We discuss an experiment investigating the influence of social cues expressed by a robot on human attributions of interpersonal characteristics towards a robot and assessments of its interaction behaviors. During a hallway navigation scenario, participants were exposed to varying expressions of proxemic behavior and gaze cues over repeated interactions with a robot. Analysis of participant perceptions of the robot’s personality revealed that cues indicative of socially mindful behavior expressed by the robot promote positive interpersonal attributions and perceptions of safe robot behavior. Results of the present study contribute to the scholarly discussion on robotic design for encouraging natural and effective interactions between humans and robots.
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References
1.
BatesD.M.MaechlerM.BolkerB. (2012). lme4: Linear mixed-effects models using S4 classes. R package version 1.1-7.
2.
BaayenR. H.DavidsonD. J.BatesD. M. (2008). Mixed-effects modeling with crossed random effects for subjects and items. Journal of Memory and Language, 59(4), 390-412.
3.
CastielloU. (2003). Understanding other people’s actions: intention and attention. Journal of Experimental Psychology: Human Perception and Performance, 29(2), 416.
4.
ChangW. L.SabanovicS.HuberL. (2014, August). Observational study of naturalistic interactions with the socially assistive robot PARO in a nursing home. In Robot and Human Interactive Communication, 2014 RO-MAN: The 23rd IEEE International Symposium on (pp. 294-299). IEEE.
5.
CohenJ.CohenP.WestS. G.AikenL. S. (2003). Applied multiple correlation/regression analysis for the behavioral sciences. Hillsdale, NJ: Lawrence Erlbaum.
6.
DelahercheE.ChetouaniM.MahdhaouiA.Saint-GeorgesC.ViauxS.CohenD. (2012). Interpersonal synchrony: A survey of evaluation methods across disciplines. Affective Computing, IEEE Transactions on, 3(3), 349-365.
7.
FioreS. M.WiltshireT. J.LobatoE. J. C.JentschF. G.HuangW. H.AxelrodB. (2013). Towards understanding social cues and signals in human-robot interaction: Effects of robot gaze and proxemics behavior. Frontiers in Psychology: Cognitive Science, 4(859), 1-15. DOI: 10.3389/fpsyg.2013.00859
8.
FranklinS.StrainS.McCallR.BaarsB. (2013). Conceptual Commitments of the LIDA Model of Cognition. Journal of Artificial General Intelligence, 4(2), 1-22.
9.
GangopadhyayN.SchilbachL. (2012). Seeing minds: a neurophilosophical investigation of the role of perception-action coupling in social perception. Social Neuroscience, 7(4), 410-423.
10.
HallE. T. (1963). A system for the notation of proxemic behavior. American Anthropologist, 65(5), 1003-1026.
11.
HegelF.GieselmannS.PetersA.HolthausP.WredeB. (2011, July). Towards a typology of meaningful signals and cues in social robotics. In RO-MAN, 2011 IEEE (pp. 72-78). IEEE.
12.
KleinkeC. L. (1986). Gaze and eye contact: a research review. Psychological Bulletin, 100(1), 78.
13.
MummJ.MutluB. (2011, March). Human-robot proxemics: physical and psychological distancing in human-robot interaction. Proceedings of the 6th international conference on Human-robot interaction (pp. 331-338).
14.
MutluB.YamaokaF.KandaT.IshiguroH.HagitaN. (2009, March). Nonverbal leakage in robots: communication of intentions through seemingly unintentional behavior. In Proceedings of the 4th ACM/IEEE international conference on Human robot interaction (pp. 69-76). ACM.
15.
PitschK.VollmerA. L.MuhligM. (2013). Robot feedback shapes the tutor’s presentation: How a robot’s online gaze strategies lead to micro-adaptation of the human’s conduct. Interaction Studies, 14(2).
16.
Rios-MartinezJ.SpalanzaniA.LaugierC. (2014). From Proxemics Theory to Socially-Aware Navigation: A Survey. International Journal of Social Robotics, 7(2), 137-153.
17.
RozgicV.XiaoB.KatsamanisA.BaucomB.GeorgiouP. G.NarayananS. (2011, May). Estimation of ordinal approach-avoidance labels in dyadic interactions: Ordinal logistic regression approach. In Acoustics, Speech and Signal Processing (ICASSP), 2011 IEEE International Conference on (pp. 2368-2371). IEEE.
18.
SaulnierP.SharlinE.GreenbergS. (2011, July). Exploring minimal nonverbal interruption in HRI. In RO-MAN, 2011 IEEE (pp. 79-86).
19.
SrinivasanV.BethelC. L.MurphyR.NassC. (2012). Validation of a behavioral robotics framework for social head gaze. In Proceedings of the “Gaze in Human-Robot Interaction” Workshop held at the 7th ACM/IEEE International Conference on Human-Robot Interaction (HRI 2012)March 5, 2012, Boston, MA.
20.
TakayamaL.PantofaruC. (2009, October). Influences on proxemic behaviors in human-robot interaction. In Intelligent Robots and Systems, 2009. IROS 2009. IEEE/RSJ International Conference on (pp. 5495-5502). IEEE.
21.
Van DoesumN. J.Van LangeD. A. W.Van LangeP. A. M. (2013). Social mindfulness: Skills and will to navigate the social world. Journal of Personality and Social Psychology, 105(1), 86-103.
22.
VinciarelliA.PanticM.BourlardH. (2009). Social signal processing: Survey of an emerging domain. Image and Vision Computing, 27(12), 1743-1759.
23.
WiltshireT. J.FioreS. M. (2014). Social, cognitive, and affective neuroscience in human-machine systems: A roadmap for improving training, human-robot interaction, and team performance. IEEE Transactions on Human-Machine Systems, 44(6), 779-787.DOI: 10.1109/THMS.2014.2343996
24.
WiltshireT. J.LobatoE. J. C.McConnellD.FioreS. M. (2015). Prospects for direct social perception: A multi-theoretical integration to further the science of social cognition. Frontiers in Human Neuroscience, 8(1007). DOI: 10.3389/fnhum.2014.01007.
25.
WiltshireT. J.SnowS. L.LobatoE. J. C.FioreS. M. (2014). Leveraging social judgment theory to examine the relationship between social cues and signals in human-robot interactions. In Proceedings of the Human Factors and Ergonomics Society 58th Annual Meeting, 1336-1340.
26.
WiltshireT. J.LobatoE. J. C.WedellA.HuangW.AxelrodBFioreS. M. (2013). Effects of robot gaze and proxemic behavior on perceived social presence during a hallway navigation scenario. In Proceedings of the Human Factors and Ergonomics Society 57th Annual Meeting, 1273-1277.
27.
WinterB. (2013). Linear models and linear mixed effects models in R with linguistic applications. arXiv:1308.5499. [http://arxiv.org/pdf/1308.5499.pdf]
