Abstract
Human robot interaction (HRI) is one of emerging areas in robotics. When robots communicate with people, non-verbal communication including facial expressions, gestures and gaze plays an important role to express their emotion and intention effectively. Thus, many researches are carried out to generate proper non-verbal communications that would make robots to be considered as social agents. This paper proposes a method of generating facial expressions and gaze directions simultaneously. When external environment is perceived, robot’s emotion is changed either instantly or gradually. The emotion is used to generate facial expressions using the fuzzy measures and fuzzy integral. At the same time, a fuzzifier is applied to the perceived information to produce useful human information. The human information includes the number of faces and the size of faces, which can be used to approximate distances from the robot to faces. The human information is used to select a gaze behavior among four candidate behaviors. Through the proposed method, robots can generate proper facial expressions and gaze behaviors at the same time. The effectiveness of the proposed method is demonstrated through the simulation and the experiments with a robotic head, developed in the RIT Laboratory, KAIST.
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References
Breazeal, C.L.: Social interactions in HRI: the robot view. IEEE Trans. Syst. Man Cybern. C Appl. Rev. 34(2), 181–186 (2004), doi:10.1109/TSMCC.2004.826268
Mehrabian, A.: Nonverbal Communication. Aldine-Atherton (1972)
Mehrabian, A.: Communication without words. Psychology Today 2(4), 53–56 (1968)
Koch, C., Ullman, S.: Shifts in selective visual attention: towards the underlying neural circuitry. Human Neurobiology 4, 219–227 (1985)
Cerf, M., Harel, J., Einhäuser, W., Koch, C.: Predicting human gaze using low-level saliency combined with face detection. Advances in Neural Information Processing Systems 20, 241–248 (2008)
Mohammad, Y., Okada, S., Nishida, T.: Autonomous development of gaze control for natural human-robot interaction. Paper presented at 2010 Wrks on Eye Gaze in Intell Human Mach Interaction, Hong Kong, China, pp 63–70 (February 2010), doi: 10.1145/2002333.2002344
Itoh, H., Fukumoto, H., Wakuya, H., Furukawa, T.: Developing a robot that performs tasks of developmental scales: on gaze control by eye-head coordination. Paper presented at SICE Annual Conference 2011, Waseda University, Tokyo, Japan, pp 2488–2491 (September 2011)
Yoo, J.-K., Kim, J.-H.: Fuzzy Integral-based Gaze Control Architecture Incorporated with Modified-univector Field-Based Navigation for Humanoid Robots. IEEE Trans. on Systems, Man and Cybernetics - Part B 42(1), 125–139 (2012)
Ekman, P., Friesen, W.: Unmasking the face: a guide to recognizing emotions from facial expressions. Prentice Hall, Englewood Cliffs (1975)
Sugeno, M.: Theory of fuzzy integrals and its applications. Ph.D. dissertation, Tokyo Institute of Technology (1974)
Sugeno, M.: Fuzzy measures and fuzzy integrals - a survey. Fuzzy Automata and Decision Processes. North Holland, Amsterdam (1977)
Grabisch, M., Nguyen, H.-T., Walker, E.-A.: Fundamentals of uncertainty calculi, with applications to fuzzy inference. Kluwer, Boston (1995)
Yoo, B-S., Cho, S-H., Kim, J-H.: Fuzzy integral-based composite facial expression generation for a robotic head. Paper presented at Int. Conf. on Fuzzy Syst., Taipei, Taiwan, pp 917–923 (June 2011), doi: 10.1109/FUZZY.2011.6007468
Takahagi, E.: A fuzzy measure identification method by diamond pairwise comparisons and φ s transformation. J. Fuzzy Optimization Decision Making 7, 219–232 (2008), doi:10.1007/S10700-008-9032-3
Narukawa, Y., Torra, V.: Fuzzy measure and probability distribution: distorted probabilities. IEEE Trans. Fuzzy Syst. 13, 617–629 (2005), doi:10.1109/TFUZZ.2005.856563
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Yoo, BS., Kim, JH. (2013). A Simultaneous Generation Method for Gaze Behaviors and Facial Expressions of a Robotic Head. In: Kim, JH., Matson, E., Myung, H., Xu, P. (eds) Robot Intelligence Technology and Applications 2012. Advances in Intelligent Systems and Computing, vol 208. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37374-9_14
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DOI: https://doi.org/10.1007/978-3-642-37374-9_14
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