Performance and storage requirements of topology-conserving maps for robot manipulator control

  • A new programming paradigm for the control of a robot manipulator by learning the mapping between the Cartesian space and the joint space (inverse Kinematic) is discussed. It is based on a Neural Network model of optimal mapping between two high-dimensional spaces by Kohonen. This paper describes the approach and presents the optimal mapping, based on the principle of maximal information gain. It is shown that Kohonens mapping in the 2-dimensional case is optimal in this sense. Furthermore, the principal control error made by the learned mapping is evaluated for the example of the commonly used PUMA robot, the trade-off between storage resources and positional error is discussed and an optimal position encoding resolution is proposed.

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Author:Rüdiger W. BrauseGND
Parent Title (German):Universität Frankfurt am Main. Fachbereich Informatik: Interner Bericht ; 89,5
Series (Serial Number):Interner Bericht / Fachbereich Informatik, Johann Wolfgang Goethe-Universität Frankfurt a.M. (89, 05)
Document Type:Working Paper
Year of Completion:1989
Year of first Publication:1989
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Release Date:2010/09/15
GND Keyword:Roboter; Selbstorganisierende Karte; Speicherbedarf
Institutes:Informatik und Mathematik / Informatik
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Licence (German):License LogoDeutsches Urheberrecht