Hierarchical neurocontroller architecture for robotic manipulation

Author

Rabelo, Luis C. ; Avula, Xavier J R

Author_Institution

Dept. of Ind. & Syst. Eng., Ohio Univ., Athens, OH, USA

Volume

12

Issue

2

fYear

1992

fDate

4/1/1992 12:00:00 AM

Firstpage

37

Lastpage

41

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.<>

Keywords

hierarchical systems; neural nets; parallel architectures; robots; adaptability; computational efficiency; computational speed; control action sequence; coordinates transformation; hierarchical neurocontroller architecture; motion decision-making process; neural nets; robot arm workspace delineation; robotic arm; robotic manipulation; Artificial neural networks; Computational modeling; Decision making; Manipulators; Neural networks; Neurocontrollers; Robot control; Robot kinematics; Service robots; Temperature;

fLanguage

English

Journal_Title

Control Systems, IEEE

Publisher

ieee

ISSN

1066-033X

Type

jour

DOI

10.1109/37.126851

Filename

126851