Synergistic neural models of a robot sensor for part orientation detection
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE, cilt.210, sa.1, ss.69-76, 1996 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 210 Sayı: 1
- Basım Tarihi: 1996
- Doi Numarası: 10.1243/pime_proc_1996_210_087_02
- Dergi Adı: PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
- Sayfa Sayıları: ss.69-76
- Gazi Üniversitesi Adresli: Hayır
Özet
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.