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

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 real- world 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.