Combining Finite State Machine and Decision-Making Tools for Adaptable Robot Behavior

  • Michalis Foukarakis
  • Asterios Leonidis
  • Margherita Antona
  • Constantine Stephanidis
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8515)


Modeling robot behavior is a common task in robot software development. However, its difficulty grows exponentially along with system complexity. To facilitate the development of a modular, rather than monolithic, behavior system, proper software tools need to be introduced. This paper proposes combination of a well-known finite state machine and a custom decision-making tool for implementing adaptive robot behaviors. The notion of automatic behavior adaptation reflects the capability of the robot to adapt during runtime based on the individual end-user, as well as the particular context of use, therefore delivering the most appropriate interaction experience. While each tool on its own can be used towards that aim, a unified approach that combines them simplifies the task at hand and distinguishes the roles of designers and programmers. To demonstrate the methods’ applicability, a concrete example of their combined use is presented.


State Machine Adaptation Behavior Decision-Making 


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Michalis Foukarakis
    • 1
  • Asterios Leonidis
    • 1
  • Margherita Antona
    • 1
  • Constantine Stephanidis
    • 1
    • 2
  1. 1.Institute of Computer ScienceFoundation for Research and Technology – Hellas (FORTH)HeraklionGreece
  2. 2.Department of Computer ScienceUniversity of CreteGreece

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