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EnglishThis paper describes a novel approach to robotic haptic recognition, which exploits an unsupervised Kohonen self-organizing feature map for performing a match-to-sample classification of three-dimensional (3-D) objects. The results obtained, even though currently referring to a simulated environment and to some working assumptions, have emphasized the validity of the approach and its applicability in a variety of dextrous robotic systems.
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| Titolo: | A neural approach to robotich haptic Recognition of 3-D objects based on a Kohonen self-organizing feature map |
| Autori: | |
| Data di pubblicazione: | 1997 |
| Rivista: | |
| Abstract: | This paper describes a novel approach to robotic haptic recognition, which exploits an unsupervis...ed Kohonen self-organizing feature map for performing a match-to-sample classification of three-dimensional (3-D) objects. The results obtained, even though currently referring to a simulated environment and to some working assumptions, have emphasized the validity of the approach and its applicability in a variety of dextrous robotic systems. |
| Handle: | http://hdl.handle.net/11391/952593 |
| Appare nelle tipologie: | 1.1 Articolo in rivista |
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