Abstract
An architecture which utilizes two artificial neural systems for planning and control of a robotic arm is presented. The first neural network system participates in the trajectory planning and the motion decision-making process. The second neural network system provides the correct sequence of control actions with a high accuracy due to the utilization of an unsupervised/supervised neural network scheme. The utilization of a hybrid hierarchical/distributed organization, supervised/unsupervised learning models, and forward modeling yielded an architecture with capabilities of high level functionality.
Recommended Citation
X. J. Avula et al., "Planning and Control of a Robotic Manipulator Using Neural Networks," Proceedings of the First IEEE Conference on Control Applications, 1992, Institute of Electrical and Electronics Engineers (IEEE), Jan 1992.
The definitive version is available at https://doi.org/10.1109/CCA.1992.269858
Meeting Name
First IEEE Conference on Control Applications, 1992
Department(s)
Chemical and Biochemical Engineering
Keywords and Phrases
Distributed Control; Forward Modeling; Functionality; Hybrid Hierarchical/Distributed Organization; Learning (Artificial Intelligence); Motion Decision-Making Process; Neural Nets; Neural Networks; Path Planning; Robot Arm Control; Robotic Manipulator; Robots; Supervised/Unsupervised Learning Models; Trajectory Planning
Document Type
Article - Conference proceedings
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
