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The Review of Socionetwork Strategies

, Volume 12, Issue 1, pp 71–96 | Cite as

PRINTEPS: An Integrated Intelligent Application Development Platform based on Stream Reasoning and ROS

  • Takeshi Morita
  • Kodai Nakamura
  • Hiroki Komatsushiro
  • Takahira Yamaguchi
Article
  • 79 Downloads

Abstract

Although AI and service robot applications have become very popular in many domains recently, many of them are specific applications and it is still difficult to develop integrated intelligent applications such as a robot teahouse and teaching assistant robots. To develop such integrated intelligent applications, we need integrated intelligent application platforms that have AI integration and agile process facilities. From the above background, we are currently developing PRactical INTElligent aPplicationS (PRINTEPS), which is a platform for developing integrated intelligent applications by combining only five types of modules, namely knowledge-based reasoning, spoken dialogue, image sensing, motion management, and machine learning. This paper proposes a workflow editor in PRINETPS based on a service-oriented architecture and a Robot Operating System that enables real-time parallel processing for multiple robots and sensors by integrating the five types of modules. The editor also supports not only developers but also domain experts in updating workflows frequently. This paper also proposes a novel method to integrate signals acquired through image sensing with knowledge (ontologies and business rules) using C-SPARQL and Semantic Web Rule Language. To evaluate PRINTEPS, we developed a robot teahouse application including customer reception and guidance to table services using a humanoid robot with PRINTEPS. Through this case study, we demonstrated that the behaviors of the robot can be modified by changing the workflow, the ontology, and the rules.

Keywords

Ontology ROS Stream reasoning PRINTEPS 

Notes

Acknowledgements

We are grateful to Prof. Hideo Saito, Dr. Yuko Ozasa, and Mr. Yusuke Nakayama for implementing the image-processing modules, to Mr. Yu Sugawara and Mr. Daiki Marukawa for implementing the knowledge modules, to Prof. Yukiko Nakano and Dr. Ryota Nishimura for implementing the spoken dialogue system and modules, and to Prof. Masaki Takahashi, Dr. Anaynori Yorozu, and Mr. Jun Kurosu  for implementing the motion management modules. We are also grateful to North Grid corporation for implementing the workflow editor. This work was supported by JST CREST Grant Number JPMJCR14E3, Japan.

References

  1. 1.
    Printeps web site. (2016). http://printeps.org/
  2. 2.
    Barbieri, D. F., Braga, D., Ceri, S., Della Valle, E., & Grossniklaus, M. (2010). C-SPARQL: A continuous query language for RDF data streams. International Journal of Semantic Computing, 4(1), 3–25.  https://doi.org/10.1142/S1793351X10000936.CrossRefGoogle Scholar
  3. 3.
    Boyer, J., & Mili, H. (2011). Agile business rule development: Process, architecture, and JRules examples. Berlin: Springer.  https://doi.org/10.1007/978-3-642-19041-4.CrossRefGoogle Scholar
  4. 4.
    Chen X, Ji J, Jiang J, Jin G, Wang F, Xie J (2010) Developing high-level cognitive functions for service robots. AAMASGoogle Scholar
  5. 5.
    Choi, D., Ha, J., Jung, M., Park, W., & Park, H. (2015). Development of robot scenario script language and tool for non-expert. Journal of Automation and Control Engineering, 3(6), 498–502.CrossRefGoogle Scholar
  6. 6.
    Datta C, Jayawardena C, Kuo IH, MacDonald BA (2012) RoboStudio—a visual programming environment for rapid authoring and customization of complex services on a personal service robot. IROSGoogle Scholar
  7. 7.
    Della Valle, E., Ceri, S., van Harmelen, F., & Fensel, D. (2009). It’s a streaming world! Reasoning upon rapidly changing information. IEEE Intelligent Systems, 24(6), 83–89.CrossRefGoogle Scholar
  8. 8.
    Fowler, M. (2010). Domain specific languages (1st ed.). Boston: Addison-Wesley.Google Scholar
  9. 9.
    Hertzberg, J., Jianwei, Z., Zhang, L., Rockel, S., Neumann, B., Lehmann, J., et al. (2014). The RACE project–robustness by autonomous competence enhancement. KI, 28(4), 297–304.Google Scholar
  10. 10.
    Krafzig, D., Banke, K., & Slama, D. (2004). Enterprise SOA: Service-oriented architecture best practices (the Coad series). Upper Saddle River: Prentice Hall.Google Scholar
  11. 11.
    Lemaignan, S., Warnier, M., Sisbot, E. A., Clodic, A., & Alami, R. (2016). Artificial cognition for social human–robot interaction: An implementation. Artificial Intelligence, 247, 45–69.CrossRefGoogle Scholar
  12. 12.
    Nishimura R, Takase Y, Nakano Y (2016) Development environment of spoken dialogue system based on PRINTEPS. The 30th annual conference of the Japanese Society for Artificial Intelligence, 4C4-2 (in Japanese) Google Scholar
  13. 13.
    Pot E, Monceaux J, Gelin R, Maisonnier B (2009) Choregraphe: A graphical tool for humanoid robot programming. In: RO-MAN 2009—The 18th IEEE international symposium on robot and human interactive communication, IEEE, pp 46–51Google Scholar
  14. 14.
    Quigley M, Conley K, Gerkey BP, Faust J, Foote T, Leibs J, Wheeler R, Ng AY (2009) ROS: An open-source robot operating system. In: ICRA workshop on open source softwareGoogle Scholar
  15. 15.
    Tenorth, M., & Beetz, M. (2013). Knowrob: A knowledge processing infrastructure for cognition-enabled robots. International Journal of Robotics Research, 32(5), 566–590.  https://doi.org/10.1177/0278364913481635.CrossRefGoogle Scholar
  16. 16.
    Waibel, M., Beetz, M., Civera, J., D’Andrea, R., Elfring, J., Galvez-Lopez, D., et al. (2011). Roboearth—a world wide web for robots. IEEE Robotics and Automation Magazine, 18(2), 69–82.  https://doi.org/10.1109/Mra.2011.941632.CrossRefGoogle Scholar
  17. 17.
    Yamaguchi T (2015) A platform printeps to develop practical intelligent applications. In: Adjunct proceedings of the 2015 ACM international joint conference on pervasive and ubiquitous computing and proceedings of the 2015 ACM international symposium on wearable computers, ACM, UbiComp/ISWC’15 Adjunct, pp 919–920.  https://doi.org/10.1145/2800835.2815383
  18. 18.
    Zander, S., Heppner, G., Neugschwandtner, G., Awad, R., Essinger, M., & Ahmed, N. (2016). A model-driven engineering approach for ROS using ontological semantics. CoRR cs.RO.Google Scholar

Copyright information

© Springer Japan KK, part of Springer Nature 2018

Authors and Affiliations

  • Takeshi Morita
    • 1
  • Kodai Nakamura
    • 1
  • Hiroki Komatsushiro
    • 1
  • Takahira Yamaguchi
    • 1
  1. 1.Keio UniversityYokohamaJapan

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