Self-Organizing Maps for Supervision in Robot Pick-And-Place Operations

  • Enrique Cervera
  • Angel P. del Pobil
Conference paper


A scheme for supervised learning based on multiple self-organizing maps (SOMs) is presented, and its application to robotic tasks, namely pick-and-place operations, is outlined. The advantage of this multiple organization is that the learning method is simplified because the problem is divided into several SOMs, which are trained in the standard unsupervised way. The resulting network preserves the SOM properties like dimensionality reduction and cluster formation, and its classification performance is comparable to other supervised methods like backpropagation networks.


Supervise Learning Supervise Method Supervise Learning Method Bayesian Classification Robotic Task 
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  1. 1.
    Kohonen, T.: Biol. Cybern. 43, 59, 1982.MathSciNetMATHCrossRefGoogle Scholar
  2. 2.
    Cervera, E., del Pobil, A.P., Marta, E., Serna, M.A.: Unsupervised Learning for Error Detection in Task Planning, Computer Science Dept. Tech Report, Jaume I University, 1994.Google Scholar
  3. 3.
    Devijver, P.A., Kittler, J.: Pattern recognition: A statistical approach. London: Prentice Hall 1982.MATHGoogle Scholar
  4. 4.
    Hertz, J., Krogh, A., Palmer, R.G.: Introduction to the Theory of Neural Computation. Addison-Wesley 1991.Google Scholar
  5. 5.
    Kurimo, K.: Proc. IEEE Workshop on Neural Networks for Signal Processing, 362, 1994.Google Scholar
  6. 6.
    Naylor, J., Higgins, A, Li, K.P., Schmoldt, D.: Neural Networks, 1, 311, 1988.CrossRefGoogle Scholar
  7. 7.
    Kohonen, T., Barna, G., Chrisley, R.: Proceedings of the IEEE International Conference on Neural Networks, San Diego, 1, 61, 1988.Google Scholar

Copyright information

© Springer-Verlag/Wien 1995

Authors and Affiliations

  • Enrique Cervera
    • 1
  • Angel P. del Pobil
    • 1
  1. 1.Computer Science Dept.Jaume I UniversityCastellóSpain

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