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, United States Of America, 29 October - 02 November 2007, pp.2083-2084 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume:
  • Doi Number: 10.1109/iros.2007.4399494
  • City: California
  • Country: United States Of America
  • Page Numbers: pp.2083-2084
  • Hacettepe University Affiliated: Yes

Abstract

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.