Abstract
In this article, we discuss implementation phases for an autonomous navigation of a mobile robotic system using SLAM gathered data, while relying on the features of learned navigation maps. The adopted SLAM based learned maps, was relying entirely on an active stereo vision for observing features of the navigation environment. We show the framework for the used lower-level software coding, that was necessary once a vision is used for multiple purposes, distance measurements, and obstacle discovery. In addition, the article describes the adopted upper-level of system intelligence using fuzzy based decision system. The proposed map based fuzzy autonomous navigation was trained from data patterns gathered during numerous navigation tasks. Autonomous navigation was further validated and verified on a mobile robot platform. (C) 2015 The Authors. Published by Elsevier B.V.