Robot Group Adaptation Gestures Based on Utterance Content and Social Position
Daisuke Katagami*, Ken Ogawa**, and Katsumi Nitta**
*Department of Applied Computer Science, Faculty of Engineering, Tokyo Polytechnic University, 1583 Iiyama, Atsugi, Kanagawa 243-0297, Japan
**Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology
We suggest adaptive gestures for robots adapting to groups based on utterance situations and social position and study the differences in type and number of teaching gestures based on the difference in groups in equivalence utterance. Gesture data is collected in which group members are directly taught to a robot through utterance situations and social position to make adaptation rule sets. Such rule sets are built by gestures to work in the group and group utterances to become common knowledge in the group. The degree of gesture adaptation is higher in a group when gestures are generated from a new text as input, confirming goodness of fit for the rule sets of individual groups through experiments.
-  http://www.honda.co.jp/ASIMO/
-  Y. Murakawa and S. Totoki, “Evaluation of “Behavior” of Service Robot “enon”: Experimental operation of enon in a shopping center,” Human-Agent Interaction Symposium 2006, 2006 (in Japanese).
-  T. Kurokawa, “Nonverbal Interface,” Ohmsha, 1994 (in Japanese).
-  Y. Nakano, T. Murayama, and T. Nishida, “Providing Information Through Conversational Agents: Emphasizing Important Concepts Using Nonverbal Information,” Proc. on Sociotechnology Research network, Vol.2, pp. 159-166, 2004 (in Japanese).
-  D. Katagami, T. Nyuwa, and K. Nitta, “Extraction and Analysis of Adaptive Action Skills of Robot under Social HAI,” The 22nd Annual Conf. of the Japanese Society for Artificial Intelligence, 2008 (in Japanese).
-  T. Tomono and T. Hashimoto, “Interpersonal Intolerance of Ambiguity and Adjustment Process of College Freshmen,” J. of Japan Society of Personality Psychology, Vol.14, No.1, pp. 132-134, 2005 (in Japanese).
-  H. Ohmura, D. Katagami, K. Nitta, T. Nozawa, and T. Kondo, “Development of Social Adaptive Agents in Simulation Game of Cross-Cultural Experience,” Human-Agent Interaction Symposium 2008, 2008 (in Japanese).
-  W. Burgard, A. B. Cremers, D. Fox, D. Hahnel, G. Lakemeyer, D. Schulz, W. Steiner, and S. Thrun, “The Interactive Museum Tour- Guide Robot,” Proc. of National Conference on Artificial Intelligence (AAAI98), pp. 11-18, 1998.
-  J. Tsukamoto, Y. Hirano, S. Kajita, and K. Mase, “Community Communication Using a Robot Providing Topics of Conversation,” The 21st Annual Conf. of the Japanese Society for Artificial Intelligence, 2007 (in Japanese).
-  B. Endrass, M. Rehm, and E. Andre, “Culture specific Communication Management for Virtual Agents,” AAMAS 2009, 2009.
-  M. Kotake, D. Katagami, and K. Nitta, “Acquisition of behavioral patterns depends on self-embodiment based on robot learning from multiple instructors,” J. of Advanced Computational Intelligence and Intelligent Informatics, Vol.11, No.8, pp. 989-997, 2007.
-  http://www.sony.jp/products/Consumer/aibo/
-  F. Yamaoka, T. Kanda, H. Ishiguro, and N. Hagita, “Interacting with a Human or a Humanoid Robot?,” Information Processing Society of Japan 2007, Vol.48, No.11, pp. 3577-3587, 2007 (in Japanese).
-  A. Green, H. Huttenrauch, and K. S. Eklundh, “Applying the Wizard-of- Oz framework to cooperative service discovery and configuration,” Proc. 13th IEEE Int. Workshop on Robot and Human Interactive Communication (Ro-Man 2004), pp. 575-580, 2004.
-  M. L. Walters, K. Dautenhahn, R. Boekhorst, K. L. Koay, C. Kaouri, S. Woods, C. Nehaniv, D. Lee, and I. Werry, “The Influence of Participants’ Personality Traits on Personal Spatial Zones in a Human-Robot Interaction Experiment,” IEEE Int. Workshop on Robot and Human Communication (Ro-Man 2005), pp. 347-352, 2005.
-  H. Sakoe and S. Chiba, “Dynamic Programing Algorithm Optimization for SpokenWord Recognition,” IEEE Trans. on Acoustics, Speech, and Signal Processing, Vol.ASSP-26, No.1, pp. 43-49, 1978.
-  Y. Yamada, E. Suzuki, H. Yokoi, and K. Takabayashi, “Decisiontree Induction from Time-series Data Based on a Standard-example Split Test,” Proc. Twentieth Int. Conf. on Machine Learning (ICML), pp. 840-847, 2003.
-  http://www.speecys.com/
-  http://www.ai-j.jp/
This article is published under a Creative Commons Attribution-NoDerivatives 4.0 International License.