Robot navigation system with obstacle: avoidance in uncertain environment using Type 2 Fuzzy Logic

This paper presents a fuzzy logic-based reactive navigation strategy for wheeled mobile robots operating in uncertain environments. The proposed approach incorporates two type-2 fuzzy logic controllers, each designed to handle different aspects of navigation. The first controller focuses on guiding the robot to its desired target configuration by adjusting its path dynamically. The second controller is dedicated to obstacle avoidance, enabling the robot to detect and navigate around obstacles in its path. Numerical tests are conducted across various scenarios, including cluttered and dynamic environments, to assess the performance of the system. The paper also compares the results of the fuzzy logic-based approach with traditional navigation techniques, such as rule-based or model-based methods, highlighting its superior adaptability and robustness. The findings demonstrate the effectiveness of the fuzzy logic system in enhancing both path planning and real-time decision-making, offering a more flexible solution for mobile robot navigation in unpredictable and complex environments.