DocumentCode
296914
Title
Neural networks in robotics: state of the art
Author
Tzafestas, Spyros G.
Author_Institution
Dept. of Electr. & Comput. Eng., Nat. Tech. Univ. of Athens, Greece
Volume
1
fYear
34881
fDate
10-14 Jul1995
Firstpage
12
Abstract
This paper provides a short review of the neural network approach to system control with reference to robotic systems. Starting with an exposition of the main neurocontrol architectures, the paper overviews the literature on the application of neural networks to robot kinematics, dynamics, path planning and motion control, including some work on neurofuzzy control. To appreciate better robot neurocontrol, an unsupervised robot neurocontroller is presented in some detail. The paper includes a discussion of the criticism made to the neural control paradigms, and an outline of some interesting areas for further research
Keywords
fuzzy control; fuzzy neural nets; motion control; neurocontrollers; path planning; robot dynamics; robot kinematics; unsupervised learning; application; motion control; neural network; neurocontrol architectures; neurofuzzy control; path planning; robot dynamics; robot kinematics; robotic systems; state-of-the-art; unsupervised control; Adaptive control; Automatic control; Biological neural networks; Control systems; Humans; Intelligent networks; Intelligent robots; Neural networks; Neurocontrollers; Neurons;
fLanguage
English
Publisher
ieee
Conference_Titel
Industrial Electronics, 1995. ISIE '95., Proceedings of the IEEE International Symposium on
Conference_Location
Athens
Print_ISBN
0-7803-7369-3
Type
conf
DOI
10.1109/ISIE.1995.496471
Filename
496471
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