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Intelligent navigation and control of a mobile robot in static and dynamic environments using hybrid fuzzy architecture

Navigation and obstacle avoidance are one of the most important tasks for any mobile robot. This article proposes the design and implementation of a hybrid fuzzy (H-fuzzy) architecture for intelligent navigation of a mobile robot in the static and dynamic environments. The proposed H-fuzzy architecture is the combination of Takagi-Sugeno type and Mamdani-type fuzzy logics, which helps the mobile robot to reach the goal with obstacle avoidance. The Takagi-Sugeno type fuzzy logic architecture (TFa) is used to assist the robot to reach the goal. The inputs of the Takagi-Sugeno type fuzzy logic architecture are obstacle distances received from the group of sensors, and the output is the turning angle between the robot and the goal. The Mamdani-type fuzzy logic architecture (MFa) is integrated with the TFa to control the motor velocities of the robot. Computer simulations are conducted through MATLAB software and implemented in real time by using Arduino microcontroller based wheeled mobile robot. Moreover, the successful experimental results on the actual mobile robot demonstrate the superiority of the proposed architecture.