[go: up one dir, main page]

Skip to main content

Human Behavior Understanding for Robotics

  • Conference paper
Human Behavior Understanding (HBU 2012)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 7559))

Included in the following conference series:

Abstract

Human behavior is complex, but structured along individual and social lines. Robotic systems interacting with people in uncontrolled environments need capabilities to correctly interpret, predict and respond to human behaviors. This paper discusses the scientific, technological and application challenges that arise from the mutual interaction of robotics and computational human behavior understanding. We supply a short survey of the area to provide a contextual framework and describe the most recent research in this area.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 49.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Abbeel, P., Ng, A.Y.: Apprenticeship learning via inverse reinforcement learning. In: Proceedings of the 21st International Conference on Machine Learning (ICML 2004), pp. 1–8 (2004)

    Google Scholar 

  2. Andry, P., Gaussier, P., Nadel, J., Hirsbrunner, B.: From sensori-motor development to low-level imitation. Adaptive Behavior 12, 117–138 (2004)

    Article  Google Scholar 

  3. Arbib, M.A., Fellous, J.M.: Emotions: from brain to robot. Trends in Cognitive Sciences 8(12), 554–561 (2004)

    Article  Google Scholar 

  4. Argall, B.D., Chernova, S., Veloso, M., Browning, B.: A survey of robot learning from demonstration. Robotics and Autonomous Systems 57(5), 469–483 (2009)

    Article  Google Scholar 

  5. Asada, M., Hosoda, K., Kuniyoshi, Y., Ishiguro, H., Inui, T., Yoshikawa, Y., Ogino, M., Yoshida, C.: Cognitive developmental robotics: A survey. IEEE Trans. Autonomous Mental Development 1(1) (2009)

    Google Scholar 

  6. Billard, A., Calinon, S., Dillmann, R., Schaal, S.: Survey: Robot programming by demonstration. In: Handbook of Robotics, ch. 59 (2008)

    Google Scholar 

  7. Breazeal, C.: Emotion and sociable humanoid robots. International Journal of Human-Computer Studies 59(1-2), 119–155 (2003)

    Article  Google Scholar 

  8. Breazeal, C.: Toward sociable robots. Robotics and Autonomous Systems 42(3), 167–175 (2003)

    Article  MATH  Google Scholar 

  9. Breazeal, C., Buchsbaum, D., Gray, J., Gatenby, D., Blumberg, B.: Learning from and about others: Towards using imitation to bootstrap the social understanding of others by robots. Artificial Life 11(1-2), 31–62 (2005)

    Article  Google Scholar 

  10. Brooks, A.G., Gray, J., Hoffman, G., Lockerd, A., Lee, H., Breazeal, C.: Robot’s play: interactive games with sociable machines. Computers in Entertainment (CIE) 2(3), 1–10 (2004)

    Article  Google Scholar 

  11. Calinon, S., Guenter, F., Billard, A.: On learning, representing and generalizing a task in a humanoid robot. IEEE Transactions on Systems, Man and Cybernetics, Part B 37(2), 286–298 (2007)

    Article  Google Scholar 

  12. Cederborg, T., Li, M., Baranes, A., Oudeyer, P.-Y.: Incremental local inline gaussian mixture regression for imitation learning of multiple tasks. In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, Taipei, Taiwan (2010)

    Google Scholar 

  13. Çeliktutan, O., Wolf, C., Sankur, B., Lombardi, E.: Real-Time Exact Graph Matching with Application in Human Action Recognition. In: Salah, A.A., Ruiz-del Solar, J., Meriçli, Ç., Oudeyer, P.-Y. (eds.) HBU 2012. LNCS, vol. 7559, pp. 17–28. Springer, Heidelberg (2012)

    Google Scholar 

  14. Chaaraoui, A.A., Climent-Pérez, P., Flórez-Revuelta, F.: An Efficient Approach for Multi-view Human Action Recognition Based on Bag-of-Key-Poses. In: Salah, A.A., Ruiz-del Solar, J., Meriçli, Ç., Oudeyer, P.-Y. (eds.) HBU 2012. LNCS, vol. 7559, pp. 29–40. Springer, Heidelberg (2012)

    Google Scholar 

  15. Dautenhahn, K., Werry, I.: Towards interactive robots in autism therapy: Background, motivation and challenges. Pragmatics & Cognition 12(1), 1–35 (2004)

    Article  Google Scholar 

  16. Fasola, J., Matarić, M.J.: Robot exercise instructor: A socially assistive robot system to monitor and encourage physical exercise for the elderly. In: 19th IEEE International Symposium in Robot and Human Interactive Communication, Viareggio, Italy, pp. 416–421 (September 2010)

    Google Scholar 

  17. Feil-Seifer, D., Matarić, M.J.: Defining socially assistive robotics. In: 9th International Conference on Rehabilitation Robotics, ICORR 2005, pp. 465–468. IEEE (2005)

    Google Scholar 

  18. Fischer, K., Saunders, J.: Between Initial Expectations and Acquaintance: Interacting with a Developing Robot. In: Salah, A.A., Ruiz-del Solar, J., Meriçli, Ç., Oudeyer, P.-Y. (eds.) HBU 2012. LNCS, vol. 7559, pp. 125–133. Springer, Heidelberg (2012)

    Google Scholar 

  19. Gobbini, M.I., Koralek, A.C., Bryan, R.E., Montgomery, K.J., Haxby, J.V.: Two takes on the social brain: A comparison of theory of mind tasks. Journal of Cognitive Neuroscience 19(11), 1803–1814 (2007)

    Article  Google Scholar 

  20. Grollman, D.H., Jenkins, O.C.: Sparse incremental learning for interactive robot control policy estimation. In: International Conference on Robotics and Automation (ICRA 2008), pp. 3315–3320 (May 2008)

    Google Scholar 

  21. Guizzo, E., Deyle, T.: Robotics trends for 2012 (the future is robots). IEEE Robot. Automat. Mag. 19(1), 119–123 (2012)

    Article  Google Scholar 

  22. Heider, F., Simmel, M.: An experimental study of apparent behavior. The American Journal of Psychology 57(2), 243–259 (1944)

    Article  Google Scholar 

  23. Hu, N., Englebienne, G., Kröse, B.: Bayesian Fusion of Ceiling Mounted Camera and Laser Range Finder on a Mobile Robot for People Detection and Localization. In: Salah, A.A., Ruiz-del Solar, J., Meriçli, Ç., Oudeyer, P.-Y. (eds.) HBU 2012. LNCS, vol. 7559, pp. 41–51. Springer, Heidelberg (2012)

    Google Scholar 

  24. Huang, A.S., Tellex, S., Bachrach, A., Kollar, T., Roy, D., Roy, N.: Natural language command of an autonomous micro-air vehicle. In: Int. Conf. on Intelligent Robots and Systems (IROS), Taipei, Taiwan (October 2010)

    Google Scholar 

  25. Jenatton, R., Mairal, J., Obozinski, G., Bach, F.: Proximal Methods for Hierarchical Sparse Coding. Journal of Machine Learning Research 12, 2297–2334 (2011), http://hal.inria.fr/inria-00516723

    MathSciNet  Google Scholar 

  26. Jenkins, O.C., Matarić, M.J., Weber, S.: Primitive-based movement classification for humanoid imitation. In: IEEE International Conference on Humanoid Robots, Humanoids 2000 (2000)

    Google Scholar 

  27. Kaplan, F., Oudeyer, P.-Y.: The progress-drive hypothesis: an interpretation of early imitation. In: Dautenhahn, K., Nehaniv, C. (eds.) Imitation and Social Learning in Robots, Humans and Animals: Behavioural, Social and Communicative Dimensions. Cambridge University Press (2007)

    Google Scholar 

  28. Karreman, D.E., Evers, V., van Dijk, E.M.A.G.: Contextual Analysis of Human Non-verbal Guide Behaviors to Inform the Development of FROG, the Fun Robotic Outdoor Guide. In: Salah, A.A., Ruiz-del Solar, J., Meriçli, Ç., Oudeyer, P.-Y. (eds.) HBU 2012. LNCS, vol. 7559, pp. 113–124. Springer, Heidelberg (2012)

    Google Scholar 

  29. Kollar, T., Tellex, S., Roy, D., Roy, N.: Toward understanding natural language directions. In: Proceedings of the 5th ACM/IEEE International Conference on Human-Robot Interaction, HRI 2010, pp. 259–266. IEEE Press, Piscataway (2010), http://dl.acm.org/citation.cfm?id=1734454.1734553

    Chapter  Google Scholar 

  30. Kozima, H., Michalowski, M.P., Nakagawa, C.: Keepon: A playful robot for research, therapy, and entertainment. International Journal of Social Robotics 1(1), 3–18 (2009)

    Article  Google Scholar 

  31. Krüger, V., Herzog, D., Baby, S., Ude, A., Kragic, D.: Learning actions from observations. IEEE Robot. Automat. Mag. 17(2), 30–43 (2010)

    Article  Google Scholar 

  32. Kulić, D., Nakamura, Y.: Incremental Learning of Full Body Motion Primitives. In: Sigaud, O., Peters, J. (eds.) From Motor Learning to Interaction Learning in Robots. SCI, vol. 264, pp. 383–406. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  33. Laptev, I.: On space-time interest points. International Journal of Computer Vision 64(2), 107–123 (2005)

    Article  MathSciNet  Google Scholar 

  34. Lim, A., Okuno, H.G.: Using Speech Data to Recognize Emotion in Human Gait. In: Salah, A.A., Ruiz-del Solar, J., Meriçli, Ç., Oudeyer, P.-Y. (eds.) HBU 2012. LNCS, vol. 7559, pp. 52–64. Springer, Heidelberg (2012)

    Google Scholar 

  35. Lopes, M., Oudeyer, P.-Y.: Active learning and intrinsically motivated exploration in robots: Advances and challenges (guest editorial). IEEE Transactions on Autonomous Mental Development 2(2), 65–69 (2010)

    Article  Google Scholar 

  36. Lopes, M., Melo, F., Montesano, L., Santos-Victor, J.: Abstraction Levels for Robotic Imitation: Overview and Computational Approaches. In: Sigaud, O., Peters, J. (eds.) From Motor Learning to Interaction Learning in Robots. SCI, vol. 264, pp. 313–355. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  37. Lopes, M., Melo, F., Montesano, L.: Active Learning for Reward Estimation in Inverse Reinforcement Learning. In: Buntine, W., Grobelnik, M., Mladenić, D., Shawe-Taylor, J. (eds.) ECML PKDD 2009, Part II. LNCS, vol. 5782, pp. 31–46. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  38. Mancini, M., Varni, G., Glowinski, D., Volpe, G.: Computing and Evaluating the Body Laughter Index. In: Salah, A.A., Ruiz-del Solar, J., Meriçli, Ç., Oudeyer, P.-Y. (eds.) HBU 2012. LNCS, vol. 7559, pp. 90–98. Springer, Heidelberg (2012)

    Google Scholar 

  39. Mangin, O., Oudeyer, P.-Y.: Learning the Combinatorial Structure of Demonstrated Behaviors with Inverse Feedback Control. In: Salah, A.A., Ruiz-del Solar, J., Meriçli, Ç., Oudeyer, P.-Y. (eds.) HBU 2012. LNCS, vol. 7559, pp. 135–147. Springer, Heidelberg (2012)

    Google Scholar 

  40. Mangin, O., Oudeyer, P.-Y.: Learning to recognize parallel combinations of human motion primitives with linguistic descriptions using non-negative matrix factorization. To Appear in IEEE/RSJ International Conference on Intelligent Robots and Systems (2012)

    Google Scholar 

  41. Matarić, M.J.: Sensory-motor primitives as a basis for learning by imitation:linking perception to action and biology to robotics. In: Imitation in Animals and Artifacts. MIT Press (2002)

    Google Scholar 

  42. Meriçli, Ç., Veloso, M., Akın, H.L.: Improving biped walk stability with complementary corrective demonstration. Autonomous Robots 32(4), 419–432 (2012), http://dx.doi.org/10.1007/s10514-012-9284-1

    Article  Google Scholar 

  43. Michaud, F., Théberge-Turmel, C.: Mobile robotic toys and autism. Socially Intelligent Agents, 125–132 (2002)

    Google Scholar 

  44. Michelet, S., Karp, K., Delaherche, E., Achard, C., Chetouani, M.: Automatic Imitation Assessment in Interaction. In: Salah, A.A., Ruiz-del Solar, J., Meriçli, Ç., Oudeyer, P.-Y. (eds.) HBU 2012. LNCS, vol. 7559, pp. 161–173. Springer, Heidelberg (2012)

    Google Scholar 

  45. Nehaniv, C.: Nine billion correspondence problems. In: Dautenhahn, K., Nehaniv, C. (eds.) Imitation and Social Learning in Robots, Humans and Animals: Behavioural, Social and Communicative Dimensions. Cambridge University Press (2007)

    Google Scholar 

  46. Nehaniv, C.L., Dautenhahn, K. (eds.): Imitation and social learning in robots, humans, and animals: behavioural, social and communicative dimensions. Cambridge University Press (2004)

    Google Scholar 

  47. Poggi, I., D’Errico, F.: Social signals: a framework in terms of goals and beliefs. Cognitive Processing (2012)

    Google Scholar 

  48. Poppe, R.: A survey on vision-based human action recognition. Image and Vision Computing 28(6), 976–990 (2010)

    Article  Google Scholar 

  49. Ratliff, N., Bagnell, J., Zinkevich, M.: Maximum margin planning. In: Proc. 23rd Int. Conf. Machine Learning, pp. 729–736 (2006)

    Google Scholar 

  50. Rosenthal, S., Biswas, J., Veloso, M.: An effective personal mobile robot agent through symbiotic human-robot interaction. In: International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2010), vol. 1, pp. 915–922 (May 2010)

    Google Scholar 

  51. Rosenthal, S., Veloso, M.M., Dey, A.K.: Acquiring accurate human responses to robots’ questions. I. J. Social Robotics 4(2), 117–129 (2012)

    Article  Google Scholar 

  52. Rosenthal, S., Veloso, M.M., Dey, A.K.: Is someone in this office available to help me? - proactively seeking help from spatially-situated humans. Journal of Intelligent and Robotic Systems 66(1-2), 205–221 (2012)

    Article  Google Scholar 

  53. Salah, A., Schouten, B.: Semiosis and the relevance of context for the AmI environment. In: Proc. European Conf. on Computing and Philosophy (2009)

    Google Scholar 

  54. Salah, A.A., Gevers, T., Sebe, N., Vinciarelli, A.: Computer vision for ambient intelligence. Journal of Ambient Intelligence and Smart Environments 3(3), 187–191 (2011)

    Google Scholar 

  55. Salah, A.A., Pantic, M., Vinciarelli, A.: Recent developments in social signal processing. In: 2011 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp. 380–385. IEEE (2011)

    Google Scholar 

  56. Salah, A.A., Gevers, T., Sebe, N., Vinciarelli, A.: Challenges of Human Behavior Understanding. In: Salah, A.A., Gevers, T., Sebe, N., Vinciarelli, A. (eds.) HBU 2010. LNCS, vol. 6219, pp. 1–12. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  57. Salah, A.A., Lepri, B., Pianesi, F., Pentland, A.: Human Behavior Understanding for Inducing Behavioral Change: Application Perspectives. In: Salah, A.A., Lepri, B. (eds.) HBU 2011. LNCS, vol. 7065, pp. 1–15. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  58. Samadani, A.-A., Gorbet, R., Kulić, D.: Gender Differences in the Perception of Affective Movements. In: Salah, A.A., Ruiz-del Solar, J., Meriçli, Ç., Oudeyer, P.-Y. (eds.) HBU 2012. LNCS, vol. 7559, pp. 65–76. Springer, Heidelberg (2012)

    Google Scholar 

  59. Schaal, S., Ijspeert, A., Billard, A.: Computational approaches to motor learning by imitation. Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences 358(1431), 537–547 (2003)

    Article  Google Scholar 

  60. Schaal, S., Peters, J., Nakanishi, J., Ijspeert, A.: Learning movement primitives. In: International Symposium on Robotics Research, ISRR 2003 (2003)

    Google Scholar 

  61. Schillaci, G., Lara, B., Hafner, V.: Internal Simulations for Behaviour Selection and Recognition. In: Salah, A.A., Ruiz-del Solar, J., Meriçli, Ç., Oudeyer, P.-Y. (eds.) HBU 2012. LNCS, vol. 7559, pp. 148–160. Springer, Heidelberg (2012)

    Google Scholar 

  62. Schouten, B.A.M., Tieben, R., van de Ven, A., Schouten, D.W.: Human Behavior Analysis in Ambient Gaming and Playful Interaction. In: Salah, A.A., Gevers, T. (eds.) Computer Analysis of Human Behavior, pp. 387–403. Springer-Verlag London Limited (2011)

    Google Scholar 

  63. Sheikhi, S., Odobez, J.-M.: Recognizing the Visual Focus of Attention for Human Robot Interaction. In: Salah, A.A., Ruiz-del Solar, J., Meriçli, Ç., Oudeyer, P.-Y. (eds.) HBU 2012. LNCS, vol. 7559, pp. 99–112. Springer, Heidelberg (2012)

    Google Scholar 

  64. Stuckler, J., Holz, D., Behnke, S.: Robocup@home: Demonstrating everyday manipulation skills in robocup@home. IEEE Robotics Automation Magazine 19(2), 34–42 (2012)

    Article  Google Scholar 

  65. Tellex, S., Kollar, T., Dickerson, S., Walter, M.R., Banerjee, A.G., Teller, S., Roy, N.: Understanding natural language commands for robotic navigation and mobile manipulation. In: Proceedings of the National Conference on Artificial Intelligence (AAAI) (August 2011)

    Google Scholar 

  66. Thomaz, A.L., Breazeal, C.: Teachable robots: Understanding human teaching behavior to build more effective robot learners. Artificial Intelligence Journal 172, 716–737 (2008)

    Article  Google Scholar 

  67. Verma, D., Rao, R.: Goal-based imitation as probabilistic inference over graphical models. In: Advances in NIPS 18 (2006)

    Google Scholar 

  68. Vincze, L., Poggi, I., D’Errico, F.: Vagueness and Dreams. Analysis of Body Signals in Vague Dream Telling. In: Salah, A.A., Ruiz-del Solar, J., Meriçli, Ç., Oudeyer, P.-Y. (eds.) HBU 2012. LNCS, vol. 7559, pp. 77–89. Springer, Heidelberg (2012)

    Google Scholar 

  69. Yücel, Z., Salah, A.A., Meriçli, Ç., Meriçli, T.: Joint visual attention modeling for naturally interacting robotic agents. In: 24th International Symposium on Computer and Information Sciences, ISCIS 2009 (2009)

    Google Scholar 

  70. Ziemke, T., Lowe, R.: On the role of emotion in embodied cognitive architectures: From organisms to robots. Cognitive Computation 1(1), 104–117 (2009)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Salah, A.A., Ruiz-del-Solar, J., Meriçli, Ç., Oudeyer, PY. (2012). Human Behavior Understanding for Robotics. In: Salah, A.A., Ruiz-del-Solar, J., Meriçli, Ç., Oudeyer, PY. (eds) Human Behavior Understanding. HBU 2012. Lecture Notes in Computer Science, vol 7559. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34014-7_1

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-34014-7_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-34013-0

  • Online ISBN: 978-3-642-34014-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics