Topology-conserving maps for learning visuo-motor-coordination

Helge J. Ritter, Thomas M. Martinetz, Klaus J. Schulten

Research output: Contribution to journalArticlepeer-review


We investigate the application of an extension of Kohonen's self-organizing mapping algorithm to the learning of visuo-motor-coordination of a simulated robot arm. We show that both arm kinematics and arm dynamics can be learned, if a suitable representation for the map output is used. Due to the topology-conserving property of the map spatially neighboring neurons can learn cooperatively, which greatly improves the robustness and the convergence properties of the algorithm.

Original languageEnglish (US)
Pages (from-to)159-168
Number of pages10
JournalNeural Networks
Issue number3
StatePublished - 1989
Externally publishedYes


  • Learning
  • Motor control
  • Robotics
  • Topology-conserving maps
  • Visuo-motor-coordination

ASJC Scopus subject areas

  • Artificial Intelligence
  • General Neuroscience


Dive into the research topics of 'Topology-conserving maps for learning visuo-motor-coordination'. Together they form a unique fingerprint.

Cite this