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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.
| Author: | Rüdiger W. BrauseGND |
|---|---|
| URN: | urn:nbn:de:hebis:30-79687 |
| ISSN: | 1432-9611 |
| 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 |
| Language: | English |
| 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 |
| HeBIS-PPN: | 228359945 |
| Institutes: | Informatik und Mathematik / Informatik |
| Dewey Decimal Classification: | 0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik |
| Sammlungen: | Universitätspublikationen |
| Licence (German): |  Deutsches Urheberrecht |
