An Embedded Genetic Fuzzy Motion Controller for a Mobile Robot

In this paper, an embedded genetic fuzzy motion control system is developed for autonomous navigation and obstacle avoidance of a mobile robot built in the ARIS Lab. A combination of four infrared sensors is equipped to measure the distance to obstacles around the mobile robot. The distance information is processed by the proposed genetic fuzzy controller to adjust the velocities of two separately-driven wheels of the robot. Here the fuzzy logic is used to process the sensor information generating the control commends; and the genetic algorithm is exploited to tune the membership functions of the fuzzy rules. Local search techniques are utilised to enhance the tuning process. The proposed motion controller has been applied on the mobile robot. Experiments have demonstrated the effectiveness of the developed genetic fuzzy controller. Copyright c ©2005 IFAC.