ABSTRACT
When should service staff initiate interaction with a visitor? Neither simply-proactive (e.g. talk to everyone in a sight) nor passive (e.g. wait until being talked to) strategies are desired. This paper reports our modeling of polite approaching behavior. In a shopping mall, there are service staff members who politely approach visitors who need help. Our analysis revealed that staff members are sensitive to "intentions" of nearby visitors. That is, when a visitor intends to talk to a staff member and starts to approach, the staff member also walks a few steps toward the visitors in advance to being talked. Further, even when not being approached, staff members exhibit "availability" behavior in the case that a visitor's intention seems uncertain. We modeled these behaviors that are adaptive to pedestrians' intentions, occurred prior to initiation of conversation. The model was implemented into a robot and tested in a real shopping mall. The experiment confirmed that the proposed method is less intrusive to pedestrians, and that our robot successfully initiated interaction with pedestrians.
Supplemental Material
- H.-M. Gross, et al., Shopbot: Progress in Developing an Interactive Mobile Shopping Assistant for Everyday Use, IEEE Int. Conf. on Systems, Man, and Cybernetics (SMC2008), pp. 3471--3478, 2008.Google ScholarCross Ref
- R. Kirby, J. Forlizzi and R. Simmons, Affective Social Robots, Robotics and Autonomous Systems, vol. 58, pp. 322332, 2010. Google ScholarDigital Library
- S. Satake, et al., How to Approach Humans?: Strategies for Social Robots to Initiate Interaction, ACM/IEEE Int. Conf. on Human-Robot Interaction (HRI2009), pp. 109--116, 2009. Google ScholarDigital Library
- E. T. Hall, The Hidden Dimension, Doubleday, 1966.Google Scholar
- M. L. Walters, et al., The Influence of Subjects' Personality Traits on Personal Spatial Zones in a Human-Robot Interaction Experiment, IEEE Int. W. on Robot and Human Interactive Communication (RO-MAN2005), pp. 347--352, 2005.Google Scholar
- H. Hüttenrauch, K. S. Eklundh, A. Green and E. A. Topp, Investigating Spatial Relationships in Human-Robot Interactions, IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS2006), pp. 5052--5059, 2006.Google ScholarCross Ref
- D. Feil-Seifer and M. Matarić, Distance-Based Computational Models for Facilitating Robot Interaction with Children, J. of Human-Robot Interaction, vol. 1, pp. 55--77, 2012.Google ScholarDigital Library
- E. A. Sisbot, et al., Implementing a Human-Aware Robot System, IEEE Int. Symposium on Robot and Human Interactive Communication (RO-MAN2006), pp. 727--732, 2006.Google ScholarCross Ref
- H. Kuzuoka, Y. Suzuki, J. Yamashita and K. Yamazaki, Reconfiguring Spatial Formation Arrangement by Robot Body Orientation, ACM/IEEE Int. Conf. on Human-Robot Interaction (HRI2010), pp. 285--292, 2010. Google ScholarDigital Library
- J. Mumm and B. Mutlu, Human-Robot Proxemics: Physical and Psychological Distancing in Human-Robot Interaction, ACM/IEEE Int. Conf. on Human-Robot Interaction (HRI2011), pp. 331--338, 2011. Google ScholarDigital Library
- M. P. Michalowski, S. Sabanovic and R. Simmons, A Spatial Model of Engagement for a Social Robot, IEEE Int. Workshop on Advanced Motion Control, pp. 762--767, 2006.Google ScholarCross Ref
- K. Yamazaki, et al., Prior-to-Request and Request Behaviors within Elderly Day Care: Implications for Developing Service Robots for Use in Multiparty Settings, European Conf. on Computer Supported Cooperative Work, pp. 61--78, 2007.Google Scholar
- Y. Kobayashi, et al., A Considerate Care Robot Able to Serve in Multi-Party Settings, IEEE Int. Symposium on Robot and Human Interactive Communication (RO-MAN2011), pp. 27--32, 2011.Google Scholar
- C. L. Sidner, C. Lee, C. D. Kidd, N. Lesh and C. Rich, Explorations in Engagement for Humans and Robots, Artificial Intelligence, vol. 166, pp. 140--164, 2005. Google ScholarDigital Library
- M. A. Yousuf, et al., How to Move Towards Visitors: A Model for Museum Guide Robots to Initiate Conversation, IEEE Int. Symp. on Robot and Human Interactive Communication (RO-MAN2013), pp. 587--592, 2013.Google Scholar
- K. Dautenhahn, et al., How May I Serve You? A Robot Companion Approaching a Seated Person in a Helping Context, ACM/IEEE Int. Conf. on Human-Robot Interaction (HRI2006), pp. 172--179, 2006. Google ScholarDigital Library
- C. Shi, M. Shimada, T. Kanda, H. Ishiguro and N. Hagita, Spatial Formation Model for Initiating Conversation, Robotics: Science and Systems Conference (RSS2011), 2011.Google Scholar
- J. Kessler, C. Schroeter and H.-M. Gross, Approaching a Person in a Socially Acceptable Manner Using a Fast Marching Planner, in Intelligent Robotics and Applications, Springer, pp. 368--377, 2011. Google ScholarDigital Library
- V. Rousseau, et al., Sorry to Interrupt, but May I Have Your Attention? Preliminary Design and Evaluation of Autonomous Engagement in HRI, J. of Human-Robot Interaction, vol. 2, pp. 41--61, 2013.Google ScholarDigital Library
- B. Scassellati, Theory of Mind for a Humanoid Robot, Autonomous Robots, vol. 12, pp. 13--24, 2002. Google ScholarDigital Library
- C. Breazeal, C. D. Kidd, A. L. Thomaz, G. Hoffman and M. Berlin, Effects of Nonverbal Communication on Efficiency and Robustness in Human-Robot Teamwork, IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS2005), pp. 383--388, 2005.Google ScholarCross Ref
- H. Hüttenrauch and K. S. Eklundh, To Help or Not to Help a Service Robot: Bystander Intervention as a Resource in Human-Robot Collaboration, Interaction Studies, vol. 7, pp. 455--477, 2006.Google ScholarCross Ref
- B. Mutlu, T. Shiwa, T. Kanda, H. Ishiguro and N. Hagita, Footing in Human-Robot Conversations: How Robots Might Shape Participant Roles Using Gaze Cues, ACM/IEEE Int. Conf. on Human-Robot Interaction (HRI2009), pp. 61--68, 2009. Google ScholarDigital Library
- K. Fischer, L. C. Jensen and L. Boenhagen, To Beep or Not to Beep Is Not the Whole Question, Int. Conf. on Social Robotics, pp. 156--165, 2014.Google ScholarCross Ref
- K. Fischer, et al., Initiating Interactions in Order to Get Help: Effects of Social Framing on People's Responses to Robots' Requests for Assistance, IEEE Int. Symp. on Robot and Human Interactive Communication (RO-MAN2014), pp. 999--1005, 2014.Google Scholar
- L. Takayama, D. Dooley and W. Ju, Expressing Thought: Improving Robot Readability with Animation Principles, ACM/IEEE Int. Conf. on Human-Robot Interaction (HRI2011), pp. 69--76, 2011. Google ScholarDigital Library
- R. Kelley, et al., Understanding Human Intentions Via Hidden Markov Models in Autonomous Mobile Robots, ACM/IEEE Int. Conf. on Human-Robot Interaction (HRI2008), pp. 367--374, 2008. Google ScholarDigital Library
- D. Brscic, T. Kanda, T. Ikeda and T. Miyashita, Person Tracking in Large Public Spaces Using 3d Range Sensors, IEEE Trans. on Human-Machine Systems, vol. 43, pp. 522 - 534, 2013.Google ScholarCross Ref
- C.-C. Chang and C.-J. Lin, Libsvm: A Library for Support Vector Machines, ACM Transactions on Intelligent Systems and Technology (TIST), vol. 2, p. 27, 2011. Google ScholarDigital Library
Index Terms
- May I help you?: Design of Human-like Polite Approaching Behavior
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