Fuzzy Representations and Control for Domestic Service Robots in Golog

  • Stefan Schiffer
  • Alexander Ferrein
  • Gerhard Lakemeyer
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7102)


In the RoboCup@Home domestic service robot competition, complex tasks such as “get the cup from the kitchen and bring it to the living room” or “find me this and that object in the apartment” have to be accomplished. At these competitions the robots may only be instructed by natural language. As humans use qualitative concepts such as “near” or “far”, the robot needs to cope with them, too. For our domestic robot, we use the robot programming and plan language Readylog, our variant of Golog. In previous work we extended the action language Golog, which was developed for the high-level control of agents and robots, with fuzzy concepts and showed how to embed fuzzy controllers in Golog. In this paper, we demonstrate how these notions can be fruitfully applied to two domestic service robotic scenarios. In the first application, we demonstrate how qualitative fluents based on a fuzzy set semantics can be deployed. In the second program, we show an example of a fuzzy controller for a follow-a-person task.


Rule Base Fuzzy Controller Reference Object Qualitative Representation Domestic Environment 
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  1. 1.
    Boutilier, C., Reiter, R., Soutchanski, M., Thrun, S.: Decision-theoretic, high-level agent programming in the situation calculus. In: Proc. 17th Nat’l Conf. on Artificial Intelligence (AAAI 2000), pp. 355–362 (2000)Google Scholar
  2. 2.
    Clementini, E., Felice, P.D., Hernandez, D.: Qualitative representation of positional information. Artificial Intelligence 95(2), 317–356 (1997)MathSciNetCrossRefzbMATHGoogle Scholar
  3. 3.
    De Giacomo, G., Lésperance, Y., Levesque, H.J.: ConGolog, A concurrent programming language based on situation calculus. Artificial Intelligence 121(1–2), 109–169 (2000)MathSciNetCrossRefzbMATHGoogle Scholar
  4. 4.
    Ferrein, A., Lakemeyer, G.: Logic-based robot control in highly dynamic domains. Robotics and Autonomous Systems, Special Issue on Semantic Knowledge in Robotics 56(11), 980–991 (2008)CrossRefGoogle Scholar
  5. 5.
    Ferrein, A., Schiffer, S., Lakemeyer, G.: A Fuzzy Set Semantics for Qualitative Fluents in the Situation Calculus. In: Xiong, C.-H., Liu, H., Huang, Y., Xiong, Y.L. (eds.) ICIRA 2008. LNCS (LNAI), vol. 5314, pp. 498–509. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  6. 6.
    Ferrein, A., Schiffer, S., Lakemeyer, G.: Embedding fuzzy controllers into golog. In: Proc. IEEE Int’l Conf. on Fuzzy Systems (FUZZ IEEE 2009), pp. 894–899 (2009)Google Scholar
  7. 7.
    Grosskreutz, H.: Probabilistic projection and belief update in the pGOLOG framework. In: Proceedings of the 2nd Cognitive Robotics Workshop (CogRob 2000) at the 14th European Conference on Artificial Intelligence (ECAI 2000), pp. 34–41 (2000)Google Scholar
  8. 8.
    Grosskreutz, H., Lakemeyer, G.: cc-Golog – An Action Language with Continuous Change. Logic Journal of the IGPL 11(2), 179–221 (2003)CrossRefzbMATHGoogle Scholar
  9. 9.
    Levesque, H.J., Reiter, R., Lespérance, Y., Lin, F., Scherl, R.B.: Golog: A logic programming language for dynamic domains. J. Logic Program 31(1-3), 59–84 (1997)MathSciNetCrossRefzbMATHGoogle Scholar
  10. 10.
    McCarthy, J.: Situations, actions and causal laws. TR. Stanford University (1963)Google Scholar
  11. 11.
    Reiter, R.: Knowledge in Action. Logical Foundations for Specifying and Implementing Dynamical Systems. MIT Press (2001)Google Scholar
  12. 12.
    Wisspeintner, T., van der Zant, T., Iocchi, L., Schiffer, S.: Robocup@home: Scientific Competition and Benchmarking for Domestic Service Robots. Interaction Studies. Special Issue on Robots in the Wild 10(3), 392–426 (2009)Google Scholar
  13. 13.
    van der Zant, T., Wisspeintner, T.: RoboCup X: A Proposal for a New League Where Robocup Goes Real World. In: Bredenfeld, A., Jacoff, A., Noda, I., Takahashi, Y. (eds.) RoboCup 2005. LNCS (LNAI), vol. 4020, pp. 166–172. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  14. 14.
    van der Zant, T., Wisspeintner, T.: Robotic Soccer. In: RoboCup@Home: Creating and Benchmarking Tomorrows Service Robot Applications, pp. 521–528. I-Tech Education and Publishing (2007)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Stefan Schiffer
    • 1
  • Alexander Ferrein
    • 1
  • Gerhard Lakemeyer
    • 1
  1. 1.Knowledge Based Systems GroupRWTH Aachen UniversityAachenGermany

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