Advertisement

International Journal of Social Robotics

, Volume 6, Issue 2, pp 195–211 | Cite as

Socially Assistive Robots: A Comprehensive Approach to Extending Independent Living

  • David O. JohnsonEmail author
  • Raymond H. Cuijpers
  • James F. Juola
  • Elena Torta
  • Mikhail Simonov
  • Antonella Frisiello
  • Marco Bazzani
  • Wenjie Yan
  • Cornelius Weber
  • Stefan Wermter
  • Nils Meins
  • Johannes Oberzaucher
  • Paul Panek
  • Georg Edelmayer
  • Peter Mayer
  • Christian Beck
Article

Abstract

Demographic developments have challenged our research on how to assist elderly people by using robots. The KSERA (Knowledgeable SErvice Robots for Aging) project integrates smart home technology and a socially-assistive robot to extend independent living for elderly people, in particular those with COPD (Chronic Obstructive Pulmonary Disease). The social robot is the most visible component of the system playing the role of communication interface between the elderly, the smart home, and the external world. The robot’s behavior is determined in part by sensor information gathered through the smart home. To ensure user acceptance, we used user-centered design to implement the robot’s behavior. This paper describes the KSERA system, how it was developed based on user needs, treatment plans, and lab studies, and how we validated the approach through user studies and field trials. The key enabling technologies for successful socially-assistive robots include person- and self-localization abilities, person-aware navigation, speech recognition and generation, robot gestures, emulated emotions, eye contact and joint attention, and audio-video communication with family members and care givers.

Keywords

Human-robot interaction Socially assistive robot Smart home User-centered design 

Notes

Acknowledgements

The KSERA project (http://www.ksera-project.eu) received funding from the European Commission under the 7th Framework Programme (FP7) for Research and Technological Development under grant agreement No. 2010-248085.

References

  1. 1.
    Akkaya K, Younis M (2005) A survey on routing protocols for wireless sensor networks. Ad Hoc Netw 3(3):325–349. doi: 10.1016/j.adhoc.2003.09.010 CrossRefGoogle Scholar
  2. 2.
    Akyildiz IF, Su W, Sankarasubramaniam Y, Cayirci E (2002) A survey on sensor networks. IEEE Commun Mag 40(8):102–114. doi: 10.1109/MCOM.2002.1024422 CrossRefGoogle Scholar
  3. 3.
    Aldebaran Robotics (2012) Nao key features. www.aldebaran-robotics.com/en/Discover-NAO/Key-Features/hardware-platform.html. Accessed 17 July 2012
  4. 4.
    Amigo (2012) Amigo: ambient intelligence for the networked home environment. www.hitech-projects.com/euprojects/amigo. Accessed 17 August 2012
  5. 5.
    Andric M, Small SL (2012) Gesture’s neural language. Front. Psychol. 3 Google Scholar
  6. 6.
    Banks MR, Willoughby LM, Banks WA (2008) Animal-assisted therapy and loneliness in nursing homes: use of robotic versus living dogs. J Am Med Dir Assoc 9(3):173–177. doi: 10.1016/j.jamda.2007.11.007 CrossRefGoogle Scholar
  7. 7.
    Bartneck C, Kulić D, Croft E, Zoghbi S (2009) Measurement instruments for the anthropomorphism, animacy, likeability, perceived intelligence, and perceived safety of robots. Int J Soc Robot 1(1):71–81 CrossRefGoogle Scholar
  8. 8.
    Bemelmans R, Gelderblom GJ, Jonker P, de Witte L (2012) Socially assistive robots in elderly care: a systematic review into effects and effectiveness. J Am Med Dir Assoc 13(2):114–120. doi: 10.1016/j.jamda.2010.10.002 CrossRefGoogle Scholar
  9. 9.
    Breazeal C (2007) Sociable robots. J Robotics Soc Jpn 24(5):591–593 CrossRefGoogle Scholar
  10. 10.
    Bremner J, Frost A, Haub C, Mather M, Ringheim K, Zuehlke E (2010) World population highlights: key findings from PRB’s 2010 world population data sheet. Population Reference Bureau Google Scholar
  11. 11.
    Broekens J, Heerink M, Rosendal H (2009) Assistive social robots in elderly care: a review. Gerontechnology 8(2):94–103 CrossRefGoogle Scholar
  12. 12.
    Cesta A, Coradeschi S, Cortellessa G, Gonzalez J, Tiberio L, Von Rump S (2010) Enabling social interaction through embodiment in ExCITE. In: ForItAAL: second Italian forum on ambient assisted living, Trento, October, pp 5–7 Google Scholar
  13. 13.
    Cesta A, Cortellessa G, Giuliani V, Pecora F, Rasconi R, Scopelliti M, Tiberio L (2007) Proactive assistive technology: an empirical study. In: Human-computer interaction (INTERACT 2007). Springer, Berlin, pp 255–268. doi: 10.1007/978-3-540-74796-325 CrossRefGoogle Scholar
  14. 14.
    Clodic A, Alami R, Montreuil V, Li S, Wrede B, Swadzba A (2007) A study of interaction between dialog and decision for human-robot collaborative task achievement. In: The 16th IEEE international symposium on robot and human interactive communication (RO-MAN 2007). IEEE Press, New York, pp 913–918. doi: 10.1109/ROMAN.2007.4415214 CrossRefGoogle Scholar
  15. 15.
    Cuijpers RH, Bruna MT, Ham JR, Torta E (2011) Attitude towards robots depends on interaction but not on anticipatory behaviour. In: Social robotics. Springer, Berlin, pp 163–172. doi: 10.1007/978-3-642-25504-5_17 CrossRefGoogle Scholar
  16. 16.
    DOMEO (Domestic Robot for Elderly Assistance) (2012). www.aal-domeo.eu. Accessed 17 August 2012
  17. 17.
    Edelmayer G, Ehrenfels G, Beck C, Mayer P, Panek P (2012) Prototyping a LED projector module carried by a humanoid nao robot to assist human robot communication by an additional visual output channel. In: Proc IASTED, pp 809–816 Google Scholar
  18. 18.
    Ekman P, Friesen WV (1969) The repertoire of nonverbal behavior: categories, origins, usage, and coding. Semiotica 1(1):49–98 Google Scholar
  19. 19.
    Ekman P, Friesen WV (1977) Manual for the facial action coding system Google Scholar
  20. 20.
    Feil-Seifer D, Mataric MJ (2005) Defining socially assistive robotics. In: 9th international conference on rehabilitation robotics (ICORR 2005). IEEE Press, New York, pp 465–468. doi: 10.1109/ICORR.2005.1501143 Google Scholar
  21. 21.
    Friedman B, Kahn PH Jr, Hagman J (2003) Hardware companions? What online AIBO discussion forums reveal about the human-robotic relationship. In: Proceedings of the SIGCHI conference on human factors in computing systems. ACM, New York, pp 273–280. doi: 10.1145/642611.642660 Google Scholar
  22. 22.
    Ham J, Bokhorst R, Cuijpers RH, van der Pol D, Cabibihan JJ (2011) Making robots persuasive: the influence of combining persuasive strategies (gazing and gestures) by a storytelling robot on its persuasive power. In: Social robotics. Springer, Berlin, pp 71–83 CrossRefGoogle Scholar
  23. 23.
    Hüttenrauch H, Eklundh KS, Green A, Topp EA (2006) Investigating spatial relationships in human-robot interaction. In: IEEE/RSJ international conference on intelligent robots and systems. IEEE Press, New York, pp 5052–5059. doi: 10.1109/IROS.2006.282535 Google Scholar
  24. 24.
    Huijnen C, Badii A, van den Heuvel H, Caleb-Solly P, Thiemert D (2011) Maybe it becomes a buddy, but do not call it a robot—seamless cooperation between companion robotics and smart homes. In: Ambient intelligence. Springer, Berlin, pp 324–329. doi: 10.1007/978-3-642-25167-244(10.1007/978-3-642-25167-244) CrossRefGoogle Scholar
  25. 25.
    International Organization for Standardization (1999) ISO 13407: human-centred design processes for interactive systems Google Scholar
  26. 26.
    International Organization for Standardization (1998). ISO 9241-11: ergonomic requirements for office work with visual display terminals (VDTs). Part 11. Guidance on usability Google Scholar
  27. 27.
    Johnson DO, Cuijpers RH, van der Pol D (2013) Imitating human emotions with artificial facial expressions. Int J Soc Robot. doi: 10.1007/s12369-013-0211-1 Google Scholar
  28. 28.
    Kendon A (1967) Some functions of gaze direction in social interaction. Acta Psychol 26:22–63 CrossRefGoogle Scholar
  29. 29.
    Knowledgeable SErvice robots for aging project (KSERA) (2012). http://www.ksera-project.eu
  30. 30.
    Kwon JW, Park YM, Koo SJ, Kim H (2007) Design of air pollution monitoring system using ZigBee networks for ubiquitous-city. In: International conference on convergence information technology, 2007. IEEE Press, New York, pp 1024–1031 CrossRefGoogle Scholar
  31. 31.
    Lee S, Noh H, Lee J, Lee K, Lee GG, Sagong S, Kim M (2011) On the effectiveness of robot-assisted language learning. ReCALL (Hull) 23(01):25–58. doi: 10.1017/S0958344010000273 CrossRefGoogle Scholar
  32. 32.
    Li Z, Feng G, Liu F, Dong JQ, Kamoua R, Tang W (2010) Wireless health monitoring system. In: Systems, applications and technology conference (LISAT), Long Island, IEEE Press, New York, pp 1–4 Google Scholar
  33. 33.
    Lohse M, Rohlfing KJ, Wrede B, Sagerer G (2008) Try something else! When users change their discursive behavior in human-robot interaction. In: IEEE international conference on robotics and automation (ICRA 2008). IEEE Press, New York, pp 3481–3486. doi: 10.1109/ROBOT.2008.4543743 CrossRefGoogle Scholar
  34. 34.
    Lowet D, Isken M, Ludden G, van Dijk DJ, Remazeilles A, Cruz Martin E (2010) State of the art in AAL robotic services, deliverable: D5.1, Florence consortium Google Scholar
  35. 35.
    Lutz C, White GM (1986) The anthropology of emotions. Annu Rev Anthropol 15:405–436 CrossRefGoogle Scholar
  36. 36.
    Mayer P, Panek P (2011) An AAL approach to status and activity assessment by use of domain expert knowledge based on sparse nonintrusive sensors. Ambient assisted living—AAL Google Scholar
  37. 37.
    Mayer P, Panek P (2012) Assessing daily activity of older persons in a real life AAL system. In: Hamza MH (ed) Proceedings of the IASTED international conference telehealth (Telehealth 2012), Innsbruck, Austria, 15–17 February 2012, pp 772–775. ISBN: 978-0-88986-909-7. doi: 10.2316/P.2012.765-012 Google Scholar
  38. 38.
    McCullagh PJ Devices and infrastructure to facilitate AAL (2012) Google Scholar
  39. 39.
    Meyer S (2011) Mein Freund der Roboter. Servicerobotik für ältere Menschen – Eine Antwort auf den demographischen Wandel Google Scholar
  40. 40.
    MOVEMENT website (2012). www.aat.tuwien.ac.at/fortec/reha.e/projects/movement/index.html. Accessed 15 August 2012
  41. 41.
    Nani M, Caleb-Solly P, Dogramadzi S, Fear T, van den Heuvel H (2010) MOBISERV: an integrated intelligent home environment for the provision of health. nutrition and mobility services to the elderly Google Scholar
  42. 42.
    Norman DA (2002) The design of everyday things. Basic Books, New York Google Scholar
  43. 43.
    Oberzaucher J, Werner F, Lemberger J, Werner K (2013) Formative evaluation of SAR in a real environment. KSERA deliverable: D5.3, January 2013. http://ksera.ieis.tue.nl/publications
  44. 44.
    Panek P, Edelmayer G, Mayer P, Beck C, Rauhala M (2012) User acceptance of a mobile LED projector on a socially assistive robot. In: Ambient assisted living. Springer, Berlin, pp 77–91 CrossRefGoogle Scholar
  45. 45.
    Pantelopoulos A, Bourbakis NG (2010) A survey on wearable sensor-based systems for health monitoring and prognosis. systems, man, and cybernetics. Part C. Applications and reviews. IEEE Trans Syst Man Cybern, Part A, Syst Hum 40(1):1–12 CrossRefGoogle Scholar
  46. 46.
    Pea RD (1987) User centered system design: new perspectives on human-computer interaction. J Educ Comput Res 3:129–134 Google Scholar
  47. 47.
    Pineau J, Montemerlo M, Pollack M, Roy N, Thrun S (2003) Towards robotic assistants in nursing homes: challenges and results. Robot Auton Syst 42(3):271–281 CrossRefzbMATHGoogle Scholar
  48. 48.
    Rauhala M (2007) Ethics and assistive technology design for vulnerable users: a case study. Stakes, Helsinki Google Scholar
  49. 49.
    Rauhala M (2009) Ethical dimensions in the involvement of older end users in technology R&D projects. In: Geyer G, Goebel R, Zimmermann K (eds) Innovative ICT solutions for older persons—a new understanding. Proc of the AAL forum 09 Vienna. OCG, Wien Google Scholar
  50. 50.
    Rauhala M (2011) When ethical guidance is missing and do-it-yourself is required: the shaping of ethical peer review guidance in the FRR project. In: A friendly rest room: developing toilets of the future for disabled and elderly people. IOS Press, Amsterdam, pp 27, 49 Google Scholar
  51. 51.
    Syrdal DS, Koay KL, Walters ML, Dautenhahn K (2007) A personalized robot companion? The role of individual differences on spatial preferences in HRI scenarios. In: The 16th IEEE international symposium on robot and human interactive communication (RO-MAN 2007). IEEE Press, New York, pp 1143–1148. doi: 10.1109/ROMAN.2007.4415252 CrossRefGoogle Scholar
  52. 52.
    Tapus A, Mataric MJ, Scassellati B (2007) Socially assistive robotics. IEEE Robot Autom Mag 14(1):35. doi:  10.1109/MRA.2007.339605 CrossRefGoogle Scholar
  53. 53.
    Torta E, Cuijpers RH, Juola JF (2012) Dynamic neural field as framework for behaviour coordination in mobile robots. In: World automation congress (WAC), 2012. IEEE Press, New York, pp 1–6 Google Scholar
  54. 54.
    Torta E, Cuijpers RH, Juola JF, van der Pol D (2011) Design of robust robotic proxemic behaviour. In: Social robotics. Springer, Berlin, pp 21–30. doi: 10.1007/978-3-642-25504-53(10.1007/978-3-642-25504-53) CrossRefGoogle Scholar
  55. 55.
    Torta E, Cuijpers RH, Juola J, van der Pol D (2012) Modeling and testing proxemic behavior for humanoid robots. Int J Humanoid Robot 9(4):1250028. doi: 10.1142/S0219843612500284 CrossRefGoogle Scholar
  56. 56.
    Torta E, Oberzaucher J, Werner F, Cuijpers RH, Juola JF (2012) The attitude toward socially assistive robots in intelligent homes: results from laboratory studies and field trials. Int J Hum-Comput Interact 1(2):76–99 Google Scholar
  57. 57.
    van der Pol D, Cuijpers RH, Juola JF (2010) Head pose estimation for real-time low-resolution video. In: Proceedings of the 28th annual European conference on cognitive ergonomics. ACM, New York, pp 353–354 Google Scholar
  58. 58.
    van der Pol D, Cuijpers RH, Juola JF (2011) Head pose estimation for a domestic robot. In: Proceedings of the 6th international conference on human-robot interaction. ACM, New York, pp 277–278 Google Scholar
  59. 59.
    van Dijk DJ, Isken M, Vester B, Winkler F, Cruz ME, O‘Donnovan K, Remazeilles A, Laval M et al (2010) State of the art of multi-purpose robots and privacy-aware AAL home services, deliverable: D2.1, Florence consortium Google Scholar
  60. 60.
    Walker W, Lamere P, Kwok P, Raj B, Singh R, Gouvea E, Wolf P, Woelfel J (2004) Sphinx-4: a flexible open source framework for speech recognition. Technical report, SMLI TR-2004-139, Sun Microsystems, Menlo Park, CA, USA Google Scholar
  61. 61.
    Wada K, Shibata T (2007) Living with seal robots—its sociopsychological and physiological influences on the elderly at a care house. IEEE Trans Robot 23(5):972–980. doi: 10.1109/TRO.2007.906261 CrossRefGoogle Scholar
  62. 62.
    Weiser M (1991) The computer for the 21st century. Sci Am 265(3):94–104 CrossRefGoogle Scholar
  63. 63.
    Werner F, Diermaier J, Schmid S, Panek P (2011) Fall detection with distributed floor-mounted accelerometers: an overview of the development and evaluation of a fall detection system within the project eHome. In: 2011 5th international conference on pervasive computing technologies for healthcare (PervasiveHealth). IEEE Press, New York, pp 354–361 Google Scholar
  64. 64.
    Yan W, Torta E, van der Pol D, Meins N, Weber C, Cuijpers RH, Wermter S (2012) Learning robot vision for assisted living. In: García-Rodríguez J, Cazorla M (eds) Robotic vision: technologies for machine learning and vision applications. IGI Global, Hershey, pp 257–280 Google Scholar
  65. 65.
    Yan W, Weber C, Wermter S (2011) A hybrid probabilistic neural model for person tracking based on a ceiling-mounted camera. J Ambient Intell Smart Environ 3(3):237–252 Google Scholar
  66. 66.
    Yan W, Weber C, Wermter S (2011) Person tracking based on a hybrid neural probabilistic model. In: Artificial neural networks and machine learning (ICANN 2011). Springer, Berlin, pp 365–372 CrossRefGoogle Scholar
  67. 67.
    Yan W, Weber C, Wermter S (2012) A neural approach for robot navigation based on cognitive map learning. In: The 2012 international joint conference on neural networks (IJCNN). IEEE Press, New York, pp 1–8 CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • David O. Johnson
    • 1
    Email author
  • Raymond H. Cuijpers
    • 1
  • James F. Juola
    • 1
  • Elena Torta
    • 1
  • Mikhail Simonov
    • 2
  • Antonella Frisiello
    • 2
  • Marco Bazzani
    • 2
  • Wenjie Yan
    • 3
  • Cornelius Weber
    • 3
  • Stefan Wermter
    • 3
  • Nils Meins
    • 3
  • Johannes Oberzaucher
    • 4
  • Paul Panek
    • 5
  • Georg Edelmayer
    • 5
  • Peter Mayer
    • 5
  • Christian Beck
    • 5
  1. 1.Human Technology InteractionEindhoven University of TechnologyEindhovenThe Netherlands
  2. 2.Istituto Superiore Mario BoellaTorinoItaly
  3. 3.Department of InformaticsUniversity of HamburgHamburgGermany
  4. 4.CEIT RALTECInstitute of Rehabilitation and Assisted Living TechnologiesSchwechatAustria
  5. 5.Vienna University of TechnologyViennaAustria

Personalised recommendations