A Prospective Fuzzy Logic approach to Knowledge-based Navigation of Mobile LEGO-Robot

The development of techniques for knowledge-based navigation constitutes one of the major trends in the current research on mobile robotics. Fuzzy logic provides tools that are of potential interest to mobile robot control. Most applications of fuzzy logic in this field concern the use of fuzzy control techniques to implement individual behavior units. In this paper we discuss how fuzzy logic computation techniques have been used in the mobile Lego robot for knowledgebased navigation. Also we implemented a robot that learns how to avoid obstacle using online selfadaptation. The outputs from each behaviour’s rule base are integrated using the command fusion process and made crisp using a modified defuzzification technique. The end result is very smooth motion control of the robot. The robot was built using the Lego RCX microcomputer and was designed with the subsumption architecture. We choose to implement the robot’s brain using the Lego RCX due to the lower cost.