Alexandre Coninx
Paul Baxter
Mark Neerincx
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Abstract
Social robots have the potential to provide support in a number of practical domains, such as learning and behaviour change. This potential is particularly relevant for children, who have proven receptive to interactions with social robots. To reach learning and therapeutic goals, a number of issues need to be investigated, notably the design of an effective child-robot interaction (cHRI) to ensure the child remains engaged in the relationship and that educational goals are met. Typically, current cHRI research experiments focus on a single type of interaction activity (e.g. a game). However, these can suffer from a lack of adaptation to the child, or from an increasingly repetitive nature of the activity and interaction. In this paper, we motivate and propose a practicable solution to this issue: an adaptive robot able to switch between multiple activities within single interactions. We describe a system that embodies this idea, and present a case study in which diabetic children collaboratively learn with the robot about various aspects of managing their condition. We demonstrate the ability of our system to induce a varied interaction and show the potential of this approach both as an educational tool and as a research method for long-term cHRI.
- Ames, C. (1992). Classrooms: Goals, structures, and student motivation. Journal of Educational Psychology, 84(3), 261--271.Google Scholar
Cross Ref
- Baillie, J.-C. (2005). URBI: Towards a universal robotic low-level programming language. In Proceedings of the 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2005) (p. 820--825).Google ScholarCross Ref
- Baillie, J.-C., Demaille, A., Hocquet, Q., Nottale, M., & Tardieu, S. (2008). The Urbi universal platform for robotics. In Proceedings of the First International Workshop on Standards and Common Platform for Robotics (SIMPAR 2008) (pp. 580--591). Venice, Italy.Google Scholar
- Baroni, I., Nalin, M., Baxter, P., Pozzi, C., Oleari, E., Sanna, A., & Belpaeme, T. (2014). What a robotic companion could do for a diabetic child. In Proceedings the 23rd IEEE International Symposium on Robot and Human Interactive Communication (RoMan '14) (pp. 936--941). Edinburgh, U.K.: IEEE Press.Google ScholarCross Ref
- Bartneck, C. (2003). Interacting with an embodied emotional character. In Proceedings of the 2003 International Conference on Designing Pleasurable Products and Interfaces (DPPI '03) (pp. 55--60). Pittsburgh, USA: ACM Press. Google ScholarDigital Library
- Baxter, P., Baroni, I., Nalin, M., Sanna, A., & Belpaeme, T. (2013). Touchscreens as mediators for social human--robot interactions: A focus group evaluation involving diabetic children. In Proceedings of the CmIS workshop at ITS '13. St Andrews, U.K.Google Scholar
- Baxter, P., deGreeff, J., & Belpaeme, T. (2013). Cognitive architecture for human--robot interaction: Towards behavioural alignment. Biologically Inspired Cognitive Architectures, 6, 30--39.Google ScholarCross Ref
- Baxter, P., Kennedy, J., Vollmer, A.-L., de Greeff, J., & Belpaeme, T. (2014). Tracking gaze over time in hri as a proxy for engagement and attribution of social agency. In Proceedings of the 2014 ACM/IEEE International Conference on Human-Robot Interaction (HRI'14) (pp. 126--127). Bielefeld, Germany: ACM Press. Google ScholarDigital Library
- Baxter, P., Wood, R., & Belpaeme, T. (2012). A touchscreen-based "sandtray" to facilitate, mediate and contextualise human-robot social interaction. In Proceedings of the 7th ACM/IEEE International Conference on Human-Robot interaction (HRI) (pp. 105--106). Boston, MA, U.S.A.: ACM/IEEE Press. Google ScholarDigital Library
- Beck, A., Canamero, L., & Bard, K. (2010). Towards an affect space for robots to display emotional body language. In Proceedings of the 19th IEEE International Symposium in Robot and Human Interactive Communication (RoMan 2010).Google ScholarCross Ref
- Beck, A., Hiolle, A., & Canamero, L. (2013). Using Perlin noise to generate emotional expressions in a robot. In Proceedings of the 35th Annual Meeting of the Cognitive Science Society (CogSci 2013) (pp. 1845--1850). Berlin, Germany.Google Scholar
- Belpaeme, T., Baxter, P., Greeff, J. D., Kennedy, J., Looije, R., Neerincx, M., ... Coti, M. (2013). Child-robot interaction: Perspectives and challenges. In Proceedings of the 5th International Conference on Social Robotics (ICSR 2013) (pp. 452--459). Bristol, U.K.: Springer. Google ScholarDigital Library
- Belpaeme, T., Baxter, P., Read, R., Wood, R., Cuay, H., Kiefer, B., ... Humbert, R. (2012). Multimodal child-robot interaction: Building social bonds. Journal of Human-Robot Interaction, 1(2), 33--53. Google ScholarDigital Library
- Beran, T. N., Ramirez-Serrano, A., Kuzyk, R., Fior, M., & Nugent, S. (2011). Understanding how children understand robots : Perceived animism in child robot interaction. Journal of Human Computer Studies, 69(7-8), 539--550. Google ScholarDigital Library
- Billard, A. (2002). Play, dreams and imitation in robota. In K. Dautenhahn, A. Bond, L. Caamero, & B. Edmonds (Eds.), Socially intelligent agents (Vol. 3, pp. 165--172). Springer.Google Scholar
- Blanson Henkemans, O. A., Bierman, B. P. B., Janssen, J., Neerincx, M. A., Looije, R., van der Bosch, H., & van der Giessen, J. A. M. (2013). Using a robot to personalise health education for children with diabetes type 1: A pilot study. Patient education and counseling, 92(2), 174--81.Google Scholar
- Blanson-Henkemans, O., Hoondert, V., Schrama-Groot, F., Looije, R., Alpay, L., & Neerincx, M. (2012). "I just have diabetes": Children's need for diabetes self-management support and how a social robot can accommodate their needs. Patient Intelligence, 4, 51--61.Google ScholarCross Ref
- Christophel, D. M. (1990). The relationships among teacher immediacy behaviors, student motivation, and learning. Communication Education, 39(4), 323--340.Google ScholarCross Ref
- Cosi, P., Paci, G., Sommavilla, G., Tesser, F., Nalin, M., & Baroni, I. (2012). An Italian event-based ASR-TTS system for the Nao robot. In Proceedings of the 7th Conference of the Italian Association of Speech Sciences (pp. 177--198). Rome, Italy.Google Scholar
- Csala, E., Németh, G., & Zainkó, C. (2012). Application of the NAO humanoid robot in the treatment of marrow-transplanted children. In Proceedings of the 3rd IEEE International Conference on Cognitive Infocommunications (pp. 655--659). Kosice, Slovakia.Google ScholarCross Ref
- Dautenhahn, K. (2004). Robots we like to live with?! A developmental perspective on a personalized, life-long robot companion. In Proceedings the 13th IEEE International Symposium on Robot and Human Interactive Communication (RoMan'14) (pp. 17--22). Kurashiki, Japan: IEEE Press.Google ScholarCross Ref
- Dautenhahn, K. (2007). Socially intelligent robots: Dimensions of human-robot interaction. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 362, 679--704.Google ScholarCross Ref
- Draper, T. W., & Clayton, W. W. (1992). Using a personal robot to teach young children. The Journal of Genetic Psychology, 153(3), 269--273.Google ScholarCross Ref
- Dweck, C. S. (1986). Motivational processes affecting learning. American Psychologist, 41(10), 1040--1048.Google ScholarCross Ref
- European Food Information Council. (2009, October). Food-based dietary guidelines in Europe. Website. Retrieved from http://www.eufic.org/article/en/expid/food-based-dietary-guidelines-in-europeGoogle Scholar
- Fine, A. (2010). Handbook on animal-assisted therapy (3rd ed.). San Diego, CA, USA: Academic Press.Google Scholar
- Gough, H. G., & Heilbrun, A. B. (1980). The adjective check list manual: ACL. Palo Alto, CA, USA: Consulting Psychologists Press, Inc.Google Scholar
- Hiolle, A., Lewis, M., & Cañamero, L. (2014). Arousal regulation and affective adaptation to human responsiveness by a robot that explores and learns a novel environment. Frontiers in Neurorobotics, 8, 17.Google ScholarCross Ref
- Hyun, E., & Son, S. (2010). Relationships between user experiences and children's perceptions of the education robot. In Proceedings of 5th ACM/IEEE International Conference on Human-Robot Interaction - HRI'10 (pp. 199--200). Osaka, Japan: ACM/IEEE Press. Google ScholarDigital Library
- Janssen, J. B., van der Wal, C. C., Neerincx, M. A., & Looije, R. (2011). Motivating children to learn arithmetic with an adaptive robot game. In Proceedings of the 3rd International Conference on Social Robotics (pp. 153--162). Berlin, Heidelberg: Springer-Verlag. Google ScholarDigital Library
- Kanda, T., Hirano, T., & Eaton, D. (2004). Interactive robots as social partners and peer tutors for children: A field trial. Human-Computer Interaction, 19, 61--84. Google ScholarDigital Library
- Kanda, T., Sato, R., Saiwaki, N., & Ishiguro, H. (2007). A two-month field trial in an elementary school for long-term human-robot interaction. IEEE Transactions on Robotics, 23(5), 962--971. Google ScholarDigital Library
- Keller, J. (1987). Strategies for stimulating the motivation to learn. Performance and Instruction, 1--7.Google Scholar
- Kelley, J. F. (1984). An iterative design methodology for user-friendly natural language office information applications. ACM Transactions on Information Systems, 2(1), 26--41. Google ScholarDigital Library
- Kennedy, J., Baxter, P., & Belpaeme, T. (2013). Constraining content in mediated unstructured social interactions: Studies in the wild. In Proceedings of the 5th International Workshop on Affective Interaction in Natural Environments at ACII 2013. IEEE Press. Google ScholarDigital Library
- Kennedy, J., Baxter, P., & Belpaeme, T. (2014). Children comply with a robot's indirect requests. In Proceedings of the 2014 ACM/IEEE International Conference on Human-Robot Interaction - HRI'14 (pp. 198--199). Bielefeld, Germany: ACM Press. Google ScholarDigital Library
- Kennedy, J., Baxter, P., & Belpaeme, T. (2015). Comparing robot embodiments in a guided discovery learning interaction with children. International Journal of Social Robotics, 7(2), 293--308.Google ScholarCross Ref
- Kidd, C. D., & Breazeal, C. (2008). Robots at home: Understanding long-term human-robot interaction. In Proceedings of the 21st IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2008) (pp. 22--26). Nice, France: IEEE Press.Google ScholarCross Ref
- Komatsu, T., & Abe, Y. (2008). Comparing an on-screen agent with a robotic agent in non-face-to-face interactions. In H. Prendinger, J. Lester, & M. Ishizuka (Eds.), Intelligent virtual agents (lecture notes in computer science 5208) (Vol. 5208, pp. 498--504). Berlin, Heidelberg: Springer Berlin Heidelberg. Google ScholarDigital Library
- Kose-Bagci, H., Ferrari, E., Dautenhahn, K., Syrdal, D. S., & Nehaniv, C. L. (2009). Effects of embodiment and gestures on social interaction in drumming games with a humanoid robot. Advanced Robotics, 23(14), 1951--1996.Google ScholarCross Ref
- Kozima, H., & Nakagawa, C. (2006). Social robots for children: Practice in communication-care. In Proceedings of the 9th IEEE International Workshop on Advanced Motion Control (pp. 768--773). Istanbul, Turkey: IEEE Press.Google ScholarCross Ref
- Kruijff-Korbayova, I., Cuayahuitl, H., Kiefer, B., Schroder, M., Cosi, P., Paci, G., ... Verhelst, W. (2012). Spoken language processing in a conversational system for child-robot interaction. In Proceedings of the Workshop on Child-Computer Interaction (WOCCI). Portland, USA.Google Scholar
- Kruijff-Korbayova, I., Kiefer, B., Baroni, I., & Zelati, M. C. (2013, December). Making human-robot quiz dialogue more conversational by adding non-quiz talk. In The 17th Workshop on the Semantics and Pragmatics of Dialogue (DialDam) (p. Poster). Amsterdam, The Netherlands.Google Scholar
- Kruijff-Korbayova, I., Oleari, E., Baroni, I., Kiefer, B., Zelati, M. C., Pozzi, C., & Sanna, A. (2014, August). Effects of off-activity talk in human-robot interaction with diabetic children. In Proceedings of the 23rd IEEE International Symposium on Robot and Human Interactive Communication (RoMan 2014) (pp. 649--654). IEEE Press.Google Scholar
- Lee, K. M., Jung, Y., Kim, J., & Kim, S. R. (2006). Are physically embodied social agents better than disembodied social agents? The effects of physical embodiment, tactile interaction, and people's loneliness in humanrobot interaction. International Journal of Human-Computer Studies, 64(10), 962--973. Google ScholarDigital Library
- Leite, I., Castellano, G., Pereira, A., Martinho, C., & Paiva, A. (2012). Modelling empathic behaviour in a robotic game companion for children: An ethnographic study in real-world settings. In Proceedings of the 7th ACM/IEEE International Conference on Human-Robot Interaction - HRI'12 (pp. 367--374). Boston, MA, U.S.A.: ACM Press. Google ScholarDigital Library
- Leite, I., Martinho, C., & Paiva, A. (2013). Social robots for long-term interaction: A survey. International Journal of Social Robotics, 5(2), 291--308.Google ScholarCross Ref
- Leyzberg, D., Spaulding, S., Toneva, M., & Scassellati, B. (2012). The physical presence of a robot tutor increases cognitive learning gains. In Proceedings of the 34th Annual Conference of the Cognitive Science Society (pp. 1882--1887). Sapporo, Japan.Google Scholar
- Looije, R., van der Zalm, A., Neerincx, M. a., & Beun, R.-J. (2012). Help, I need some body: The effect of embodiment on playful learning. In Proceedings of the 21st IEEE International Symposium on Robot and Human Interactive Communication (RoMan 2012) (pp. 718--724). IEEE Press.Google ScholarCross Ref
- Lu, a. S., Baranowski, J., Islam, N., & Baranowski, T. (2012). How to engage children in self-administered dietary assessment programmes. Journal of Human Nutrition and Dietetics, 1--5.Google Scholar
- Markus, H., Eichberg, J., & Andre, E. (2012). Studies on grounding with gaze and pointing gestures in human-robot-interaction. In 4th International Conference on Social Robotics (ICSR 2012) (pp. 378--387). Chengdu, China. Google ScholarDigital Library
- Meltzer, D. E. (2002). The relationship between mathematics preparation and conceptual learning gains in physics: A possible hidden variable in diagnostic pretest scores. American Journal of Physics, 70(12), 1259.Google ScholarCross Ref
- Nalin, M., Baroni, I., Kruijff-Korbayova, I., Canamero, L., Lewis, M., Beck, A., ... Sanna, A. (2012). Children's adaptation in multi-session interaction. In Proceedings of the 21st IEEE International Symposium in Robot and Human Interactive Communication (RoMan 2012).Google Scholar
- Nalin, M., Baroni, I., Sanna, A., & Pozzi, C. (2012). Robotic companion for diabetic children. In Proceedings of the 11th International Conference on Interaction Design and Children - IDC'12 (p. 260). New York, New York, USA: ACM Press. Google ScholarDigital Library
- Nalin, M., Verga, M., Sanna, A., & Saranummi, N. (2013). Directions for ICT research in disease prevention. In M. Cruz-Cunha, I. Miranda, & P. Goncalves (Eds.), Handbook of research on ICTs for human-centered healthcare and social care services (pp. 229--247). Hershey, Pennsylvania, USA: IGI Global Press.Google Scholar
- Office of Disease Prevention and Health Promotion. (2013). Physical activity guidelines. Website. Retrieved from http://www.health.gov/paguidelinesGoogle Scholar
- Richman, W. L., Kiesler, S., Weisband, S., & Drasgow, F. (1999). A meta-analytic study of social desirability distortion in computer-administered questionnaires, traditional questionnaires, and interviews. Journal of Applied Psychology, 84(5), 754.Google ScholarCross Ref
- Riek, L. (2012). Wizard of Oz studies in HRI: A systematic review and new reporting guidelines. Journal of Human-Robot Interaction, 1(1), 119--136. Google ScholarDigital Library
- Ros, R., Baroni, I., & Demiris, Y. (2014). Adaptive humanrobot interaction in sensorimotor task instruction: From human to robot dance tutors. Robotics and Autonomous Systems, 62(6), 707--720. Google ScholarDigital Library
- Ros, R., Coninx, A., Demiris, Y., Patsis, G., Enescu, V., & Sahli, H. (2014). Behavioral accommodation towards a dance robot tutor. In Proceedings of the 2014 ACM/IEEE International Conference on Human-Robot Interaction - HRI'14 (pp. 278--279). New York, New York, USA: ACM Press. Google ScholarDigital Library
- Ros, R., & Demiris, Y. (2013). Creative dance: An approach for social interaction between robots and children. In A. A. Salah, H. Hung, O. Aran, & H. Gunes (Eds.), Human behavior understanding (Lecture Notes in Computer Science) (Vol. 8212, pp. 40--51). Springer. Google ScholarDigital Library
- Ros, R., Nalin, M., Wood, R., Baxter, P., Looiije, R., Demiris, Y., ... Pozzi, C. (2011). Child-robot interaction in the wild: Advice to the aspiring experimenter. In Proceedings of the 13th International Conference on Multimodal Interfaces (pp. 335--342). Alicante, Spain: ACM Press. Google ScholarDigital Library
- Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55(1), 68--78.Google ScholarCross Ref
- Saerbeck, M., Schut, T., Bartneck, C., & Janse, M. D. (2010). Expressive robots in education: Varying the degree of social supportive behavior of a robotic tutor. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI 2010) (pp. 1613--1622). Atlanta, USA: ACM Press. Google ScholarDigital Library
- Salter, T., Werry, I., & Michaud, F. (2007). Going into the wild in child-robot interaction studies. Intelligent Service Robotics, 1(2), 93--108.Google ScholarCross Ref
- Salter, T., Werry, I., & Michaud, F. (2008). Going into the wild in childrobot interaction studies: Issues in social robotic development. Intelligent Service Robotics, 1(2), 93--108.Google ScholarCross Ref
- Schiefele, U. (1991). Interest, learning, and motivation. Educational Psychologist, 26(3-4), 299--323.Google ScholarCross Ref
- Segura, E. M., Kriegel, M., Aylett, R., Deshmukh, A., & Cramer, H. (2012). How do you like me in this: User embodiment preferences for companion agents. In Proceedings of the 12th International Conference on Intelligent Virtual Agents (Lecture Notes in Computer Science) (Vol. 7502, pp. 112--125). Santa Cruz, CA, USA: Springer Berlin / Heidelberg. Google ScholarDigital Library
- Shibata, T. (2011). Importance of physical interaction between human and robot for therapy. In C. Stephanidis (Ed.), Universal Access in Human-Computer Interaction: Applications and Services (Vol. 6768, pp. 437--447). Berlin, Heidelberg: Springer Berlin Heidelberg. Google ScholarDigital Library
- Short, E., Swift-spong, K., Greczek, J., Ramachandran, A., Litoiu, A., Grigore, E. C., ... Scassellati, B. (2014). How to train your dragonbot: Socially assistive robots for teaching children about nutrition through play. In 23rd IEEE Symposium on Robot and Human Interactive Communication (RoMan). Edinburgh, U.K.: IEEE Press.Google ScholarCross Ref
- Sidner, C. L. (2012). Engagement: Looking and not looking as evidence for disengagement. In Proceedings of the Workshop on Gaze in HRI (at HRI'12). Boston, MA, USA.Google Scholar
- Sidner, C. L., Lee, C., Kidd, C. D., Lesh, N., & Rich, C. (2005). Explorations in engagement for humans and robots. Artificial Intelligence, 166(1-2), 140--164. Google ScholarDigital Library
- Stiehl, W. D., Lee, J. K., Breazeal, C., Nalin, M., Morandi, A., & Sanna, A. (2009). The huggable: A platform for research in robotic companions for pediatric care. In Proceedings of the 8th International Conference on Interaction Design and Children - IDC'09 (p. 317). New York, New York, USA: ACM Press. Google ScholarDigital Library
- Tanaka, F., Cicourel, A., & Movellan, J. R. (2007). Socialization between toddlers and robots at an early childhood education center. In Proceedings of the National Academy of Sciences of the United States of America (Vol. 104, pp. 17954--8).Google ScholarCross Ref
- Tanaka, F., Movellan, J. R., Fortenberry, B., & Aisaka, K. (2006). Daily HRI evaluation at a classroom environment: Reports from dance interaction experiments. In Proceedings of the 1st ACM SIGCHI/SIGART Conference on Human-Robot Interaction (HRI '06) (pp. 3--9). Salt Lake City, Utah, USA. Google ScholarDigital Library
- Tapus, A., Tapus, C., & Matarić, M. J. (2008, February). Userrobot personality matching and assistive robot behavior adaptation for post-stroke rehabilitation therapy. Intelligent Service Robotics, 1(2), 169--183.Google ScholarCross Ref
- Tesser, F., Sommavilla, G., Paci, G., & Cosi, P. (2013). Experiments with signal-driven symbolic prosody for statistical parametric speech synthesis. In Proceedings of the 8th ISCA Speech Synthesis Workshop (pp. 2--6). Barcelona, Spain.Google Scholar
- Thill, S., Pop, C. A., Belpaeme, T., Ziemke, T., & Vanderborght, B. (2012). Robot-assisted therapy for autism spectrum disorders with (partially) autonomous control: Challenges and outlook. Paladyn Journal of Behavioral Robotics, 3(4), 209--217.Google ScholarCross Ref
- Turkle, S., Breazeal, C., Dasté, O., & Scassellati, B. (2006). Encounters with Kismet and Cog: Children respond to relational artifacts. In P. Messaris & L. Humphreys (Eds.), Digital media: Transformations in human communication (pp. 1--20). New York: Peter Lang Publishing.Google Scholar
- Wainer, J., Feil-Seifer, D. J., Shell, D. A., & Mataric, M. J. (2007). Embodiment and human-robot interaction: A task-based perspective. In Proceedings of the 16th IEEE International Symposium on Robot and Human Interactive Communication (RoMan 2007) (pp. 872--877). IEEE.Google ScholarCross Ref
- Wang, W., Enescu, V., & Sahli, H. (2013). Towards real-time continuous emotion recognition from body movements. Human Behavior Understanding, 8212, 1--11. Google ScholarDigital Library
- Wood, L. J., Dautenhahn, K., Rainer, A., Robins, B., Lehmann, H., & Syrdal, D. S. (2013). Robot-mediated interviews---How effective is a humanoid robot as a tool for interviewing young children? PloS ONE, 8(3), e59448.Google ScholarCross Ref
- World Health Organization. (2014). A healthy lifestyle. Website. Retrieved from http://www.euro.who.int/en/health-topics/disease-prevention/nutrition/a-healthy-lifestyleGoogle Scholar
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- Towards long-term social child-robot interaction: using multi-activity switching to engage young users
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