Abstract
Integrating the components described in the previous articles of this chapter, we introduce the Bielefeld “Curious Robot”, which is able to acquire new knowledge and skills in direct human-robot interaction. This paper focuses on the cognitive architecture of the overall system. We propose to combine (i) a communication layer based on a generic, human-accessible XML data format, (ii) multiple low-level sensor and control processes publishing their sensor information into the system and receiving commands or parameterizations from higher-level deliberative processes, and (iii) high-level coordination processes based on hierarchical state machines. The efficiency of the proposed approach is shown in an interactive tutoring scenario, where the Bielefeld “Curious Robot”, a bimanual robot system, should learn to identify, grasp, and clean various everyday objects from a table. The capability of the system to interact with lay persons is proven in a user study.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Allen, J.F.: Mixed-initiative interaction. IEEE Intelligent Systems 14(5), 14–23 (1999)
Bohus, D., Rudnicky, A.I.: The ravenclaw dialog management framework: Architecture and systems. Computer Speech & Language 23(3), 332–361 (2009)
Engelhardt, K.G., Edwards, R.A.: Human-robot integration for service robotics. In: Rahimi, M., Karwowski, W. (eds.) Human-Robot Interaction, pp. 315–346. Taylor & Francis Ltd. (1992)
Fink, G.A.: Developing HMM-Based Recognizers with ESMERALDA. In: Matoušek, V., Mautner, P., Ocelíková, J., Sojka, P. (eds.) TSD 1999. LNCS (LNAI), vol. 1692, pp. 229–234. Springer, Heidelberg (1999)
Fong, T., Thorpe, C., Baur, C.: Collaboration, dialogue, human-robot interaction. In: Advances in Telerobotics, pp. 255–266. Springer (2003)
Fong, T., Kunz, C., Hiatt, L.M., Bugajska, M.: The human-robot interaction operating system. In: HRI 2006: Proceedings of the 1st ACM SIGCHI/SIGART Conference on Human-Robot Interaction, pp. 41–48. ACM, New York (2006)
Furnas, G.W., Landauer, T.K., Gomez, L.M., Dumais, S.T.: The vocabulary problem in human-system communication. Commun. ACM 30(11), 964–971 (1987)
Hanheide, M., Sagerer, G.: Active memory-based interaction strategies for learning-enabling behaviors. In: International Symposium on Robot and Human Interactive Communication (RO-MAN), Munich (2008)
Hüwel, S., Wrede, B., Sagerer, G.: Robust speech understanding for multi-modal human-robot communication. In: Proc. 15th Int. Symposium on Robot and Human Interactive Communication, pp. 45–50. IEEE (2006)
Kim, T., Hinds, P.: Who should i blame? effects of autonomy and transparency on attributions in human-robot interaction. In: The 15th IEEE Interantional Symposium on Robot and Human Interactive Communication (RO-MAN 2006), pp. 80–85 (2006)
Kortenkamp, D., Simmons, R.: Robotic System Architectures and Programming, ch. 8, pp. 187–206. Springer (2008)
Lang, C., et al.: Feedback interpretation based on facial expressions in human–robot interaction. In: International Symposium on Robot and Human Interactive Communication (RO-MAN), pp. 189–194. IEEE, Toyama (2009)
Litman, D.J., Hirschberg, J.B., Swerts, M.: Predicting automatic speech recognition performance using prosodic cues. In: Proceedings of NAACL 2000, pp. 218–225 (2000)
Lütkebohle, I.: Coordination and composition patterns in the “curious robot” scenario. PhD thesis, Bielefeld University (in Press, 2011)
Lütkebohle, I., Peltason, J., Schillingmann, L., Elbrechter, C., Wrede, B., Wachsmuth, S., Haschke, R.: The Curious Robot - Structuring Interactive Robot Learning. In: International Conference on Robotics and Automation, Robotics and Automation Society. IEEE (2009)
Nagai, Y., Hosada, K., Morita, A., Asada, M.: A constructive model for the development of joint attention. Connection Science 15(4), 211–229 (2003)
Pohling, M.: Verhaltensweisen zur Steuerung der Blickrichtung eines humanoiden Roboters. Tech. rep., Bielefeld University, bachelor Thesis (2009)
Steels, L., Kaplan, F.: Aibo’s first words: The social learning of language and meaning. Evolution of Communication 4(1), 3–32 (2001)
Woods, S.N., Walters, M.L., Koay, K.L., Dautenhahn, K.: Methodological issues in HRI: A comparison of live and video-based methods in robot to human approach direction trials. In: Proceedings of the 15th IEEE International Symposium on Robot and Human Interactive Communication, pp. 51–58. IEEE (2006)
Wrede, S., Hanheide, M., Wachsmuth, S., Sagerer, G.: Integration and coordination in a cognitive vision system. In: International Conference on Computer Vision Systems (ICVS), IEEE, New York City (2006)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag GmbH Berlin Heidelberg
About this chapter
Cite this chapter
Lütkebohle, I. et al. (2012). A Mixed-Initiative Approach to Interactive Robot Tutoring. In: Prassler, E., et al. Towards Service Robots for Everyday Environments. Springer Tracts in Advanced Robotics, vol 76. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25116-0_34
Download citation
DOI: https://doi.org/10.1007/978-3-642-25116-0_34
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-25115-3
Online ISBN: 978-3-642-25116-0
eBook Packages: EngineeringEngineering (R0)