DocumentCode
1385443
Title
A neural approach to robotic haptic recognition of 3-D objects based on a Kohonen self-organizing feature map
Author
Faldella, E. ; Fringuelli, B. ; Passeri, D. ; Rosi, L.
Author_Institution
Dept. of Electron., Comput. & Syst. Sci., Bologna Univ., Italy
Volume
44
Issue
2
fYear
1997
fDate
4/1/1997 12:00:00 AM
Firstpage
267
Lastpage
269
Abstract
This 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
Keywords
image classification; object recognition; robots; self-organising feature maps; unsupervised learning; 3-D object recognition; dextrous robotic systems; match-to-sample classification; neural approach; robotic haptic recognition; simulated environment; unsupervised Kohonen self-organizing feature map; Analytical models; Haptic interfaces; Information analysis; Iron; Neural networks; Object recognition; Probes; Robot sensing systems; Robot vision systems; Solid modeling;
fLanguage
English
Journal_Title
Industrial Electronics, IEEE Transactions on
Publisher
ieee
ISSN
0278-0046
Type
jour
DOI
10.1109/41.564167
Filename
564167
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