ABSTRACT
Drones are rapidly populating human spaces, yet little is known about how these flying robots are perceived and understood by humans. Recent works suggested that their acceptance is predicated upon their sociability. This paper explores the use of facial expressions to represent emotions on social drones. We leveraged design practices from ground robotics and created a set of rendered robotic faces that convey basic emotions. We evaluated individuals’ response to these emotional facial expressions on drones in two empirical studies (N = 98, N = 98). Our results demonstrate that individuals accurately recognize five drone emotional expressions, as well as make sense of intensities within emotion categories. We describe how participants were emotionally affected by the drone, showed empathy towards it, and created narratives to interpret its emotions. As a consequence, we formulate design recommendations for social drones and discuss methodological insights on the use of static versus dynamic stimuli in affective robotics studies.
Supplemental Material
- Dante Arroyo, Cesar Lucho, Silvia Julissa Roncal, and Francisco Cuellar. 2014. Daedalus: A sUAV for Human-Robot Interaction. In Proceedings of the 2014 ACM/IEEE International Conference on Human-Robot Interaction (Bielefeld, Germany) (HRI ’14). Association for Computing Machinery, New York, NY, USA, 116–117. https://doi.org/10.1145/2559636.2563709Google ScholarDigital Library
- Mauro Avila Soto, Markus Funk, Matthias Hoppe, Robin Boldt, Katrin Wolf, and Niels Henze. 2017. DroneNavigator: Using Leashed and Free-Floating Quadcopters to Navigate Visually Impaired Travelers. In Proceedings of the 19th International ACM SIGACCESS Conference on Computers and Accessibility (Baltimore, Maryland, USA) (ASSETS ’17). Association for Computing Machinery, New York, NY, USA, 300–304. https://doi.org/10.1145/3132525.3132556Google ScholarDigital Library
- Tadas Baltrušaitis, Laurel D. Riek, and Peter Robinson. 2010. Synthesizing Expressions Using Facial Feature Point Tracking: How Emotion is Conveyed. In Proceedings of the 3rd International Workshop on Affective Interaction in Natural Environments (Firenze, Italy) (AFFINE ’10). Association for Computing Machinery, New York, NY, USA, 27–32. https://doi.org/10.1145/1877826.1877835Google ScholarDigital Library
- Christoph Bartneck, Juliane Reichenbach, and Albert van Breemen. 2004. In your face, robot! The influence of a character’s embodiment on how users perceive its emotional expressions. In Proceedings of Design and Emotion 2004 Conference (Ankara, Turkey). 32–51.Google Scholar
- Joseph Bates. 1994. The Role of Emotion in Believable Agents. Commun. ACM 37, 7 (July 1994), 122–125. https://doi.org/10.1145/176789.176803Google ScholarDigital Library
- Roy Baumeister, Kathleen Vohs, C DeWall, and Liqing Zhang. 2007. How Emotion Shapes Behavior: Feedback, Anticipation, and Reflection, Rather Than Direct Causation. Personality and Social Psychology Review 11 (06 2007), 167–203. https://doi.org/10.1177/1088868307301033Google ScholarCross Ref
- Mehmet Aydin Baytas, Damla Çay, Yuchong Zhang, Mohammad Obaid, Asim Evren Yantaç, and Morten Fjeld. 2019. The Design of Social Drones: A Review of Studies on Autonomous Flyers in Inhabited Environments. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (Glasgow, Scotland Uk) (CHI ’19). Association for Computing Machinery, New York, NY, USA, 1–13. https://doi.org/10.1145/3290605.3300480Google ScholarDigital Library
- Andrea Behrends, Sybille Müller, and Isabel Dziobek. 2012. Moving in and out of synchrony: A concept for a new intervention fostering empathy through interactional movement and dance. The Arts in Psychotherapy 39, 2 (2012), 107–116.Google ScholarCross Ref
- Margaret M. Bradley and Peter J. Lang. 1994. Measuring emotion: the self-assessment manikin and the semantic differential. Journal of Behavior Therapy and Experimental Psychiatry 25, 1(1994), 49–59. https://doi.org/10.1016/0005-7916(94)90063-9Google ScholarCross Ref
- Cynthia Breazeal. 2001. Affective Interaction between Humans and Robots. In Proceedings of the 6th European Conference on Advances in Artificial Life (Prague, Czech Republic) (ECAL ’01). Springer-Verlag, Berlin, Heidelberg, 582–591.Google ScholarCross Ref
- Cynthia Breazeal. 2003. Emotion and Sociable Humanoid Robots. International Journal of Human-Computer Studies 59, 1–2 (July 2003), 119–155. https://doi.org/10.1016/S1071-5819(03)00018-1Google ScholarDigital Library
- Cynthia Breazeal. 2003. Toward sociable robots. Robotics and Autonomous Systems 42, 3-4 (2003), 167–175. https://doi.org/10.1016/S0921-8890(02)00373-1Google ScholarCross Ref
- Elizabeth Broadbent, Vinayak Kumar, Xingyan Li, John Sollers 3rd, Rebecca Q. Stafford, Bruce A. MacDonald, and Daniel M. Wegner. 2013. Robots with display screens: a robot with a more humanlike face display is perceived to have more mind and a better personality. PloS one 8, 8 (2013), e72589. https://doi.org/10.1371/journal.pone.0072589Google ScholarCross Ref
- Anke M. Brock, Julia Chatain, Michelle Park, Tommy Fang, Martin Hachet, James A. Landay, and Jessica R. Cauchard. 2018. FlyMap: Interacting with Maps Projected from a Drone. In Proceedings of the 7th ACM International Symposium on Pervasive Displays (Munich, Germany) (PerDis ’18). Association for Computing Machinery, New York, NY, USA, Article 13, 9 pages. https://doi.org/10.1145/3205873.3205877Google ScholarDigital Library
- A. Bruce, I. Nourbakhsh, and R. Simmons. 2002. The role of expressiveness and attention in human-robot interaction. In Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292), Vol. 4. IEEE, 4138–4142. https://doi.org/10.1109/ROBOT.2002.1014396Google ScholarCross Ref
- Andrew J. Calder, Andrew W. Young, Jill Keane, and Michael Dean. 2000. Configural information in facial expression perception.Journal of Experimental Psychology: Human Perception and Performance 26, 2(2000), 527–551. https://doi.org/10.1037//0096-1523.26.2.527Google ScholarCross Ref
- Lola Cañamero and Jakob Fredslund. 2001. I show you how I like you - can you read it in my face? [robotics]. IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans 31, 5 (2001), 454–459. https://doi.org/10.1109/3468.952719Google ScholarDigital Library
- Jessica R. Cauchard, Jane L. E, Kevin Y. Zhai, and James A. Landay. 2015. Drone & me: An Exploration into Natural Human-Drone Interaction. In Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing (Osaka, Japan) (UbiComp ’15). Association for Computing Machinery, New York, NY, USA, 361–365. https://doi.org/10.1145/2750858.2805823Google ScholarDigital Library
- Jessica R. Cauchard, Kevin Y. Zhai, Marco Spadafora, and James A. Landay. 2016. Emotion Encoding in Human-Drone Interaction. In The Eleventh ACM/IEEE International Conference on Human Robot Interaction (Christchurch, New Zealand) (HRI ’16). IEEE, 263–270.Google Scholar
- Ashley Colley, Lasse Virtanen, Pascal Knierim, and Jonna Häkkilä. 2017. Investigating Drone Motion as Pedestrian Guidance. In Proceedings of the 16th International Conference on Mobile and Ubiquitous Multimedia (Stuttgart, Germany) (MUM ’17). Association for Computing Machinery, New York, NY, USA, 143–150. https://doi.org/10.1145/3152832.3152837Google ScholarDigital Library
- Juliet M. Corbin and Anselm Strauss. 1990. Grounded theory research: Procedures, canons, and evaluative criteria. Qualitative Sociology 13, 1 (1990), 3–21. https://doi.org/10.1007/BF00988593Google ScholarCross Ref
- Frédéric Dehais, Emrah Akin Sisbot, Rachid Alami, and Mickaël Causse. 2011. Physiological and subjective evaluation of a human–robot object hand-over task. Applied Ergonomics 42, 6 (2011), 785–791. https://doi.org/10.1016/j.apergo.2010.12.005Google ScholarCross Ref
- Brian R. Duffy. 2003. Anthropomorphism and the social robot. Robotics and Autonomous Systems 42, 3-4 (2003), 177–190. https://doi.org/10.1016/s0921-8890(02)00374-3Google ScholarCross Ref
- Jane L. E, Ilene L. E, James A. Landay, and Jessica R. Cauchard. 2017. Drone & Wo: Cultural Influences on Human-Drone Interaction Techniques. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery, New York, NY, USA, 6794–6799. https://doi.org/10.1145/3025453.3025755Google ScholarDigital Library
- Paul Ekman and Wallace V. Friesen. 1971. Constants across cultures in the face and emotion. Journal of Personality and Social Psychology 17, 2(1971), 124–129. https://doi.org/10.1037/h0030377Google ScholarCross Ref
- Paul Ekman, Wallace V. Friesen, and Joseph C. Hager. 2002. Facial Action Coding System: The Manual on CD ROM. Salt Lake City, UT, USA.Google Scholar
- Hillary Anger Elfenbein and Nalini Ambady. 2003. When familiarity breeds accuracy: Cultural exposure and facial emotion recognition. Journal of Personality and Social Psychology 85, 2(2003), 276–290. https://doi.org/10.1037/0022-3514.85.2.276Google ScholarCross Ref
- Sara Eriksson, Åsa Unander-Scharin, Vincent Trichon, Carl Unander-Scharin, Hedvig Kjellström, and Kristina Höök. 2019. Dancing With Drones: Crafting Novel Artistic Expressions Through Intercorporeality. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (Glasgow, Scotland Uk) (CHI ’19). Association for Computing Machinery, New York, NY, USA, 1–12. https://doi.org/10.1145/3290605.3300847Google ScholarDigital Library
- Friederike Eyssel, Frank Hegel, Gernot Horstmann, and Claudia Wagner. 2010. Anthropomorphic inferences from emotional nonverbal cues: A case study. In 19th International Symposium in Robot and Human Interactive Communication. IEEE, 646–651. https://doi.org/10.1109/ROMAN.2010.5598687Google ScholarCross Ref
- Julia Fink. 2012. Anthropomorphism and Human Likeness in the Design of Robots and Human-Robot Interaction. In International Conference on Social Robotics. Springer, 199–208. https://doi.org/10.1007/978-3-642-34103-8_20Google ScholarDigital Library
- Kerstin Fischer, Malte Jung, Lars Christian Jensen, and Maria Vanessa aus der Wieschen. 2019. Emotion Expression in HRI – When and Why. In 2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI). IEEE, 29–38. https://doi.org/10.1109/HRI.2019.8673078Google ScholarCross Ref
- Terrence Fong, Illah Nourbakhsh, and Kerstin Dautenhahn. 2003. A survey of socially interactive robots. Robotics and Autonomous Systems 42, 3-4 (2003), 143–166. https://doi.org/10.1016/S0921-8890(02)00372-XGoogle ScholarCross Ref
- Alan J. Fridlund. 1991. Evolution and facial action in reflex, social motive, and paralanguage. Biological Psychology 32, 1 (1991), 3–100. https://doi.org/10.1016/0301-0511(91)90003-yGoogle ScholarCross Ref
- Nico H. Frijda and Batja Mesquita. 1994. The social roles and functions of emotions. In Emotion and Culture: Empirical Studies of Mutual Influence. American Psychological Association, Washington, DC, US, 51–87. https://doi.org/10.1037/10152-002Google ScholarCross Ref
- Chris D. Frith and Uta Frith. 2006. How we predict what other people are going to do. Brain Research 1079, 1 (2006), 36–46. https://doi.org/10.1016/j.brainres.2005.12.126Google ScholarCross Ref
- Shlomo Hareli and Anat Rafaeli. 2008. Emotion cycles: On the social influence of emotion in organizations. Research in Organizational Behavior 28 (2008), 35–59. https://doi.org/10.1016/j.riob.2008.04.007Google ScholarCross Ref
- Markus Häring, Nikolaus Bee, and Elisabeth André. 2011. Creation and Evaluation of emotion expression with body movement, sound and eye color for humanoid robots. In 2011 RO-MAN. IEEE, 204–209. https://doi.org/10.1109/ROMAN.2011.6005263Google ScholarCross Ref
- Guy Hoffman and Wendy Ju. 2014. Designing Robots with Movement in Mind. Journal of Human-Robot Interaction 3, 1 (Feb. 2014), 91–122. https://doi.org/10.5898/JHRI.3.1.HoffmanGoogle ScholarDigital Library
- Jihong Hwang, Taezoon Park, and Wonil Hwang. 2013. The effects of overall robot shape on the emotions invoked in users and the perceived personalities of robot. Applied Ergonomics 44, 3 (2013), 459–471. https://doi.org/10.1016/j.apergo.2012.10.010Google ScholarCross Ref
- Alisa Kalegina, Grace Schroeder, Aidan Allchin, Keara Berlin, and Maya Cakmak. 2018. Characterizing the Design Space of Rendered Robot Faces. In Proceedings of the 2018 ACM/IEEE International Conference on Human-Robot Interaction (Chicago, IL, USA) (HRI ’18). Association for Computing Machinery, New York, NY, USA, 96–104. https://doi.org/10.1145/3171221.3171286Google ScholarDigital Library
- Kari Daniel Karjalainen, Anna Elisabeth Sofia Romell, Photchara Ratsamee, Asim Evren Yantac, Morten Fjeld, and Mohammad Obaid. 2017. Social Drone Companion for the Home Environment: A User-Centric Exploration. In Proceedings of the 5th International Conference on Human Agent Interaction (Bielefeld, Germany) (HAI ’17). Association for Computing Machinery, New York, NY, USA, 89–96. https://doi.org/10.1145/3125739.3125774Google ScholarDigital Library
- L.N. Kendall, Quentin Raffaelli, Alan Kingstone, and Rebecca M. Todd. 2016. Iconic faces are not real faces: enhanced emotion detection and altered neural processing as faces become more iconic. Cognitive Research: Principles and Implications 1, 1, Article 19 (2016), 14 pages. https://doi.org/10.1186/s41235-016-0021-8Google ScholarCross Ref
- Bomyeong Kim, Hyun Young Kim, and Jinwoo Kim. 2016. Getting Home Safely with Drone. In Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct (Heidelberg, Germany) (UbiComp ’16). Association for Computing Machinery, New York, NY, USA, 117–120. https://doi.org/10.1145/2968219.2971426Google ScholarDigital Library
- Eun Ho Kim, Sonya S. Kwak, and Yoon Keun Kwak. 2009. Can robotic emotional expressions induce a human to empathize with a robot?. In RO-MAN 2009 - The 18th IEEE International Symposium on Robot and Human Interactive Communication. IEEE, 358–362. https://doi.org/10.1109/ROMAN.2009.5326282Google ScholarCross Ref
- Hyun Young Kim, Bomyeong Kim, and Jinwoo Kim. 2016. The Naughty Drone: A Qualitative Research on Drone as Companion Device. In Proceedings of the 10th International Conference on Ubiquitous Information Management and Communication (Danang, Viet Nam) (IMCOM ’16). Association for Computing Machinery, New York, NY, USA, Article 91, 6 pages. https://doi.org/10.1145/2857546.2857639Google ScholarDigital Library
- Elly A. Konijn and Henriette C. Van Vugt. 2008. Emotions in Mediated Interpersonal Communication: Toward modeling emotion in virtual humans. In Mediated Interpersonal Communication. Routledge, 114–144.Google Scholar
- Dana Kulic and Elizabeth A. Croft. 2007. Affective State Estimation for Human–Robot Interaction. IEEE Transactions on Robotics 23, 5 (2007), 991–1000. https://doi.org/10.1109/TRO.2007.904899Google ScholarDigital Library
- Aleksandra Kupferberg, Stefan Glasauer, Markus Huber, Markus Rickert, Alois Knoll, and Thomas Brandt. 2011. Biological movement increases acceptance of humanoid robots as human partners in motor interaction. AI & Society 26, 4 (2011), 339–345. https://doi.org/10.1007/s00146-010-0314-2Google ScholarDigital Library
- Joseph La Delfa, Mehmet Aydin Baytas, Rakesh Patibanda, Hazel Ngari, Rohit Ashok Khot, and Florian ’Floyd’ Mueller. 2020. Drone Chi: Somaesthetic Human-Drone Interaction. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (Honolulu, HI, USA) (CHI ’20). Association for Computing Machinery, New York, NY, USA, 1–13. https://doi.org/10.1145/3313831.3376786Google ScholarDigital Library
- Iolanda Leite, André Pereira, Carlos Martinho, and Ana Paiva. 2008. Are emotional robots more fun to play with?. In RO-MAN 2008 - The 17th IEEE International Symposium on Robot and Human Interactive Communication. IEEE, 77–82. https://doi.org/10.1109/ROMAN.2008.4600646Google ScholarCross Ref
- Jukka M. Leppänen and Jari K. Hietanen. 2004. Positive facial expressions are recognized faster than negative facial expressions, but why?Psychological Research 69, 1-2 (2004), 22–29. https://doi.org/10.1007/s00426-003-0157-2Google ScholarCross Ref
- Diana Löffler, Nina Schmidt, and Robert Tscharn. 2018. Multimodal Expression of Artificial Emotion in Social Robots Using Color, Motion and Sound. In Proceedings of the 2018 ACM/IEEE International Conference on Human-Robot Interaction (Chicago, IL, USA) (HRI ’18). Association for Computing Machinery, New York, NY, USA, 334–343. https://doi.org/10.1145/3171221.3171261Google ScholarDigital Library
- Maya B Mathur and David B Reichling. 2016. Navigating a social world with robot partners: A quantitative cartography of the Uncanny Valley. Cognition 146(2016), 22–32. https://doi.org/10.1016/j.cognition.2015.09.008Google ScholarCross Ref
- Maya B. Mathur, David B. Reichling, Francesca Lunardini, Alice Geminiani, Alberto Antonietti, Peter A. M. Ruijten, Carmel Levitan, Gideon Nave, Dylan Manfredi, Brandy Bessette-Symons, Attila Szuts, and Balazs Aczel. 2020. Uncanny but not confusing: Multisite study of perceptual category confusion in the Uncanny Valley. Computers in Human Behavior 103 (2020), 21–30. https://doi.org/10.1016/j.chb.2019.08.029Google ScholarDigital Library
- John J. McArdle. 2009. Latent Variable Modeling of Differences and Changes with Longitudinal Data. Annual Review of Psychology 60 (2009), 577–605. https://doi.org/10.1146/annurev.psych.60.110707.163612Google ScholarCross Ref
- Masahiro Mori, Karl F. MacDorman, and Norri Kageki. 2012. The Uncanny Valley [From the Field]. IEEE Robotics Automation Magazine 19, 2 (2012), 98–100. https://doi.org/10.1109/MRA.2012.2192811Google ScholarCross Ref
- Florian Mueller and Matthew Muirhead. 2014. Understanding the Design of a Flying Jogging Companion. In Proceedings of the Adjunct Publication of the 27th Annual ACM Symposium on User Interface Software and Technology (Honolulu, Hawaii, USA) (UIST’14 Adjunct). Association for Computing Machinery, New York, NY, USA, 81–82. https://doi.org/10.1145/2658779.2658786Google ScholarDigital Library
- Florian Mueller and Matthew Muirhead. 2014. Understanding the Design of a Flying Jogging Companion. In Proceedings of the Adjunct Publication of the 27th Annual ACM Symposium on User Interface Software and Technology (Honolulu, Hawaii, USA) (UIST’14 Adjunct). Association for Computing Machinery, New York, NY, USA, 81–82. https://doi.org/10.1145/2658779.2658786Google ScholarDigital Library
- Bilge Mutlu, Fumitaka Yamaoka, Takayuki Kanda, Hiroshi Ishiguro, and Norihiro Hagita. 2009. Nonverbal Leakage in Robots: Communication of Intentions through Seemingly Unintentional Behavior. In Proceedings of the 4th ACM/IEEE International Conference on Human Robot Interaction (La Jolla, California, USA) (HRI ’09). Association for Computing Machinery, New York, NY, USA, 69–76. https://doi.org/10.1145/1514095.1514110Google ScholarDigital Library
- Jean Newlove and John Dalby. 2004. Laban for all. Taylor & Francis US.Google Scholar
- Nikolaas N. Oosterhof and Alexander Todorov. 2008. The functional basis of face evaluation. Proceedings of the National Academy of Sciences 105, 32(2008), 11087–11092. https://doi.org/10.1073/pnas.0805664105Google ScholarCross Ref
- Nikolaas N. Oosterhof and Alexander Todorov. 2009. Shared perceptual basis of emotional expressions and trustworthiness impressions from faces. Emotion 9, 1 (2009), 128–133. https://doi.org/10.1037/a0014520Google ScholarCross Ref
- Hannah R. M. Pelikan, Mathias Broth, and Leelo Keevallik. 2020. ”Are You Sad, Cozmo?”: How Humans Make Sense of a Home Robot’s Emotion Displays. In Proceedings of the 2020 ACM/IEEE International Conference on Human-Robot Interaction(Cambridge, United Kingdom) (HRI ’20). Association for Computing Machinery, New York, NY, USA, 461–470. https://doi.org/10.1145/3319502.3374814Google ScholarDigital Library
- Anssi Peräkylä and Johanna Elisabeth Ruusuvuori. 2012. Facial Expression and Interactional Regulation of Emotion. In Emotion in Interaction. Oxford University Press, Chapter 4, 64–91. https://doi.org/10.1093/acprof:oso/9780199730735.003.0004Google ScholarCross Ref
- Robert Plutchik. 1980. A general psychoevolutionary theory of emotion. In Theories of Emotion. Elsevier, 3–33. https://doi.org/10.1016/B978-0-12-558701-3.50007-7Google ScholarCross Ref
- Mauricio E. Reyes, Ivan V. Meza, and Luis A. Pineda. 2019. Robotics facial expression of anger in collaborative human–robot interaction. International Journal of Advanced Robotic Systems 16, 1 (2019), 13. https://doi.org/10.1177/1729881418817972Google ScholarCross Ref
- Tiago Ribeiro and Ana Paiva. 2012. The Illusion of Robotic Life: Principles and Practices of Animation for Robots. In Proceedings of the Seventh Annual ACM/IEEE International Conference on Human-Robot Interaction (Boston, Massachusetts, USA) (HRI ’12). Association for Computing Machinery, New York, NY, USA, 383–390. https://doi.org/10.1145/2157689.2157814Google ScholarDigital Library
- Laurel D. Riek, Tal-Chen Rabinowitch, Bhismadev Chakrabarti, and Peter Robinson. 2009. How Anthropomorphism Affects Empathy toward Robots. In Proceedings of the 4th ACM/IEEE International Conference on Human Robot Interaction (La Jolla, California, USA) (HRI ’09). Association for Computing Machinery, New York, NY, USA, 245–246. https://doi.org/10.1145/1514095.1514158Google ScholarDigital Library
- Annie Roy-Charland, Melanie Perron, Olivia Beaudry, and Kaylee Eady. 2014. Confusion of fear and surprise: A test of the perceptual-attentional limitation hypothesis with eye movement monitoring. Cognition and Emotion 28, 7 (2014), 1214–1222. https://doi.org/10.1080/02699931.2013.878687Google ScholarCross Ref
- Peter A. M. Ruijten and Raymond H. Cuijpers. 2018. If Drones Could See: Investigating Evaluations of a Drone with Eyes. In International Conference on Social Robotics. Springer, 65–74. https://doi.org/10.1007/978-3-030-05204-1_7Google ScholarCross Ref
- James A. Russell and Merry Bullock. 1985. Multidimensional scaling of emotional facial expressions: Similarity from preschoolers to adults. Journal of Personality and Social Psychology 48, 5(1985), 1290–1298. https://doi.org/10.1037/0022-3514.48.5.1290Google ScholarCross Ref
- Eleanor Sandry. 2015. Re-evaluating the form and communication of social robots. International Journal of Social Robotics 7, 3 (2015), 335–346. https://doi.org/10.1007/s12369-014-0278-3Google ScholarCross Ref
- Margret Selting. 2010. Affectivity in conversational storytelling: An analysis of displays of anger or indignation in complaint stories. Pragmatics 20, 2 (2010), 229–277. https://doi.org/10.1075/prag.20.2.06selGoogle ScholarCross Ref
- Megha Sharma, Dale Hildebrandt, Gem Newman, James E. Young, and Rasit Eskicioglu. 2013. Communicating Affect via Flight Path: Exploring Use of the Laban Effort System for Designing Affective Locomotion Paths. In Proceedings of the 8th ACM/IEEE International Conference on Human-Robot Interaction (Tokyo, Japan) (HRI ’13). IEEE, 293–300. https://doi.org/10.1109/HRI.2013.6483602Google ScholarCross Ref
- Takanori Shibata, Kazuyoshi Wada, Tomoko Saito, and Kazuo Tanie. 2005. Human interactive robot for psychological enrichment and therapy. In Proceedings of the AISB ’05 Symposium on Robot Companions: Hard Problems and Open Challenges in Robot-Human Interaction (University of Hertfordshire, Hatfield, UK), Vol. 5. The Society for the Study of Artificial Intelligence and the Simulation of Behaviour (AISB), 98–109.Google Scholar
- Stefan Sosnowski, Ansgar Bittermann, Kolja Kuhnlenz, and Martin Buss. 2006. Design and Evaluation of Emotion-Display EDDIE. In 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems (Beijing, China). IEEE, 3113–3118. https://doi.org/10.1109/IROS.2006.282330Google ScholarCross Ref
- Lorna H. Stewart, Sara Ajina, Spas Getov, Bahador Bahrami, Alexander Todorov, and Geraint Rees. 2012. Unconscious evaluation of faces on social dimensions. Journal of Experimental Psychology: General 141, 4 (2012), 715–727. https://doi.org/10.1037/a0027950Google ScholarCross Ref
- Dante Tezza and Marvin Andujar. 2019. The State-of-the-Art of Human–Drone Interaction: A Survey. IEEE Access 7(2019), 167438–167454. https://doi.org/10.1109/ACCESS.2019.2953900Google ScholarCross Ref
- Tim Treurniet, Lang Bai, Simon à Campo, Xintong Wang, Jun Hu, and Emilia Barakova. 2019. Drones with eyes: expressive Human-Drone Interaction. In 1st International Workshop on Human-Drone Interaction. Glasgow, United Kingdom, 7. https://hal.archives-ouvertes.fr/hal-02128380Google Scholar
- Eva Wiese, Giorgio Metta, and Agnieszka Wykowska. 2017. Robots As Intentional Agents: Using Neuroscientific Methods to Make Robots Appear More Social. Frontiers in Psychology 8, Article 1663(2017), 19 pages. https://doi.org/10.3389/fpsyg.2017.01663Google ScholarCross Ref
- Anna Wojciechowska, Jeremy Frey, Esther Mandelblum, Yair Amichai-Hamburger, and Jessica R. Cauchard. 2019. Designing Drones: Factors and Characteristics Influencing the Perception of Flying Robots. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 3, 3, Article 111 (Sept. 2019), 19 pages. https://doi.org/10.1145/3351269Google ScholarDigital Library
- Anna Wojciechowska, Jeremy Frey, Sarit Sass, Roy Shafir, and Jessica R. Cauchard. 2019. Collocated Human-Drone Interaction: Methodology and Approach Strategy. In 2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI). IEEE, 172–181. https://doi.org/10.1109/HRI.2019.8673127Google ScholarCross Ref
- Anna Wojciechowska, Foad Hamidi, Andrés Lucero, and Jessica R. Cauchard. 2020. Chasing Lions: Co-Designing Human-Drone Interaction in Sub-Saharan Africa. In Proceedings of the 2020 ACM Designing Interactive Systems Conference (Eindhoven, Netherlands) (DIS ’20). Association for Computing Machinery, New York, NY, USA, 141–152. https://doi.org/10.1145/3357236.3395481Google ScholarDigital Library
- Alexander Yeh, Photchara Ratsamee, Kiyoshi Kiyokawa, Yuki Uranishi, Tomohiro Mashita, Haruo Takemura, Morten Fjeld, and Mohammad Obaid. 2017. Exploring Proxemics for Human-Drone Interaction. In Proceedings of the 5th International Conference on Human Agent Interaction (Bielefeld, Germany) (HAI ’17). Association for Computing Machinery, New York, NY, USA, 81–88. https://doi.org/10.1145/3125739.3125773Google ScholarDigital Library
- Shen Zhang, Zhiyong Wu, Helen M. Meng, and Lianhong Cai. 2007. Facial Expression Synthesis Using PAD Emotional Parameters for a Chinese Expressive Avatar. In Proceedings of the 2nd International Conference on Affective Computing and Intelligent Interaction (Lisbon, Portugal) (ACII ’07). Springer-Verlag, Berlin, Heidelberg, 24–35. https://doi.org/10.1007/978-3-540-74889-2_3Google ScholarDigital Library
- Jiayin Zhao, Qi Meng, Licong An, and Yifang Wang. 2019. An event-related potential comparison of facial expression processing between cartoon and real faces. PLoS ONE 14, 1, Article e0198868(2019), 13 pages. https://doi.org/10.1371/journal.pone.0198868Google ScholarCross Ref
Index Terms
- Drone in Love: Emotional Perception of Facial Expressions on Flying Robots
Recommendations
Person-independent estimation of emotional experiences from facial expressions
IUI '05: Proceedings of the 10th international conference on Intelligent user interfacesThe aim of this research was to develop methods for the automatic person-independent estimation of experienced emotions from facial expressions. Ten subjects watched series of emotionally arousing pictures and videos, while the electromyographic (EMG) ...
Psychological responses to simulated displays of mismatched emotional expressions
Embodied agents are often designed with the ability to simulate human emotion. This paper investigates the psychological impact of simulated emotional expressions on computer users with a particular emphasis on how mismatched facial and audio ...
A Customer Emotion Recognition through Facial Expression using Kinect Sensors v1 and v2: A Comparative Analysis
IMCOM '16: Proceedings of the 10th International Conference on Ubiquitous Information Management and CommunicationProducts evoke positive or negative emotions to customers. Those with negative emotion toward the product are likely to reject it, while those with positive emotion toward the product are enticed to buy it. There were already some studies on customer ...
Comments