Fuzzy Logic User Adaptive Navigation Control System For Mobile Robots In Unknown Environments

This paper presents a software implementation of a user adaptive fuzzy control system for autonomous navigation in mobile robots for unknown environments. This system has been tested in a pioneer mobile robot and on a robotic wheelchair, fitted with PLS laser sensor to detect the obstacles and odometry sensors for localization of robots and the goal positions. The system is able to drive the robots to their goal position avoiding static and dynamic obstacles, without using any pre-built map. Our approach learn from user behaviors in the way it can resolve different situations against obstacles or walls.We propose and implement two updates for the fuzzy system. For the implementation of the learning algorithm we use a weighting scheme giving a value for each fuzzy-rule, this value is based on the synapse-weight idea and represent the contribution of each rule in the system output. We also create of a more important sector in the definition of the fuzzy-variables, based on a statistics system that measure the uses of all the sets of the variables in order to contract the size of the rule-base.