DocumentCode :
380568
Title :
A biologically inspired learning to grasp system
Author :
Oztop, E. ; Arbib, M.A.
Author_Institution :
Dept. of Comput. Sci., Univ. of Southern California, Los Angeles, CA, USA
Volume :
1
fYear :
2001
fDate :
2001
Firstpage :
857
Abstract :
We propose and implement a learning to grasp system inspired from the development of reaching and grasping in infants, and the neurophysiology of the monkey premotor cortex. The system is composed of a virtual 19 DOF kinematics arm/hand and a learning mechanism that enables it to perform a successful grasp. The learning is based on "motor babbling". The model performs open hand reaches to the vicinity of the targets, which human infants younger than 4 moths of age appear to do. The contact of the hand with the object triggers an enclosure of the hand simulating the palmer reflex, characteristic to infants that are younger than 6 months of age. The varying degree of enclosure of each finger and the randomness in the reaching phase enables the system to explore the grasp configuration space. The learning scheme employed is a Hebbian one.
Keywords :
Hebbian learning; Jacobian matrices; biocontrol; biomimetics; feedforward; haptic interfaces; inverse problems; learning systems; manipulator kinematics; mechanoception; virtual reality; Hebbian learning; Jacobian pseudo-inverse; Java language; forward kinematics; grasp configuration space; grasp planning; grasping; haptic feedback; hybrid neural control circuit; hybrid system; infants; inverse kinematics problem; learning to grasp system; monkey premotor cortex neurophysiology; motor babbling; open hand reaches; palmer reflex; premotor functionality; proprioceptive feedback; reaching; somatosensory cortex; virtual 19 DOF kinematics arm/hand; virtual fingers; Brain modeling; Computer science; Fingers; Grasping; Humans; Kinematics; Learning systems; Neurons; Neurophysiology; Pediatrics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society, 2001. Proceedings of the 23rd Annual International Conference of the IEEE
ISSN :
1094-687X
Print_ISBN :
0-7803-7211-5
Type :
conf
DOI :
10.1109/IEMBS.2001.1019077
Filename :
1019077
Link To Document :
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