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A Software System for Robotic Learning by Experimentation

  • Iman Awaad
  • Ronny Hartanto
  • Beatriz León
  • Paul Plöger
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5325)

Abstract

The goal of this work is to develop an integration framework for a robotic software system which enables robotic learning by experimentation within a distributed and heterogeneous setting. To meet this challenge, the authors specified, defined, developed, implemented and tested a component-based architecture called XPERSIF. The architecture comprises loosely-coupled, autonomous components that offer services through their well-defined interfaces and form a service-oriented architecture. The Ice middleware is used in the communication layer. Additionally, the successful integration of the XPERSim simulator into the system has enabled simultaneous quasi-realtime observation of the simulation by numerous, distributed users.

Keywords

Cognitive Architecture Simple Object Access Protocol Autonomous Component Robot Learning Overhead Camera 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Iman Awaad
    • 1
  • Ronny Hartanto
    • 1
  • Beatriz León
    • 2
  • Paul Plöger
    • 1
  1. 1.Bonn-Rhein-Sieg University of Applied ScienceSankt AugustinGermany
  2. 2.Universitat Jaume ICastellon de la PlanaSpain

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