Share Email Print

Proceedings Paper

Artificial Neural-Net Based Intelligent Robotics Control
Author(s): Yoh-Han Pao; Dejan J. Sobajic
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Fast real-time intelligent control of dynamic systems can be implemented with a combination of logic-based (higher level) strategies and automatic reflexive pattern driven responses generated with artificial neural-nets (ANN). In this paper we are concerned with the adaptive control of a robot manipulator with two degrees of freedom. The objective is to move the end effector of a two limbed manipulator towards a target point until the positions of two coincide. The task is to generate the control signals for movement of the arm through the use of ANN. Control algorithm is computationally simple and robust due to the exploitation of highly parallel information processing capabilities of multilayered neural-nets. Feasibility of obstacle avoidance is discussed also. The proposed approach was evaluated with a computer simulation. A feedforward neural-net was used for this purpose. The results are presented and discussed in this paper.

Paper Details

Date Published: 19 February 1988
PDF: 8 pages
Proc. SPIE 0848, Intelligent Robots and Computer Vision VI, (19 February 1988); doi: 10.1117/12.942801
Show Author Affiliations
Yoh-Han Pao, Case Western Reserve University (United States)
Dejan J. Sobajic, Case Western Reserve University (United States)

Published in SPIE Proceedings Vol. 0848:
Intelligent Robots and Computer Vision VI
David P. Casasent; Ernest L. Hall, Editor(s)

© SPIE. Terms of Use
Back to Top