Artificial Neural Networks For Robotics Coordinate Transformation

Author

Stephen Aylor
Luis Rabelo
Sema Alptekin, Missouri University of Science and Technology

Abstract

Artificial neural networks with such characteristics as learning, graceful degradation, and speed inherent to parallel distributed architectures might provide a flexible and cost solution to the real time control of robotics systems. In this investigation artificial neural networks are presented for the coordinate transformation mapping of a two-axis robot modeled with Fischertechnik physical modeling components. The results indicate that artificial neural systems could be utilized for practical situations and that extended research in these neural structures could provide adaptive architectures for dynamic robotics control. © 1992.

Recommended Citation

S. Aylor et al., "Artificial Neural Networks For Robotics Coordinate Transformation," Computers and Industrial Engineering, vol. 22, no. 4, pp. 481 - 493, Elsevier, Jan 1992.

The definitive version is available at https://doi.org/10.1016/0360-8352(92)90023-D

Department(s)

Engineering Management and Systems Engineering

International Standard Serial Number (ISSN)

0360-8352

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2023 Elsevier, All rights reserved.

Publication Date

01 Jan 1992