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This paper describes intelligent navigation using an embedded interval type-2 neuro-fuzzy controller. Weightless neural network (WNNs) strategy is used because fast learning, easy hardware implementation and well suited to microcontroller-based-real-time systems. The WNNs utilizes previous sensor data and analyzes the situation of the current environment and classifies geometric feature such as U-shape,...
This paper describes environmental recognition and motion control using weightless neural network classifier and interval type-2 fuzzy logic controller. The weightless neural network classifies geometric feature such as U-shape, corridor and left or right corner using ultrasonic sensors. The neural network utilizes previous sensor data and analyzes the situation of the current environment. The behavior...
Reactive autonomous mobile robot navigating in real time environment is one of the most important requirements. Most of the systems have some common drawbacks such as, large computation, expensive equipment, hard implementation, and the complexity of the system. The work presented in this paper deals with a type-2 fuzzy-neural controller using RAM-based network to make navigation decisions. The proposed...
This paper presents a type-2 fuzzy logic controller that has been applied to a mobile robot utilizing eight ultrasonic sensors as distance sensors. The inputs are obtained from the mounted ultrasonic sensors and sent to a microchip PIC16F84 microcontroller onboard the robot. Furthermore the PIC16F84 analyses the inputs as data and provides the necessary control signal. The controller, which based...
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