International Science and Technology Journal

An independent mobile robot is created through the design and development of an intelligent controller that can steer and enable the robot to move through a real - world environment, avoiding obstacles that are both structured and unstructured, especially in crowded and dynamic environments that may be found on land , underground , above water , in the air or in space. When faced with an uncertain situation, an intelligent system can choose an appropriate course of action that will boost its chances of success. Success is defined as achieving behavioral sub goals that would help it reach its main objective. This study investigates fuzzy logic-based navigation techniques for mobile robots with a large number- up to 1,000 robots -in an uncharted terrain. Mobile robot navigation is accomplished by Fuzzy Logic Controllers (FLC) that employ a variety of membership functions. First , a fuzzy controller was used, with three parameters for each type, there are 4 distinct types of input members, 2 distinct types of output members, and four distinct types of output members . The following two varieties of fuzzy controllers were created and they each contain five parameters and the identical input and output members. A variety of ultrasonic sensors are installed on each robot to gauge the distances of objects in its immediate vicinity and an infrared sensor to determine the target's bearing. Through a series of exercises, these approaches have been put to the test to show how well the robots can avoid impediments, find their way around obstacles and reach their goals. FLC with a Gaussian membership function is the method that has been determined to be the most effective for mobile robot navigation.In order to navigate a mobile robot in a tough crowded environment usingPetri Net Model for avoiding inter-robot collision , this study developed an intelligent controller using fuzzy theory . The efficiency of the controllers was confirmed by the simulation results. The present study concludes that the fuzzy logic controller with Gaussian membership is the best of the three strategies for multiple mobile robot navigation. Key words : Fuzzy Logic Controllers , mobile robot , navigation