Gaze Behavioral Adaptation Towards Group Members for Providing Effective Recommendations
An adequate robot gaze control is essential for successful and natural human-robot interactions. In multi-party contexts, the effective use of the gaze shared among the participants may have a strong impact in keeping the participants’ attention and obtaining a persuasive effect. To gain a deeper understanding of how the robot gaze behavior might influence and shape the human perception of the interaction and the decision-making process in small groups, we conducted a between-subjects experimental study using a humanoid robot in a movie recommendation scenario. Our results showed that different gaze behaviors resulted in different group acceptance rates if combined with the personal acceptance of the group members. However, users were not able to differentiate the behaviors in term of naturalness and persuasiveness. Moreover, results showed that other factors, such as the length of the recommendation, play a significant role in the users’ perception of the interaction naturalness.
This work has been partially supported by MIUR within the PRIN2015 research project “User-centered Profiling and Adaptation for Socially Assistive Robotics - UPA4SAR”.
- 1.Admoni, H., Hayes, B., Feil-Seifer, D., Ullman, D., Scassellati, B.: Are you looking at me?: perception of robot attention is mediated by gaze type and group size. In: Proceedings of the 8th ACM/IEEE International Conference on HRI, pp. 389–396 (2013)Google Scholar
- 2.Cozzolongo, G., De Carolis, B., Pizzutilo, S.: Social robots as mediators between users and smart environments. In: Proceedings of the 12th International Conference on Intelligent User Interfaces, IUI 2007, pp. 353–356. ACM, New York (2007)Google Scholar
- 5.Imai, M., Kanda, T., Ono, T., Ishiguro, H., Mase, K.: Robot mediated round table: analysis of the effect of robot’s gaze. In: Proceedings of 11th IEEE International Workshop on Robot and Human Interactive Communication, pp. 411–416 (2002)Google Scholar
- 6.Karreman, D.E., Bradford, G.U.S., van Dijk, E.M., Lohse, M., Evers, V.: Picking favorites: the influence of robot eye-gaze on interactions with multiple users. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 123–128, November 2013Google Scholar
- 8.Koda, T., Ogura, M., Matsui, Y.: Shyness level and sensitivity to gaze from agents - are shy people sensitive to agent’s gaze? In: Traum, D., Swartout, W., Khooshabeh, P., Kopp, S., Scherer, S., Leuski, A. (eds.) IVA 2016. LNCS, vol. 10011, pp. 359–363. Springer, Cham (2016). doi: 10.1007/978-3-319-47665-0_33 CrossRefGoogle Scholar
- 9.Mutlu, B., Forlizzi, J., Hodgins, J.: A storytelling robot: modeling and evaluation of human-like gaze behavior. In: 6th IEEE-RAS International Conference on Humanoid Robots, pp. 518–523, December 2006Google Scholar
- 11.Mutlu, B., Shiwa, T., Kanda, T., Ishiguro, H., Hagita, N.: Footing in human-robot conversations: how robots might shape participant roles using gaze cues. In: 4th ACM/IEEE International Conference on HRI, pp. 61–68. ACM (2009)Google Scholar
- 13.Rossi, S., Cervone, F.: Social utilities and personality traits for group recommendation: a pilot user study. In: Proceedings of the 8th International Conference on Agents and Artificial Intelligence, pp. 38–46 (2016)Google Scholar
- 14.Shinozawa, K., Naya, F., Kogure, K., Yamato, J.: Effect of robot’s tracking users on human decision making. In: IROS, pp. 1908–1913. IEEE (2004)Google Scholar
- 15.Staffa, M., Gregorio, M.D., Giordano, M., Rossi, S.: Can you follow that guy?. In: 22th European Symposium on Artificial Neural Networks, ESANN, pp. 511–516 (2014)Google Scholar
- 17.Yoshino, T., Takase, Y., Nakano, Y.I.: Controlling robot’s gaze according to participation roles and dominance in multiparty conversations. In: Tenth Annual ACM/IEEE International Conference on HRI, Extended Abstracts, pp. 127–128. ACM (2015)Google Scholar