Abstract
A hierarchical neurocontroller architecture consisting of two artificial neural network systems for the manipulation of a robotic arm is presented. The higher-level network system participates in the delineation of the robot arm workspace and coordinates transformation and the motion decision-making process. The lower-level network provides the correct sequence of control actions. A straightforward example illustrates the architecture''s capabilities, including speed, adaptability, and computational efficiency
Recommended Citation
X. J. Avula and L. C. Rabelo, "Hierarchical Neurocontroller Architecture for Robotic Manipulation," IEEE Control Systems Magazine, Institute of Electrical and Electronics Engineers (IEEE), Jan 1992.
The definitive version is available at https://doi.org/10.1109/37.126851
Meeting Name
41st IAS Annual Meeting of the Industry Applications Conference, 2006
Department(s)
Chemical and Biochemical Engineering
Keywords and Phrases
Adaptability; Computational Efficiency; Computational Speed; Control Action Sequence; Coordinates Transformation; Hierarchical Neurocontroller Architecture; Hierarchical Systems; Motion Decision-Making Process; Neural Nets; Neural Networks; Parallel Architectures; Robot Arm Workspace Delineation; Robotic Arm; Robotic Manipulation; Robots
International Standard Serial Number (ISSN)
0272-1708
Document Type
Article - Journal
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 1992 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Publication Date
01 Jan 1992
