Vision-Based Mobile Robot Map Building and Environment Fuzzy Learning

Abstract

This article describes an AI related procedure to learn the environment and the navigation map for the KSU-IMR (King Saud University-Intelligent Mobile Robotic) system. Beforehand, navigation was routed based wholly on the mobile visual sensory inputs (3D vision). After learning, the mobile robot undertakes the most suitable action while navigating, this is after it found the most suitable route after learning the navigation map. Successful computer routines are used to serve such purposes, resulting on learning maps of occupancy grids while relying on stereo vision SLAM based navigation.