DocumentCode :
2655651
Title :
Goal directed model inversion
Author :
Colombano, Silvano P. ; Compton, Michael ; Bualat, Maria
Author_Institution :
NASA-Ames Res. Center, Moffett Field, CA, USA
fYear :
1991
fDate :
18-21 Nov 1991
Firstpage :
2422
Abstract :
A new neural network technique for model inversion called goal directed model inversion (GDM) is presented. It allows the system to produce an inverse model in a goal directed manner. The major advantage of an inverse model created in this matter is that it can adapt to unexpected changes in the system with which it must interact. As an example of the GDMI technique, a simple kinematic controller was built for a simulated robotic arm with three degrees of freedom. The system was trained by presenting a sequence of goals of increasing difficulty in some required region of space. As the controller was trained, its ability to extrapolate correct control actions to new distant goals increased
Keywords :
controllers; kinematics; learning systems; neural nets; robots; goal directed model inversion; kinematic controller; neural network technique; simulated robotic arm; training; unexpected changes; Bridges; Error correction; Inverse problems; Neural networks; Orbital robotics; Position measurement; Robot kinematics; Sampling methods; Supervised learning; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1991. 1991 IEEE International Joint Conference on
Print_ISBN :
0-7803-0227-3
Type :
conf
DOI :
10.1109/IJCNN.1991.170751
Filename :
170751
Link To Document :
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