Intelligent Service Robotics

, Volume 5, Issue 4, pp 259–273 | Cite as

Caesar: an intelligent domestic service robot

  • Stefan SchifferEmail author
  • Alexander Ferrein
  • Gerhard Lakemeyer
Special Issue


In this paper we present Caesar, an intelligent domestic service robot. In domestic settings for service robots complex tasks have to be accomplished. Those tasks benefit from deliberation, from robust action execution and from flexible methods for human–robot interaction that account for qualitative notions used in natural language as well as human fallibility. Our robot Caesar deploys AI techniques on several levels of its system architecture. On the low-level side, system modules for localization or navigation make, for instance, use of path-planning methods, heuristic search, and Bayesian filters. For face recognition and human–machine interaction, random trees and well-known methods from natural language processing are deployed. For deliberation, we use the robot programming and plan language Readylog, which was developed for the high-level control of agents and robots; it allows combining programming the behaviour using planning to find a course of action. Readylog is a variant of the robot programming language Golog. We extended Readylog to be able to cope with qualitative notions of space frequently used by humans, such as “near” and “far”. This facilitates human–robot interaction by bridging the gap between human natural language and the numerical values needed by the robot. Further, we use Readylog to increase the flexible interpretation of human commands with decision-theoretic planning. We give an overview of the different methods deployed in Caesar and show the applicability of a system equipped with these AI techniques in domestic service robotics.


Domestic service robotics Situation calculus Golog Decision-theoretic planning Qualitative spatial representation Reasoning Cognitive robotics Fuzzy sets 



This work would not have been possible without the continuous efforts of the members of the AllemaniACs RoboCup Team, namely Tobias Baumgartner, Daniel Beck, Vaishak Belle, Masrur Doostdar, Niklas Hoppe, Bahram Maleki-Fard, Tim Niemüller, Christoph Schwering, Andreas Wortmann and others. We gratefully acknowledge partly funding for this research by the German National Science Foundation (DFG) under grants La 747/9-1, 2 and 5 and by the NRW Ministry of Education and Research (MSWF). We also thank the anonymous reviewers for their helpful comments on earlier versions of this paper.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Stefan Schiffer
    • 1
    Email author
  • Alexander Ferrein
    • 2
  • Gerhard Lakemeyer
    • 1
  1. 1.Knowledge Based Systems GroupRWTH Aachen UniversityAachenGermany
  2. 2.FH Aachen University of Applied SciencesAachenGermany

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