. Q. Wang. A visual attention model for robot object tracking. International Journal of Automation and Computing, vol. 7, no. 1, pp. 39–46, 2010.

    Article  Google Scholar 

  20. C. Breazeal. Robot in society: Friend or appliance?. In Proceedings of Autonomous Agents Workshop on Emotion-based Agent Architectures, IEEE, Seattle, USA, pp. 11–37, 1999.

    Google Scholar 

  21. Z. Leon. Robotic yo-yo: Modelling and control strategies. Robotica, vol. 24, no. 2, pp. 211–220, 2006.

    Google Scholar 

  22. T. Petrivc, A. Gams, A. J. Ijspeert, L. v Zlajpah. On-line frequency adaptation and movement imitation for rhythmic robotic tasks. The International Journal of Robotics Research, vol. 30, no. 14, pp. 1775–1788, 2011.

    Article  Google Scholar 

  23. A. Cooka, E. Pedro, A. Kim. Robots: Assistive technologies for play, learning and cognitive development. Technology and Disability, vol. 22, no. 3, pp. 127–145, 2010.

    Google Scholar 

  24. W. G. Song. Robotics: Kinematics, Dynamics and Control, Beijing, China: Science Press, pp. 18–56, 2007. (in Chinese)

    Google Scholar 

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Acknowledgments

This work was supported by Hebei Province Natural Science Foundation for Youths (No. F2015402108), the Foundation for Young Scholars of Hebei Educational Committee (No.QN20131152), Handan Municipal Science and Technology Projects (No. 1421103054).

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Correspondence to Wei Wang.

Additional information

Recommended by Associate Editor Lihui Wang

Wei Wang received the M. Sc. degree in control theory and control engineering from Jiangnan University, China in 2008, and the Ph.D. degree from University of Science and Technology Beijing, China in 2012. Since 2012, he has been a faculty member at Hebei University of Engineering, China. He has published about 40 refereed journal and conference papers.

His research interests include human-robot cooperation and implicit interaction.

Xiao-dan Huang received the M. Sc. degree in electronic information from University of Science and Technology Beijing, China in 2012. Since 2012, she has been a faculty member at Hebei University of Engineering, China. She has published about 10 refereed journal and conference papers.

Her research interests include robotics and implicit interaction.

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Wang, W., Huang, XD. Virtual plate based controlling strategy of toy play for robot’s communication development in JA space. Int. J. Autom. Comput. 16, 93–101 (2019). https://doi.org/10.1007/s11633-016-1022-2

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