A novel soft-computing technique to segment satellite images for mobile robot localization and navigation

DOĞRUER C. U., Koku B., DÖLEN M.

IEEE/RSJ International Conference on Intelligent Robots and Systems, California, Amerika Birleşik Devletleri, 29 Ekim - 02 Kasım 2007, ss.2083-2084 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası:
  • Doi Numarası: 10.1109/iros.2007.4399494
  • Basıldığı Şehir: California
  • Basıldığı Ülke: Amerika Birleşik Devletleri
  • Sayfa Sayıları: ss.2083-2084
  • Hacettepe Üniversitesi Adresli: Evet

Özet

Localization of mobile robots has been studied rigorously in the last decade. A number of successful approaches such as Extended Kalman Filter, Markov Localization, and Monte Carlo Localization assume that the map of the environment is originally presented to the robot. However, an important information package like the map of the environment could not be taken for granted in most realworld problems. In this study, a novel technique composed of a combination of Fuzzy C-Means and Fuzzy Neural Network methods is proposed to segment and convert a satellite image into a digital map for outdoor mobile robot applications.