Synergistic neural models of a robot sensor for part orientation detection


Pham D., SAĞIROĞLU Ş.

PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE, vol.210, no.1, pp.69-76, 1996 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 210 Issue: 1
  • Publication Date: 1996
  • Doi Number: 10.1243/pime_proc_1996_210_087_02
  • Title of Journal : PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE
  • Page Numbers: pp.69-76

Abstract

This paper describes the use of neural networks to compute the orientation of a part from the output signals of an inertial sensor which is a device for determining the location of parts by measuring their inertial parameters. The paper investigates an approach for increasing the accuracy of the computed orientation. This involves employing a group of neural networks and combining their outputs. The paper presents the results obtained for several neural network combinations. These show that the accuracy achieved in a combined system is higher than that of its individual components provided the number of components is not too large.