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
fDate :
4/1/1997 12:00:00 AM
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;
Journal_Title :
Industrial Electronics, IEEE Transactions on
