467 research outputs found
Machine Body Language: Expressing a Smart Speakerâs Activity with Intelligible Physical Motion
Peopleâs physical movement and body language implicitly convey what they think and feel, are doing or are about to do. In contrast, current smart speakers miss out on this richness of body language, primarily relying on voice commands only. We present QUBI, a dynamic smart speaker that leverages expressive physical motion â stretching, nodding, turning, shrugging, wiggling, pointing and leaning forwards/backwards â to convey cues about its underlying behaviour and activities. We conducted a qualitative Wizard of Oz lab study, in which 12 participants interacted with QUBI in four scripted scenarios. From our study, we distilled six themes: (1) mirroring and mimicking motions; (2) body language to supplement voice instructions; (3) anthropomorphism and personality; (4) audio can trump motion; (5) reaffirming uncertain interpretations to support mutual understanding; and (6) emotional reactions to QUBIâs behaviour. From this, we discuss design implications for future smart speakers
Tangible Interaction with In-Car Smart Intelligence
Interacting with a car was once a tactile experience, which is on the decline with the rise of car assistants, where the dominant form of interaction is through screen displays and voice recognition. These interaction modalities within a car are not the only options available. In this paper, we discuss reintroducing tactility into the automotive experience. This work presents a tactile embodiment of an intelligent car system, different from previous studies, to improve engagement and emotional connection between users and future intelligent cars. A prototype tool was designed to embody an intelligent car system. It was used to investigate how to interact with and control a smart-comfort system to improve user comfort. The tool invited users to interact through touch. Users could use their hands to physically agree or disagree with changes made by the system with the system moving in response, creating a bi-directional interaction symbiosis that re-prioritises tactility
Interactive spaces for children: gesture elicitation for controlling ground mini-robots
[EN] Interactive spaces for education are emerging as a mechanism for fostering children's natural ways of learning by means of play and exploration in physical spaces. The advanced interactive modalities and devices for such environments need to be both motivating and intuitive for children. Among the wide variety of interactive mechanisms, robots have been a popular research topic in the context of educational tools due to their attractiveness for children. However, few studies have focused on how children would naturally interact and explore interactive environments with robots. While there is abundant research on full-body interaction and intuitive manipulation of robots by adults, no similar research has been done with children. This paper therefore describes a gesture elicitation study that identified the preferred gestures and body language communication used by children to control ground robots. The results of the elicitation study were used to define a gestural language that covers the different preferences of the gestures by age group and gender, with a good acceptance rate in the 6-12 age range. The study also revealed interactive spaces with robots using body gestures as motivating and promising scenarios for collaborative or remote learning activities.This work is funded by the European Development Regional Fund (EDRF-FEDER) and supported by the Spanish MINECO (TIN2014-60077-R). The work of Patricia Pons is supported by a national grant from the Spanish MECD (FPU13/03831). Special thanks are due to the children and teachers of the Col-legi Public Vicente Gaos for their valuable collaboration and dedication.Pons TomĂĄs, P.; JaĂ©n MartĂnez, FJ. (2020). Interactive spaces for children: gesture elicitation for controlling ground mini-robots. Journal of Ambient Intelligence and Humanized Computing. 11(6):2467-2488. https://doi.org/10.1007/s12652-019-01290-6S24672488116Alborzi H, Hammer J, Kruskal A et al (2000) Designing StoryRooms: interactive storytelling spaces for children. In: Proceedings of the conference on designing interactive systems processes, practices, methods, and techniquesâDISâ00. ACM Press, New York, pp 95â104Antle AN, Corness G, Droumeva M (2009) What the body knows: exploring the benefits of embodied metaphors in hybrid physical digital environments. Interact Comput 21:66â75. https://doi.org/10.1016/j.intcom.2008.10.005Belpaeme T, Baxter PE, Read R et al (2013) Multimodal childârobot interaction: building social bonds. J Human-Robot Interact 1:33â53. https://doi.org/10.5898/JHRI.1.2.BelpaemeBenko H, Wilson AD, Zannier F, Benko H (2014) Dyadic projected spatial augmented reality. In: Proceedings of the 27th annual ACM symposium on user interface software and technologyâUISTâ14, pp 645â655Bobick AF, Intille SS, Davis JW et al (1999) The KidsRoom: a perceptually-based interactive and immersive story environment. Presence Teleoper Virtual Environ 8:367â391. https://doi.org/10.1162/105474699566297Bonarini A, Clasadonte F, Garzotto F, Gelsomini M (2015) Blending robots and full-body interaction with large screens for children with intellectual disability. In: Proceedings of the 14th international conference on interaction design and childrenâIDCâ15. ACM Press, New York, pp 351â354Cauchard JR, E JL, Zhai KY, Landay JA (2015) Drone & me: an exploration into natural humanâdrone interaction. In: Proceedings of the 2015 ACM international joint conference on pervasive and ubiquitous computingâUbiCompâ15. ACM Press, New York, pp 361â365Connell S, Kuo P-Y, Liu L, Piper AM (2013) A Wizard-of-Oz elicitation study examining child-defined gestures with a whole-body interface. In: Proceedings of the 12th international conference on interaction design and childrenâIDCâ13. ACM Press, New York, pp 277â280Derboven J, Van Mechelen M, Slegers K (2015) Multimodal analysis in participatory design with children. In: Proceedings of the 33rd annual ACM conference on human factors in computing systemsâCHIâ15. ACM Press, New York, pp 2825â2828Dong H, Danesh A, Figueroa N, El Saddik A (2015) An elicitation study on gesture preferences and memorability toward a practical hand-gesture vocabulary for smart televisions. IEEE Access 3:543â555. https://doi.org/10.1109/ACCESS.2015.2432679Druin A (1999) Cooperative inquiry: developing new technologies for children with children. In: Proceedings of the SIGCHI conference on human factors computer system CHI is limitâCHIâ99, vol 14, pp 592â599. https://doi.org/10.1145/302979.303166Druin A (2002) The role of children in the design of new technology. Behav Inf Technol 21:1â25. https://doi.org/10.1080/01449290110108659Druin A, Bederson B, Boltman A et al (1999) Children as our technology design partners. In: Druin A (ed) The design of childrenâs technology. Morgan Kaufman, San Francisco, pp 51â72Epps J, Lichman S, Wu M (2006) A study of hand shape use in tabletop gesture interaction. CHIâ06 extended abstracts on human factors in computing systemsâCHI EAâ06. ACM Press, New York, pp 748â753Fender AR, Benko H, Wilson A (2017) MeetAliveâŻ: room-scale omni-directional display system for multi-user content and control sharing. In: Proceedings of the 2017 ACM international conference on interactive surfaces and spaces, pp 106â115Fernandez RAS, Sanchez-Lopez JL, Sampedro C et al (2016) Natural user interfaces for humanâdrone multi-modal interaction. In: 2016 international conference on unmanned aircraft systems (ICUAS). IEEE, New York, pp 1013â1022Garcia-Sanjuan F, Jaen J, Nacher V, Catala A (2015) Design and evaluation of a tangible-mediated robot for kindergarten instruction. In: Proceedings of the 12th international conference on advances in computer entertainment technologyâACEâ15. ACM Press, New York, pp 1â11Garcia-Sanjuan F, Jaen J, Jurdi S (2016) Towards encouraging communication in hospitalized children through multi-tablet activities. In: Proceedings of the XVII international conference on human computer interaction, pp 29.1â29.4Gindling J, Ioannidou A, Loh J et al (1995) LEGOsheets: a rule-based programming, simulation and manipulation environment for the LEGO programmable brick. In: Proceedings of symposium on visual languages. IEEE Computer Society Press, New York, pp 172â179Gonzalez B, Borland J, Geraghty K (2009) Whole body interaction for child-centered multimodal language learning. In: Proceedings of the 2nd workshop on child, computer and interactionâWOCCIâ09. ACM Press, New York, pp 1â5GrĂžnbĂŠk K, Iversen OS, Kortbek KJ et al (2007) Interactive floor support for kinesthetic interaction in children learning environments. In: Humanâcomputer interactionâINTERACT 2007. Lecture notes in computer science, pp 361â375Guha ML, Druin A, Chipman G et al (2005) Working with young children as technology design partners. Commun ACM 48:39â42. https://doi.org/10.1145/1039539.1039567Hansen JP, Alapetite A, MacKenzie IS, MĂžllenbach E (2014) The use of gaze to control drones. In: Proceedings of the symposium on eye tracking research and applicationsâETRAâ14. ACM Press, New York, pp 27â34Henkemans OAB, Bierman BPB, Janssen J et al (2017) Design and evaluation of a personal robot playing a self-management education game with children with diabetes type 1. Int J Hum Comput Stud 106:63â76. https://doi.org/10.1016/j.ijhcs.2017.06.001Horn MS, Crouser RJ, Bers MU (2011) Tangible interaction and learning: the case for a hybrid approach. Pers Ubiquitous Comput 16:379â389. https://doi.org/10.1007/s00779-011-0404-2Hourcade JP (2015) Child computer interaction. CreateSpace Independent Publishing Platform, North CharlestonHöysniemi J, HĂ€mĂ€lĂ€inen P, Turkki L (2004) Wizard of Oz prototyping of computer vision based action games for children. Proceeding of the 2004 conference on interaction design and children building a communityâIDCâ04. ACM Press, New York, pp 27â34Höysniemi J, HĂ€mĂ€lĂ€inen P, Turkki L, Rouvi T (2005) Childrenâs intuitive gestures in vision-based action games. Commun ACM 48:44â50. https://doi.org/10.1145/1039539.1039568Hsiao H-S, Chen J-C (2016) Using a gesture interactive game-based learning approach to improve preschool childrenâs learning performance and motor skills. Comput Educ 95:151â162. https://doi.org/10.1016/j.compedu.2016.01.005Jokela T, Rezaei PP, VÀÀnĂ€nen K (2016) Using elicitation studies to generate collocated interaction methods. In: Proceedings of the 18th international conference on humanâcomputer interaction with mobile devices and services adjunct, pp 1129â1133. https://doi.org/10.1145/2957265.2962654Jones B, Benko H, Ofek E, Wilson AD (2013) IllumiRoom: peripheral projected illusions for interactive experiences. In: Proceedings of the SIGCHI conference on human factors in computing systemsâCHIâ13, pp 869â878Jones B, Shapira L, Sodhi R et al (2014) RoomAlive: magical experiences enabled by scalable, adaptive projector-camera units. In: Proceedings of the 27th annual ACM symposium on user interface software and technologyâUISTâ14, pp 637â644Kaminski M, Pellino T, Wish J (2002) Play and pets: the physical and emotional impact of child-life and pet therapy on hospitalized children. Child Heal Care 31:321â335. https://doi.org/10.1207/S15326888CHC3104_5Karam M, Schraefel MC (2005) A taxonomy of gestures in human computer interactions. In: Technical report in electronics and computer science, pp 1â45Kistler F, AndrĂ© E (2013) User-defined body gestures for an interactive storytelling scenario. Lect Notes Comput Sci (including subser Lect Notes Artif Intell Lect Notes Bioinform) 8118:264â281. https://doi.org/10.1007/978-3-642-40480-1_17Konda KR, Königs A, Schulz H, Schulz D (2012) Real time interaction with mobile robots using hand gestures. In: Proceedings of the seventh annual ACM/IEEE international conference on humanârobot interactionâHRIâ12. ACM Press, New York, pp 177â178Kray C, Nesbitt D, Dawson J, Rohs M (2010) User-defined gestures for connecting mobile phones, public displays, and tabletops. In: Proceedings of the 12th international conference on human computer interaction with mobile devices and servicesâMobileHCIâ10. ACM Press, New York, pp 239â248Kurdyukova E, Redlin M, AndrĂ© E (2012) Studying user-defined iPad gestures for interaction in multi-display environment. In: Proceedings of the 2012 ACM international conference on intelligent user interfacesâIUIâ12. ACM Press, New York, pp 93â96Lambert V, Coad J, Hicks P, Glacken M (2014) Social spaces for young children in hospital. Child Care Health Dev 40:195â204. https://doi.org/10.1111/cch.12016Lee S-S, Chae J, Kim H et al (2013) Towards more natural digital content manipulation via user freehand gestural interaction in a living room. In: Proceedings of the 2013 ACM international joint conference on pervasive and ubiquitous computingâUbiCompâ13. ACM Press, New York, p 617Malinverni L, Mora-Guiard J, Pares N (2016) Towards methods for evaluating and communicating participatory design: a multimodal approach. Int J Hum Comput Stud 94:53â63. https://doi.org/10.1016/j.ijhcs.2016.03.004Mann HB, Whitney DR (1947) On a test of whether one of two random variables is stochastically larger than the other. Ann Math Stat 18:50â60. https://doi.org/10.1214/aoms/1177730491Marco J, Cerezo E, Baldassarri S et al (2009) Bringing tabletop technologies to kindergarten children. In: Proceedings of the 23rd British HCI Group annual conference on people and computers: celebrating people and technology, pp 103â111Michaud F, Caron S (2002) Roball, the rolling robot. Auton Robots 12:211â222. https://doi.org/10.1023/A:1014005728519Micire M, Desai M, Courtemanche A et al (2009) Analysis of natural gestures for controlling robot teams on multi-touch tabletop surfaces. In: Proceedings of the ACM international conference on interactive tabletops and surfacesâITSâ09. ACM Press, New York, pp 41â48Mora-Guiard J, Crowell C, Pares N, Heaton P (2016) Lands of fog: helping children with autism in social interaction through a full-body interactive experience. In: Proceedings of the 15th international conference on interaction design and childrenâIDCâ16. ACM Press, New York, pp 262â274Morris MR (2012) Web on the wall: insights from a multimodal interaction elicitation study. In: Proceedings of the 2012 ACM international conference on interactive tabletops and surfaces. ACM Press, New York, pp 95â104Morris MR, Wobbrock JO, Wilson AD (2010) Understanding usersâ preferences for surface gestures. Proc Graph Interface 2010:261â268Nacher V, Garcia-Sanjuan F, Jaen J (2016) Evaluating the usability of a tangible-mediated robot for kindergarten children instruction. In: 2016 IEEE 16th international conference on advanced learning technologies (ICALT). IEEE, New York, pp 130â132Nahapetyan VE, Khachumov VM (2015) Gesture recognition in the problem of contactless control of an unmanned aerial vehicle. Optoelectron Instrum Data Process 51:192â197. https://doi.org/10.3103/S8756699015020132Obaid M, HĂ€ring M, Kistler F et al (2012) User-defined body gestures for navigational control of a humanoid robot. In: Lecture notes in computer science (including subseries lecture notes in artificial intelligence and lecture notes in bioinformatics), pp 367â377Obaid M, Kistler F, HĂ€ring M et al (2014) A framework for user-defined body gestures to control a humanoid robot. Int J Soc Robot 6:383â396. https://doi.org/10.1007/s12369-014-0233-3Obaid M, Kistler F, KasparaviÄiĆ«tÄ G, et al (2016) How would you gesture navigate a drone?: a user-centered approach to control a drone. In: Proceedings of the 20th international academic Mindtrek conferenceâAcademicMindtrekâ16. ACM Press, New York, pp 113â121Pares N, Soler M, Sanjurjo Ă et al (2005) Promotion of creative activity in children with severe autism through visuals in an interactive multisensory environment. In: Proceeding of the 2005 conference on interaction design and childrenâIDCâ05. ACM Press, New York, pp 110â116Pfeil K, Koh SL, LaViola J (2013) Exploring 3D gesture metaphors for interaction with unmanned aerial vehicles. In: Proceedings of the 2013 international conference on intelligent user interfacesâIUIâ13, pp 257â266. https://doi.org/10.1145/2449396.2449429Piaget J (1956) The childâs conception of space. Norton, New YorkPiaget J (1973) The child and reality: problems of genetic psychology. Grossman, New YorkPiumsomboon T, Clark A, Billinghurst M, Cockburn A (2013) User-defined gestures for augmented reality. CHIâ13 extended abstracts on human factors in computing systemsâCHI EAâ13. ACM Press, New York, pp 955â960Pons P, CarriĂłn A, Jaen J (2018) Remote interspecies interactions: improving humans and animalsâ wellbeing through mobile playful spaces. Pervasive Mob Comput. https://doi.org/10.1016/j.pmcj.2018.12.003Puranam MB (2005) Towards full-body gesture analysis and recognition. University of Kentucky, LexingtonPyryeskin D, Hancock M, Hoey J (2012) Comparing elicited gestures to designer-created gestures for selection above a multitouch surface. In: Proceedings of the 2012 ACM international conference on interactive tabletops and surfacesâITSâ12. ACM Press, New York, pp 1â10Raffle HS, Parkes AJ, Ishii H (2004) Topobo: a constructive assembly system with kinetic memory. System 6:647â654. https://doi.org/10.1145/985692.985774Read JC, Markopoulos P (2013) Childâcomputer interaction. Int J Child-Comput Interact 1:2â6. https://doi.org/10.1016/j.ijcci.2012.09.001Read JC, Macfarlane S, Casey C (2002) Endurability, engagement and expectations: measuring childrenâs fun. In: Interaction design and children, pp 189â198Read JC, Markopoulos P, ParĂ©s N et al (2008) Child computer interaction. In: Proceeding of the 26th annual CHI conference extended abstracts on human factors in computing systemsâCHIâ08. ACM Press, New York, pp 2419â2422Robins B, Dautenhahn K (2014) Tactile interactions with a humanoid robot: novel play scenario implementations with children with autism. Int J Soc Robot 6:397â415. https://doi.org/10.1007/s12369-014-0228-0Robins B, Dautenhahn K, Te Boekhorst R, Nehaniv CL (2008) Behaviour delay and robot expressiveness in childârobot interactions: a user study on interaction kinesics. In: Proceedings of the 3rd ACMIEEE international conference on human robot interaction, pp 17â24. https://doi.org/10.1145/1349822.1349826Ruiz J, Li Y, Lank E (2011) User-defined motion gestures for mobile interaction. In: Proceedings of the 2011 annual conference on human factors in computing systemsâCHIâ11. ACM Press, New York, p 197Rust K, Malu M, Anthony L, Findlater L (2014) Understanding childdefined gestures and childrenâs mental models for touchscreen tabletop interaction. In: Proceedings of the 2014 conference on interaction design and childrenâIDCâ14. ACM Press, New York, pp 201â204Salter T, Dautenhahn K, Te Boekhorst R (2006) Learning about natural human-robot interaction styles. Robot Auton Syst 54:127â134. https://doi.org/10.1016/j.robot.2005.09.022Sanghvi J, Castellano G, Leite I et al (2011) Automatic analysis of affective postures and body motion to detect engagement with a game companion. In: Proceedings of the 6th international conference on humanârobot interactionâHRIâ11. ACM Press, New York, pp 305â311Sanna A, Lamberti F, Paravati G, Manuri F (2013) A Kinect-based natural interface for quadrotor control. Entertain Comput 4:179â186. https://doi.org/10.1016/j.entcom.2013.01.001Sato E, Yamaguchi T, Harashima F (2007) Natural interface using pointing behavior for humanârobot gestural interaction. IEEE Trans Ind Electron 54:1105â1112. https://doi.org/10.1109/TIE.2007.892728Schaper M-M, Pares N (2016) Making sense of body and space through full-body interaction design. In: Proceedings of the 15th international conference on interaction design and childrenâIDCâ16. ACM Press, New York, pp 613â618Schaper M-M, Malinverni L, Pares N (2015) Sketching through the body: child-generated gestures in full-body interaction design. In: Proceedings of the 14th international conference on interaction design and childrenâIDCâ15. ACM Press, New York, pp 255â258Seyed T, Burns C, Costa Sousa M et al (2012) Eliciting usable gestures for multi-display environments. In: Proceedings of the 2012 ACM international conference on interactive tabletops and surfacesâITSâ12. ACM Press, New York, p 41Shimon SSA, Morrison-Smith S, John N et al (2015) Exploring user-defined back-of-device gestures for mobile devices. In: Proceedings of the 17th international conference on humanâcomputer interaction with mobile devices and servicesâMobileHCIâ15. ACM Press, New York, pp 227â232Sipitakiat A, Nusen N (2012) Robo-blocks: a tangible programming system with debugging for children. In: Proceedings of the 11th international conference on interaction design and childrenâIDCâ12. ACM Press, New York, p 98Soler-Adillon J, Ferrer J, Pares N (2009) A novel approach to interactive playgrounds: the interactive slide project. In: Proceedings of the 8th international conference on interaction design and childrenâIDCâ09. ACM Press, New York, pp 131â139Stiefelhagen R, Fogen C, Gieselmann P et al (2004) Natural humanârobot interaction using speech, head pose and gestures. In: 2004 IEEE/RSJ international conference on intelligent robots and systems (IROS) (IEEE Cat. No. 04CH37566). IEEE, New York, pp 2422â2427Subrahmanyam K, Greenfield PM (1994) Effect of video game practice on spatial skills in girls and boys. J Appl Dev Psychol 15:13â32. https://doi.org/10.1016/0193-3973(94)90004-3Sugiyama J, Tsetserukou D, Miura J (2011) NAVIgoid: robot navigation with haptic vision. In: SIGGRAPH Asia 2011 emerging technologies SAâ11, vol 15, p 4503. https://doi.org/10.1145/2073370.2073378Takahashi T, Morita M, Tanaka F (2012) Evaluation of a tricycle-style teleoperational interface for children: a comparative experiment with a video game controller. In: 2012 IEEE RO-MAN: the 21st IEEE international symposium on robot and human interactive communication. IEEE, New York, pp 334â338Tanaka F, Takahashi T (2012) A tricycle-style teleoperational interface that remotely controls a robot for classroom children. In: Proceedings of the seventh annual ACM/IEEE international conference on humanârobot interactionâHRIâ12. ACM Press, New York, pp 255â256Tjaden L, Tong A, Henning P et al (2012) Childrenâs experiences of dialysis: a systematic review of qualitative studies. Arch Dis Child 97:395â402. https://doi.org/10.1136/archdischild-2011-300639Vatavu R-D (2012) User-defined gestures for free-hand TV control. In: Proceedings of the 10th European conference on interactive TV and videoâEuroiTVâ12. ACM Press, New York, pp 45â48Vatavu R-D (2017) Smart-Pockets: body-deictic gestures for fast access to personal data during ambient interactions. Int J Hum Comput Stud 103:1â21. https://doi.org/10.1016/j.ijhcs.2017.01.005Vatavu R-D, Wobbrock JO (2015) Formalizing agreement analysis for elicitation studies: new measures, significance test, and toolkit. In: Proceedings of the 33rd annual ACM conference on human factors in computing systemsâCHIâ15. ACM Press, New York, pp 1325â1334Vatavu R-D, Wobbrock JO (2016) Between-subjects elicitation studies: formalization and tool support. In: Proceedings of the 2016 CHI conference on human factors in computing systemsâCHIâ16. ACM Press, New York, pp 3390â3402Voyer D, Voyer S, Bryden MP (1995) Magnitude of sex differences in spatial abilities: a meta-analysis and consideration of critical variables. Psychol Bull 117:250â270. https://doi.org/10.1037/0033-2909.117.2.250Wainer J, Robins B, Amirabdollahian F, Dautenhahn K (2014) Using the humanoid robot KASPAR to autonomously play triadic games and facilitate collaborative play among children with autism. IEEE Trans Auton Ment Dev 6:183â199. https://doi.org/10.1109/TAMD.2014.2303116Wang Y, Zhang L (2015) A track-based gesture recognition algorithm for Kinect. Appl Mech Mater 738â7399:334â338. https://doi.org/10.4028/www.scientific.net/AMM.738-739.334
An emotion and memory model for social robots : a long-term interaction
In this thesis, we investigate the role of emotions and memory in social robotic companions. In particular, our aim is to study the effect of an emotion and memory model towards sustaining engagement and promoting learning in a long-term interaction. Our Emotion and Memory model was based on how humans create memory under various emotional events/states. The model enabled the robot to create a memory account of user's emotional events during a long-term child-robot interaction. The robot later adapted its behaviour through employing the developed memory in the following interactions with the users. The model also had an autonomous decision-making mechanism based on reinforcement learning to select behaviour according to the user preference measured through user's engagement and learning during the task. The model was implemented on the NAO robot in two different educational setups. Firstly, to promote user's vocabulary learning and secondly, to inform how to calculate area and perimeter of regular and irregular shapes. We also conducted multiple long-term evaluations of our model with children at the primary schools to verify its impact on their social engagement and learning. Our results showed that the behaviour generated based on our model was able to sustain social engagement. Additionally, it also helped children to improve their learning. Overall, the results highlighted the benefits of incorporating memory during child-Robot Interaction for extended periods of time. It promoted personalisation and reflected towards creating a child-robot social relationship in a long-term interaction
How to Include Humanoid Robots into Experimental Research: A Multi-Step Approach
Robots have penetrated many areas of daily life, including increased uses of humanoid robots in personal and organizational settings such as health care, eldercare, and service encounters with customers. Little research examines humanoid robots in these professional settings, even though the human-robot interaction (HRI) is particularly critical in such contexts. On the basis of a literature review and experience from several experimental studies, this article offers some guidance for designing HRI experiments with humanoid robots. In addition to detailing major challenges associated with designing HRI studies, this article suggests important next steps for experimental research with humanoid robots, as well as implications for further study
Pulling Back the Curtain on the Wizards of Oz
The Wizard of Oz method is an increasingly common practice in HCI and CSCW studies as part of iterative design processes for interactive systems. Instead of designing a fully-fledged system, the âtechnical workâ of key system components is completed by human operators yet presented to study participants as if computed by a machine. However, little is known about how Wizard of Oz studies are interactionally and collaboratively achieved in situ by researchers and participants. By adopting an ethnomethodological perspective, we analyse our use of the method in studies with a voice-controlled vacuum robot and two researchers present. We present data that reveals how such studies are organised and presented to participants and unpack the coordinated orchestration work that unfolds âbehind the scenesâ to complete the study. We examine how the researchers attend to participant requests and technical breakdowns, and discuss the performative, collaborative, and methodological nature of their work. We conclude by offering insights from our application of the approach to others in the HCI and CSCW communities for using the method
Social Robots as Language Tutors:Challenges and Opportunities
In this paper we highlight several challenges we encountered while developing an Intelligent Tutoring System. Most importantly, technical limitations are currently standing in the way of the robot's ability to behave fully autonomously, and there is a need for methods and best practices from the field of human-computer interaction to ensure that user experience goals related to the quality of the holistic experience of interacting with a robot are set, and subsequently met. We also identify opportunities in the form of a modular (technical) architecture, and the implementation of a human-centered design process by including this discipline as one of the core components when setting up a project in the field of human-robot interaction
Impact of Head Motion on the Assistive Robot Expressiveness - Evaluation with Elderly Persons
International audienceIn the near future, robots will support human to perform tasks in many domains (industrial, domestic, educational and health tasks).Such robot behaviors need to take into account the social interaction between robot and human.In this context, we focus on the expressiveness of a moving head for an assistive robot for the elderly.We designed a new moving head for the KompaĂŻ companion robot.On one hand, this new head improves its perception capabilities.On the other hand, we expect to jointly increase its social skills and thus its acceptability.This new head is composed of a tablet to animate a virtual face according to 4 facial expressions and a mechanical neck with 4 degrees of freedom to enhance the robot's expression.Before improving face expressions and adding more complex head movements, it is essential to evaluate the combination of simple head movements with virtual face expressions. A study was held jointly with physicians (psychologists, ergonomists) at the Broca Hospital in Paris to assess the impact to combine head movements with virtual face expressions, and the global acceptability of the KompaĂŻ head by the elderly
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