Navigation system and obstacle avoidance for mobile robot using Type-2 fuzzy logic in uncertain environments

     This paper introduces a reactive navigation strategy for wheeled mobile robots, utilizing type-2 fuzzy logic to manage uncertainty in dynamic environments. The approach incorporates two distinct type-2 fuzzy logic controllers, each tailored to address specific challenges in navigation. The first controller focuses on steering the robot toward its target by continuously adjusting its path in response to changing conditions. The second controller specializes in obstacle avoidance, enabling the robot to detect and maneuver around obstacles it encounters during its journey.      To evaluate the performance of the system, numerical simulations are carried out across various scenarios, including dynamic and cluttered environments, to demonstrate its robustness. Additionally, the results of the type-2 fuzzy logic approach are compared with conventional navigation techniques, such as rule-based or model-based methods. The comparison underscores the system’s greater adaptability and resilience. The study concludes that type-2 fuzzy logic provides an effective and flexible solution, significantly improving both path planning and real-time decision-making in unpredictable and complex environments.